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Virtual Lockstep for Fault Tolerance and Architectural Vulnerability Analysis

Permanent Link: http://ufdc.ufl.edu/UFE0024343/00001

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Title: Virtual Lockstep for Fault Tolerance and Architectural Vulnerability Analysis
Physical Description: 1 online resource (166 p.)
Language: english
Creator: Jeffery, Casey
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: fault, injection, lockstep, reliability, tolerance, virtualization
Electrical and Computer Engineering -- Dissertations, Academic -- UF
Genre: Electrical and Computer Engineering thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: This dissertation presents a flexible technique that can be applied to commodity many-core architectures to exploit idle resources and ensure reliable system operation. The proposed system interposes a dynamically-adaptable fault tolerance layer between the hardware and the operating system through the use of a hypervisor. It avoids the introduction of a new single point of failure by incorporating the hypervisor into the sphere of replication. This approach greatly simplifies implementation over specialized hardware, operating system, or application-based techniques and offers significant flexibility in the type and degree of protection provided. The possible levels of protection considered range from duplex replication to arbitrary n-modular replication limited only by the number of processors in the system. The feasibility of the approach is considered for both near- and long-term computing platforms and a prototype is developed as a proof-of-concept and used to estimate the performance overhead and gather empirical data on fault tolerance capabilities. A fault detection latency reduction technique is also proposed and analyzed using the fault injection facilities provided by the prototype.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Casey Jeffery.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Figueiredo, Renato J.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024343:00001

Permanent Link: http://ufdc.ufl.edu/UFE0024343/00001

Material Information

Title: Virtual Lockstep for Fault Tolerance and Architectural Vulnerability Analysis
Physical Description: 1 online resource (166 p.)
Language: english
Creator: Jeffery, Casey
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: fault, injection, lockstep, reliability, tolerance, virtualization
Electrical and Computer Engineering -- Dissertations, Academic -- UF
Genre: Electrical and Computer Engineering thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: This dissertation presents a flexible technique that can be applied to commodity many-core architectures to exploit idle resources and ensure reliable system operation. The proposed system interposes a dynamically-adaptable fault tolerance layer between the hardware and the operating system through the use of a hypervisor. It avoids the introduction of a new single point of failure by incorporating the hypervisor into the sphere of replication. This approach greatly simplifies implementation over specialized hardware, operating system, or application-based techniques and offers significant flexibility in the type and degree of protection provided. The possible levels of protection considered range from duplex replication to arbitrary n-modular replication limited only by the number of processors in the system. The feasibility of the approach is considered for both near- and long-term computing platforms and a prototype is developed as a proof-of-concept and used to estimate the performance overhead and gather empirical data on fault tolerance capabilities. A fault detection latency reduction technique is also proposed and analyzed using the fault injection facilities provided by the prototype.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Casey Jeffery.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Figueiredo, Renato J.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024343:00001


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1 VIRTUAL LOCKSTEP FOR FAULT TOLERANCE AND ARCHITECTURAL VULNERABILITY ANALYSIS By CASEY M. JEFFERY A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2009

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2 2009 Casey M. Jeffery

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3 I dedicate this to my wife for her unwavering support.

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4 ACKNOWLEDGMENTS I must acknowledge my advisor Prof. Renato Figueiredo for everything he has done for me over the past six years I have learned a great deal from him both in the classroom and from our collaborat ions in various research and publication efforts. He is always available to provide direction and exhibits incredible patience and understanding He and Prof. Jos Fortes have done a great job in directing the Advanced Computer and Information Systems ( ACIS ) lab while encouraging the students to set high goals and then work hard to achieve them. I would like to acknowledge Steve Bennett, who helpe d me in getting my first internship with the Core Virtualization Research (CVR) group at Intel as well as Tariq Masood, who assist ed me in achieving my first success in virtual lockstep during that internship. I also must recognize Alain Kgi, Philip Lant z, Sebastian Schnberg, and my other coworkers in the CVR group. I undertook this virtual lockstep work and other research project s that required advanced system programming skills and knowledge of Intel x86 architecture, an d without their support would not have learned what I needed to be successful at them Finally, I would like to thank my family, who have no idea what I do but support me nevertheless. They are responsible for providing me with the necessary work ethic and continued encouragement to be successful at whatever I apply myself to. My wife, in particular, is always there for me at every step and has the benefit of knowing the path well, since she completed it herself.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ...............................................................................................................4 LIST OF TABLES ...........................................................................................................................8 LIST OF FIGURES .........................................................................................................................9 ABSTRACT ...................................................................................................................................12 1 INTRODUCTION ..................................................................................................................13 Motivation ...............................................................................................................................13 Device Reliability ............................................................................................................14 Many C ore Architectures ................................................................................................15 Virtualization Technology ...............................................................................................16 Overview and Scope ...............................................................................................................17 Contributions ...................................................................................................................19 Dissertation Overview .....................................................................................................20 2 BACKGROUND AND RELATED WORK ..........................................................................22 Terminology ...........................................................................................................................22 Fault Tolerance Basics ............................................................................................................22 Fault Tolerance thro ugh Redundancy .....................................................................................24 Redundancy .....................................................................................................................24 Hardware Redundancy .............................................................................................25 Data Redu ndancy .....................................................................................................26 Network Redundancy ...............................................................................................27 Replica Coordination .......................................................................................................29 Requirem ents for Replication ...................................................................................29 Forms of Replication ................................................................................................30 Group Communication and Membership .................................................................34 Related Work in Fault Tolerance ............................................................................................38 Hardware Fault Tolerance ...............................................................................................39 Processor Logic ........................................................................................................39 Memory and I/O Devices .........................................................................................41 Software Fault Tolerance ................................................................................................43 Instruction Set Architecture .....................................................................................43 Operating System .....................................................................................................45 Middleware ...............................................................................................................46 Application/Compiler ...............................................................................................47 Case Study: Stratus ftServer architecture ........................................................................48 Fault Injection ..................................................................................................................49 Many C or e Architectures .......................................................................................................51 Network on Chip Architectures ......................................................................................51

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6 Parallel Programming ......................................................................................................54 Virtualization and Logical Partitioning ..................................................................................54 Hardware Virtual Machines ............................................................................................55 Logical Partitioning .........................................................................................................57 3 PROPOSED FAULT TOLERANT ARCHITECTURE ........................................................61 Architecture Overview ............................................................................................................61 Replication Model Scope ................................................................................................61 Platform Partitioning and Virtualization .........................................................................62 Platform Monitoring ........................................................................................................66 Fault Model and Fault Tolerance Overview ...........................................................................66 Fault Models ....................................................................................................................66 Fault Tolerance Capabilities ............................................................................................68 Virtual Lockstep Overview .....................................................................................................72 Deterministic Execution ..................................................................................................72 Platform Partitioning Requireme nts ................................................................................74 Hypervisor Requirements ................................................................................................75 4 TEST PLATFORM OVERVIEW ..........................................................................................78 Sy stem Overview ....................................................................................................................78 KVM Hypervisor Overview ...................................................................................................80 KVM Components ...........................................................................................................81 KVM Implementation Details .........................................................................................83 Hardware Features and Limitations ........................................................................................84 Performance Counters .....................................................................................................85 Virtualization Hardware Extensions ................................................................................88 Interrupt Delivery ............................................................................................................89 Communication Infrastructure .........................................................................................90 Prototype Implementation Details ..........................................................................................90 Guest State Replication ...................................................................................................91 Guest Synchr onization .....................................................................................................92 Deterministic Execution ..................................................................................................93 Prototype Limitations .............................................................................................................96 Layered Virtualization ............................................................................................................97 5 RELIABILITY MODEL AND PERFORMANCE RESULTS ............................................100 Prototype Test Platform ........................................................................................................100 Replication and Synchronization Overhead .........................................................................104 Replication and Reintegration Costs .............................................................................104 Virt ual Lockstep Benefit Analysis ................................................................................109 Virtual Lockstep Performance Overhead ......................................................................114 6 FAULT INJECTION AND VIRTUAL PROCESSOR STATE FINGER PRINTING ........118 Fault Injection Model ...........................................................................................................118

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7 Fault Injection Details ...................................................................................................118 Fault Propagation Analysis ............................................................................................119 Processor State Comparisons ................................................................................................120 Virtual Processor State Fingerprinting ..........................................................................121 Hashing Details .............................................................................................................122 Fingerprinting Optimizations ........................................................................................123 KVM Prototype Fault Injection ............................................................................................124 Fault Injection Overview ...............................................................................................124 Fault Injection Performance Results .............................................................................126 Virtual Processor State Fingerprinting Results .............................................................137 7 SUMMARY AND FUTURE WORK ..................................................................................148 Summary ........................................................................................................................148 Future Work ...................................................................................................................150 APPENDIX: FINGERPRINTINGBASED FAULT DETECTION RESULTS ........................152 LIST OF REFEREN CES .............................................................................................................156 BIOGRAPHICAL SKETCH .......................................................................................................166

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8 LIST OF TABLES Table page 31 Replication configurat ion and capability summary. ..........................................................70 41 Prototype platform hardware and software specifications. ................................................80 51 Guest static snapshot replica tion size, image size, and state transfer time for a variety of guest operating systems. ..............................................................................................105 52 Definition of exit reason labels. .......................................................................................111 53 Virtual lockstep performance overhead summary. ..........................................................115 61 Hashing performance of various algorithms for a random 4KB page of memory. .........123 62 Fault injection target registers and their inclusion in the VMCS. ....................................125 63 Control register CR0 bit descriptions. .............................................................................129 64 Control register CR3 bit descriptions. .............................................................................129 65 Control register CR4 bit descriptions. .............................................................................130 65 RFLAGS register bit descriptions. ...................................................................................136

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9 LIST OF FIGURES Figure page 11 Multicore energy efficiency performance benefit achieves 73% performance improvement with negli gible increase in power [93]. .......................................................16 21 Interstitial redundancy (shaded blocks) in a two dimensional mesh network. The (4,4) configuration includes all spares and (1,4) configuration includes the two outermost spares. ................................................................................................................28 22 Classic Paxos with four group members. The view change algorithm selects the primary and broadcasts it to all other members. The primary then chooses a value and attempts to get the other members to choose the same value and accept it. When successful, the final decision is written back to all members and returned. ......................36 23 Byzantine Paxos with four group members. The view change algorithm determines the primary without trusting the primary. The primary then chooses a value and attempts to get the other members to choose the same value and accept it. When successful, the final decision is written back to all members and returned. ......................37 24 Chandra Toueg algorithm with four group members. All members send the primary a value/view pair. The primary makes the choice for the view and broadcasts to al l members. It then awaits a majority of acks and records the decision if they are received. If a single nack is received, a new view is started with a new primary. ............38 25 Architecture of hype rvisor based duplex replication model. .............................................43 26 Stratus architecture with lockstepped processors and independent replicated I/O subsystem bridged with fault detection and isolation chipsets. .........................................49 27 Sample control flow for an EFI BIOS being logically partitioned at boot time. ...............58 28 Partitioned quadcore platform with one partition hosting an OS directly and the other partition hosting a type I hypervisor that has two guest operating systems. ............59 31 Logically partitioned many core platform with each partition hosting a hypervisor. The main partition hosts one or more guest virtual machines while the replica partition hosts a virtually lockstepped replica of a single virtual machine. ......................63 32 Logicall y partitioned quadcore platform with each partition hosting a hypervisor. The main partition hosts a single guest virtual machine while the three replica partitions hosts virtually lockstepped replicas of main guest. ...........................................64 33 Physical many core processor arrangement options include single socket, multisocket, or networked systems. ...........................................................................................65

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10 34 Fault detection inherent in virtual lockstep output value buffer. Divergence is detected when backup generates value that differs from the current head of the buffer. .................................................................................................................................69 35 Fault detection inherent in virtual lockstep input value buffe r. Divergence is detected when backup requests input value for a different operation than is at the current head of the buffer. .......................................................................................................................71 36 VT x transition latencies for five generations of Intel Xeon processors. ......................77 41 High level overview of test platform used for virtual lockstep prototype development and testing. .........................................................................................................................79 42 High level overview of KVM hypervisor architecture. .....................................................82 43 Interface diagram of the KVM hypervisor. ........................................................................84 44 Deterministic VM ex it generation using performance monitor interrupts. ........................87 45 Circular bounded broadcast buffer with primary inserting at in and two backup replicas retrieving from out pointers. .................................................................................93 46 Deterministic execution and interrupt delivery with epochs defined by the deterministic VM exits. ......................................................................................................94 47 Deterministic execution and inte rrupt delivery with epochs defined by performance counter interrupt generation. ..............................................................................................94 48 KVM execution loop diagram [68]. ...................................................................................96 51 V M exits per second for various combinations of operating system and benchmark. ....107 52 Total bytes per second of nondeterministic data for various combinations of operating system and benchmar k. ....................................................................................108 53 Total runtime for various combinations of operating system and benchmark broken down by time spent running in the guest and time spent in the hypervisor. ....................110 54 Break down of the VM exit reasons while executing the test workloads. .......................112 55 Percentage of total runtime spent in the hypervisor broken down by the specific exit reasons while executing the test workloads. ....................................................................113 56 Total runtime of primary and either one replica (dual modular redundant), two replicas, (triple modular redundant), or thre e replicas (quad modular redundant) with a shared buffer size ranging from 5,000 entries to 80,000 entries. ..................................116 61 Robert Sedgewick hash function code. ............................................................................122

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11 62 Fault injection failure distribution for control registers. ..................................................128 63 Fault injection failure distribution for segment registers. ................................................131 64 Fault injection failure distribution for system descriptor tables and the task register. ....132 65 Fault injection failure distribution for general purpo se registers. ....................................133 66 Fault injection failure distribution for various system registers. .....................................134 67 Fault injection failure distrib ution for the RFLAG register. ............................................135 68 Average time to fault detection measured in deterministic VM exits. ............................137 69 Percent of tri als in which fingerprinting based fault detection detected the fault either before (better) or after (worse) than it was detected via I/O comparisons or system crash. The detection was concurrent for the remainder of the trials. ...............................138 610 Fingerprinting optimization showing first fields to indicate failure on average for all registers. ...........................................................................................................................141 611 Fingerprinting optimization showing fi rst fields to indicate failure for CR0 register. ....143 612 Fingerprinting optimization showing first fields to indicate failure for the segment registers. ...........................................................................................................................144 613 Fingerprinting optimization showing first fields to indicate failure for the general purpose registers. .............................................................................................................145 614 Fingerprinting optimization showing first fi elds to indicate failure for the system registers. ...........................................................................................................................146 A 1 Fingerprinting optimization showing first fields to indicate failure for CR3 register. ....152 A 2 Fingerprinting optimization showing first fields to indicate failure for CR4 register. ....153 A 3 Fingerprinting optimization showing first fields to indicate failure fo r descriptor tables and task register. ....................................................................................................154 A 4 Fingerprinting optimization showing first fields to indicate failure for RFLAGS register. .............................................................................................................................155

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12 Abstract of Diss ertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy VIRTUAL LOCKSTEP FOR FAULT TOLERANCE AND ARCHITECTURAL VULNERABILITY ANALYSIS By Casey M. Jeffery August 2009 Chair: Renato J. O. Figueiredo Major: Electrical and Computer Engineering This dissertation presents a flexible technique that can be applied to commodity many core architectures to ex ploit idle resources and ensure reliable system operation. The proposed system interposes a dynamically adaptable fault tolerance layer between the hardware and the operating system throu gh the use of a hypervisor It avoids the introduction of a new single point of failure by incorporating the hypervi sor into the sphere of replication. This approach greatly simplifies implement ation over specialized hardware, operating system, or applicationbased techniques and offers significant flexibility in the type and degree of protection provided. The possible levels of protection considered range from duplex replication to arbitrary nmodular replication limited only by the number of processors in the system. The feasibility of the approach is considered for both near an d longterm computing platforms and a pr ototype is developed as a proof of concept and used to estimate the performance overhead and gather empirical data on fault tolerance capabilities. A fault detection latency reduction technique is also proposed and analyzed using the fault injection facilities provided by the prototype.

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13 CHAPTER 1 INTRODUCTION Motivation The capabilities of the single chip microprocessor have progressed at an astonishing pace since Intel introduced the model 4004 chip more than 35 years ago. Numerous technological hurdles have been overcome to maintain the steady march of Moores Law and advance from a microprocessor with a mere 2,300 transistors to modern designs with more than a million times that amount. One of the greatest challenges on the horizon for continuing such advancements beyond the next decade is that of maintaining acceptable processor reliability. The motivation of this work is to explore techniques of both assessing and improving the reliability of general purpose processors through replicated execution tha t is inexpensive both in terms of implementation costs and performance overhead. The ideas are based on well recognized aspects of future processor designs. The first is that as the size of transistors continues to shrink, the reliability of individual tra nsistors is unlikely to improve and at best will remain constant. This means that a process technology that allows for a ten fold increase in the number of transistors on a device will increase the device level error rate by at least the same factor of ten The second principle is that the paradigm shift from single core processors to dual and quadcore will continue so that even commodity computing platforms will have dozens or possibly hundreds of cores. The key target of the technique is improving proce ssor level reliability of many core platforms by transparently replicating execution across cores in response to signs of pending uncorrectable errors. A small percentage of the cores are used to dynamically replicate execution of cores that require additi onal redundancy, either because a high rate of faults is detected or critical portions of code are being computed. Additionally, the model could be applied to systems

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14 that have very high reliability requirements and/or are subject to much higher rates of f aults due to single event upsets, such as those used in the aerospace industry. Device Reliability The progression to nanoscale device sizes is impinging on fundamental physical limits and bringing about new reliability issues to contend with such as an increase in singleevent upsets induced by radiation events and electromagnetic interference, extreme static and dynamic transistor variability, and transistor performance degradation and wear out [8] [ 13 ] [ 14 ] [ 28 ] [ 51] [ 114]. These effects are expected to present a challenge regardless of the specific process technology used [18]. For example, it is projected that the soft error rates of combinational logic will soon approach the levels at which error protection mechanisms became necessary in memory de vices [20] [ 51 ] [ 106]. It is also forecasted that soft errors will account for a greater portion of total system failures than all other means of failure combined [8]. The problem of soft errors has been present since the dawn of digital electronics, but it has been most prevalent in memory devices that can be protected much more easily than logic circuits [130 ]. The significant increase in transistor variability is the result of the use of sub wavelength lithography to pattern the device structures, as w ell as from the decrease in the number of dopant atoms in the transistor channel. The patterning variation is expected to be dealt with through new techniques such as extreme ultraviolet (EUV), imprint, or maskless lithography, although no solution is yet in place [60]. The dopant variability is the result of an exponential decrease in the number of dopant atoms required for each new generation of process technology. Modern 45 nm CMOS technology has channel dopant levels on the order of 100s of atoms while the 16nm technology, expected within the next decade, will require only 10s atoms and result in a very high level of transistor variability [13] [ 14].

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15 Finally, there is the issue of device wear out due to time dependent dielectric breakdown, electromig ratio n, and thermal cycling [114] [ 126 ]. The resulting failures, termed intrinsic hard failures are permanent and decrease the long term reliability of the devices. The model used in [114] shows an increase in failures in time (FIT) of more than 300% on average when scaling from a 180nm process technology to a 65 nm process. Such an increase in the rate of hard faults results in the wear out phase of the device occurring much earlier and shortening the usable lifetime of the part. Many C ore Architectures The semiconductor industry has recently transitioned to a multi core paradigm to make use of the huge number of transistors that can now be placed on a single chip. The multi core approach allows for improved overall performance while side stepping the power and heat dissipation limitations of continued clock frequency scaling [14] [ 113]. The energy efficiency advantage of multi core architectures in depicted in Figure 1 1 from [93] where the cost of 73% more power is necessary for overclocking to achieve a mere 13% performance improvement while a dual core system is capable of a 73% performance improvement with negligible additional power. The industry roadmaps anticipate this approach continuing on to many core designs that have dozens or even hundreds of possibly heterogeneous cores on a single die [10] [ 14] [ 60 ] [ 119 ]. Of course, the limiting factor in realizing overall performance improvements with many core architectures is the ability of software to extract sufficient parallelism to take advantage of all the cores concurrently. Unfortunately, parallel programming has historically proven very challenging and is expected to remain so. The move from instructionlevel parallelism to thread and applicationlevel parallelism allows for better use of mul tiple cores, but there will inevitably be unused processing cores sitting idle [41].

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16 Dual-core Performance Power 1.73x 1.13x 1.00x 1.73x 1.02x Over-clocked (+20%) Max Frequency Under-clocked (-20%) Figure 1 1. Multi core energy efficiency performance benefit achieves 73% performance improvement with negligible increase in power [93]. As the available transistors an d the corresponding processor core count s grow the idle cycles of these otherwise unused and very powerful resources will allow extra functionality, such as advanced reliability enhancements, to be integrated into the platform. These enhancements are poss ible with negligible impact to the performance of the existing workloads as long as they use otherwise idle resources and do not hamper the available memory or inter processor communication bandwidth or the caching structures. Virtualization Technology A h ypervisor, also commonly referred to as a virtual machine monitor (VMM), is a layer of software that sits logically between the hardware and the operating system. It offers an additional level of abstraction that separates the physical hardware from the op erating system [46]. One of the key benefits the hypervisor provides is a virtual hardware interface that can be made much simpler and more constrained than that of the native hardware. Having a simple, controlled interface greatly simplifies the elimination of nondeterminism in the system, which facilitates the realization of the properties necessary for replicated execution as it will be used in this research.

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17 The use of hypervisors has risen dramatically in the past decade as the capabilities of processo rs and the complexity of software have progressed As one example, over 85% of companies with between 100 and 5,000 employees claim to have deployed some form of virtualization technology [36] Virtualization of the hardware allows for use cases such as se rver consolidation, data isolation, program testing and development, cross platform compatibility, and others [98] [ 127 ]. In the near future, every major operating system will have an integrated hypervisor with Linux incorporating the KVM hypervisor in ve rsion 2.6.20 and Microsoft integrating Virtual PC and Hyper VTM hypervisors into Windows 7 and Windows ServerThere have also been a number of advancements in the area of virtualization that have made i t easier for developers to w rite a hypervisor and significantly decreased the associated performance overhead to the point of approaching native hardware speeds [1 ] [ 120 ]. C urrently there are hardware based virtualization extensions integrated into every major processor architecture, as well as in peripheral devices such as network cards. Soon, at least in the enterprise computing sector, the entire platform will be virtualization aware and practically every server m anufactured will have the necessary support for the virtual lockstep replication model presented in this dissertation. 2008 R2, respectively. Overview and Scope There are numerous levels at which to apply replication in an effort to improve system reliability. The replication model considered in this dissertation is a novel, hybrid approach that is a form of virtual lockstep. It provides operating system replication across an arbitrary number of processor cores under the control of a hypervisor. The hypervisor itself is also replicated so as to avoid the introduction of a new single point of fail ure. The key benefit of the hypervisor based approach is that it can be done purely in software so as to work with commodity processor

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18 architectures, yet it can be enhanced to take advantage of virtualization specific hardware extensions such as IntelThe generalized virtual lockstep replication model proposed provides a means of coping with both transient and intermittent faul ts in the processor cores that are caused by single event upsets and device marginality. It is the first such model to allow for the incorporation of varying degrees of fault tolerance, up to and including arbitrary and possibly malicious Byzantine failure s. It is meant to ensure correct functionality while minimizing redundancy overhead and avoiding the need for complex hardware, operating system, or application changes. The types of systems targeted for this approach are multi and many core PCs and low to mid range servers, as well as specialized systems with additional reliability requirements. Such systems have historically not supported lockstepped execution and are not amenable to replication of the entire physical system, as has historically been do ne in highend mainframes. Vi rtualization Technology (also referred to as VT x or VMX) to improve capabilities and reduce the performance impact [57 ] [ 68]. Additionally, a novel method of enhancing the fault detection capabilities, and correspondingly the availability, of the system is proposed. The virtualizationbased architecture is leveraged as a means of reducing fault detectio n latency through monitoring of virtual processor state hashes. The virtual state is hashed into unique fingerprints that are compared at regular intervals to detect a divergence between replicas before the error propagates to the output of the processor. This is similar to techniques which hash the physical state of the processor, but it does not require complex, costly, and legacy incompatible additions to the processor architecture. The early fault detection mechanism is shown to improve the overall syst em availability by increasing the likelihood that a rollback recovery is initiated before the error is recorded to the saved state in the system checkpoint.

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19 Finally, a mechanism for analyzing the architectural vulnerability factor of a processor is present ed. The fault injection capabilities inherent in a virtualized system are utilized to induce faults into the bits of the processor registers and the propagation of the fault is monitoring by tracking the subsequent state of the processor. This is similar i n application to previous techniques such as RTL fault injection, hardware radiation testing, and analytical fault modeling. The goal of the technique is to assess the sensitivity of various processor structures to single and multibit single event upsets as well as intermittent faults and stuck at faults caused by device marginality and wear out. This technique of monitoring the architectural vulnerability is used to quantitatively analyze the performance of the proposed early fault detection mechanism a nd to further optimize the algorithm by determining the most sensitive subset of the processor state for each register/bit combination. It is shown that only a small subset of the total virtual processor state is necessary in the fingerprint to maintain a high level of fault detection. A second optimization is suggested in which either custom hashing hardware or idle processor resources may be used to improve the hashing performance of the fingerprinting technique by seamlessly integrating into the existing virtualization hardware. Contributions In summary, the specific topics address ed in this dissertation and the corresponding goals are summarized as follows: Define the first generalized virtual lockstep model in which the platform is logically or physically partitioned and the hypervisor is incorporated into the sphere of replication. The model is meant to be agnostic to the specific type of hypervisor, communication protocol, or computing platform used. Demonstrate the ability of the proposed architectur e to extend the degree of replication previously considered by lockstep architectures by allowing for a variable degree of protection ranging from dynamic duplex replication in which a

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20 single backup is tied to one or more primary cores to arbitrary nmodul ar configurations with the possibility of supporting Byzantine protocols. Develop a proof of concept test platform for virtual lockstep using a fullfeatured hypervisor and quantitatively analyze the performance impact of the proposed model over nonrepl icated execution. This is the first virtual lockstep implementation with the features presented in the model. It is a software only approach that relies on hardware extensions for virtualization of Intel processers and extends the open source KVM hypervis or Implement a novel, low overhead fault detection latency reduction technique that takes advantage of the virtual processor state maintained by the hypervisor to generate unique fingerprints that often detect faults much earlier than relying on output c omparisons or the inherent detection capabilities of virtual lockstep. This is a unique form of processor state fingerprinting that i s practical given that it does not require hardware modification but may be easily enhanced by assigning idle, general purp ose compute resources to perform the hashing. Define a fault injection protocol to be used as a test harness for quantitatively analyzing the capabilities of the fault detection and recovery capabilities of the prototype. The fault injection capabilities double as an original means of assessing the architecture vulnerability factor of a processor. This can be used to obtain accurate fault sensitivity data for real hardware and allows for tuning of the protection mechanisms. Dissertation Overview The remai nder of the dissertation is organized as follows: Chapter 2 gives an introduction to the basic concepts in fault tolerance, redundancy, and replica coordination, as well as a literature review encompassing previous work in both hardware and software based approaches to fault tolerance. A brief overview, including the current state of the art, is also provided for relevant work in the areas of many core processor architectures and virtualization technology. Chapter 3 introduces the generalized virtual locks tep model and fault tolerance mechanisms and goes on to show how they can be applied to current and future computing platforms. The details of a prototype test platform that implements the proposed model are given in Chapter 4. Chapter 5 summarizes the ben chmarks used in evaluating the performance of the prototype, as well as the additional modeling and test cases used to evaluate the practicality of the approach. The fault

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21 injection mechanism and fault detection latency reduction technique are covered in C hapter 6. Finally, Chapter 7 summarizes the goals of the research and the steps in achieving them. It also provides more insight into the future applicability of the model and additional research that may be done to further enhance the benefits derived fro m the approach.

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22 CHAPTER 2 BACKGROUND AND RELAT ED WORK Terminology The terminology used in discussing reliability is often overloaded and is not always unambiguous. For clarification, a distinction is made between defects, faults, and errors. The term de fect is used to reference a permanent, physical imperfection in a device that is caused at fabrication by a processing error. The ability of a part to work correctly in the presence of defects is called defect tolerance. If a defect occurs in a device that is being accessed and consistently results in incorrect data being calculated and returned, it is said to result in a permanent or hard fault It is also possible for the defect to result in a weak device that will fail intermittently and/or have very poo r performance; this is called a parametric or intermittent fault. A failure may also occur without being the result of a physical defect. The extraordinarily small size of the circuitry makes it susceptible to soft errors as a result of environmental effec ts such as cosmic rays, alpha particles, and neutrons. This type of fault is not permanent and is referred to as a transient or soft fault. The next time the memory bit or logic gate is used it will function correctly and does not require additional action. If a fault can be corrected either by a mechanism in the hardware or through the use of software, then the system is said to have fault tolerance. If however a fault occurs t hat cannot be corrected, it will fall into one of three categories: it will cau se an error that is seen by the user, it will become benign as a result of being masked or in a bit that is never used, or it will remain undetected as silent data corruption (SDC) waiting to be uncovered at a later time. Fault Tolerance Basics The challen ge of providing fault tolerance in computing systems is as old as the field itself. There has been an enormous amount of research conducted over the years with the goal of

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23 providing dependable system operation. The term dependability is used as it encompas ses not only the reliability of the system, but also the availabilit y, safety, and maintainability. Reliability is defined as the probability that a system functions correctly for time t and is based on the rate of errors seen over T the lifetime of the p art. Formally it is written as follows: R ( t ) = Prob ( T > t ) [22]. The mean time to failure, MTTF, is defined as the expected time the system will last until a failu re occurs and is calculated as MTTF = E[T] = 0dt R(t) (1) The availability i s related to the reliability in that it is the ratio of the MTTF to the MTTF plus the mean time to repair (MTTR). The term safety means that the failures that do occur do not permanently corrupt the data being processed or the underlying system itself. And finally, the maintainability of a system is determined by the ease or speed with which it can be repaired when a failure does occur. MTTR MTTF MTTF ty Availabili (2) An important aspect to consider when designing for fault tolerance is the set of possible fai lure modes that must be considered. The most straightforward is a crash failure in which the system operates correctly up until the time of the failure and then fails in a detectable fashion. Other possibilities include an omission failure where the system does not respond to a request, a timing failure where the response does not occur in a timely manner, or a response failure in which the value returned is incorrect or the result of an invalid state transition. Finally, the most difficult type of failure to contend with is an arbitrary failure that is caused by the system producing arbitrary, possibly malicious responses.

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24 Fault Tolerance through Redundancy There are numerous techniques available for providing fault tolerance by either protecting the system from the occurrence of errors or allowing for quick recovery from them. The focus of this dissertation is on several forms of redundancy that have historically been shown to achieve a high level of fault tolerance with a reasonable amount of overhead in t erms of performance and cost. Although other techniques are not considered explicitly, it is possible in many cases to incorporate them into the proposed model to achieve additional benefits with a corresponding increase to the cost and complexity of the s ystem. Examples include various forms of checkpointing with rollback recovery which allow for fast system recovery to a previously saved state, and software rejuvenation approaches that periodically refresh the state of the guests to flush out any undetec ted faults that may have occurred [17] [ 19 ] [ 69 ] [ 84 ] [ 92] [ 111]. Redundancy M any forms of redundancy are possible, and may include any combination of additional hardware and/or software resources. The general hardware approach consists of replicatin g all or part of the physical system and incorporating fault detection and reconfiguration logic. The extra resources may either be used actively by applying them concurrently with execution on the original base system or passively by having the base syste m periodically update the state of the backups but only enable them w hen the base system has failed. The general software approach is to make use of information coding techniques such as parity bits that are calculated for each piece of data being process ed and then appended to the data so as to be validated by the receiver. It is also possible for redundancy to be implemented in time through repeated execution of the same operation. The software can replicate the execution either temporally by executing it on the same hardware each time or spatially splitting the execution concurrently across different pieces of hardware.

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25 Hardware Redundancy The most basic redundant model is a simple, parallel system with active replication. All redundant units are enabled at all times, which ensures all replicas are always up to date and the system as a whole is operational as long as any single unit is still functional and the error detection logic is capable of reconfiguring the system. The reliability of this simple, pa rallel system is calculated as ] ) ( 1 1 )[ ( ) (1 det N ection parallelt R t R t R (3) where Rdet ectionThere are a number of limitations in a simple active replication scheme, including the inability to ensure a seamless fail over when a unit in the system goes down and the high cost of maintaining a large number of units online at all times. A powerful technique for providing seamless failover is one in which the units are not only replicated but a voter is used to consolidate the outputs into a single value. As long as a majority of the units in the system are functioning correctly, the failure of a unit will not be observable. ( t ) is the reliability of the error detection logic and N is the number of spare units in the system, which leads to a total of N+1 units It is clear from this equation that the performance of the error detection logic should not be overlooked given that it is a gating factor on the overall system reliability In triple modular redundancy (TMR), for example, three units execute in parallel and the resulting output is determined by a majority vote. In general, this type of system is known as N modular redundanc y and the reliability is described by the equation for an M of N configuration as i N i N M i voter Nl of Mt R t R i N t R t R ) ( 1 ) ( ) ( ) ( (4)

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26 It is a wellknown effect of N modular re dundant systems that the overall reliability actually decreases for low levels of individual unit reliability. This means that a single unit is generally a better choice when the unit reliability at or below approximately 50%. For relatively high reliability units, the N modular redundancy approach can achieve significant reliability gains. A technique for reducing the overhead in an actively replicated system is to avoid having all units online concurrently. Instead, the spare units are only powered on whe n necessary, such as to resolve a discrepancy seen in the output of the active systems. For example, the TMR system could be implemented as a duplex or dual modular redundant (DMR) system that activates a spare unit only when the outputs of the active unit s are not in agreement. Not only does this reduce the cost in terms of power consumption, but it increases the lifetime of the units that are powered down. Data Redundancy Another technique for providing redundancy is through embedding extra bits of inform ation into the system. This is achieved through the use of information coding techniques that apply an algorithm to each unit of data to generate a codeword with additional information that can be used to detect, and in some cases correct errors that occur The level of protection is improved by increasing the distance between codewords or number of bits by which valid bit patterns are separated. If valid codewords are separated by a single bit, it is possible to detect an error, whereas if the separation i s increased to two bits, it is possible to correct the error in any single bit position. The most basic forms of data redundancy are parity codes, the simplest of which is a single parity bit. The parity bit is added to ensure either an even or odd number of 1s in the bits of the data. A more powerful class of codes is known as Hamming codes. These codes function by

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27 overlapping the parity bits. In the general algorithm, the parity bits are placed at bit positions corresponding with powers of two (i.e. 1, 2, 4, 8, etc.). The parity bit at position 2nIt is also possible to apply parity at a coarser granularity than at the bit level. The Redundant Array of Independent Disks (RAID) and Redundant Array of Independent Memory (RAIM) techniq ues applied to hard disk and main memory subsystems, respectively are examples of this. There are numerous algorithms defined for various levels of RAID with the simplest being RAID level1 where the data are mirrored across two devices. A more complex con figuration that is often used in practice is level 5. In RAID level 5, blocks of data defined by the stripe size are interleaved among N devices where N is at least three and 1/ N of the total storage area is reserved for parity. All of the parity data are not stored on a single device, however. Instead, the parity blocks are distributed equally among all devices to improve the performance of the system and balance the wear across all devices. will then be calculated based on the bits at all positions for which that bit n is set in the binary representation. The basic Hamming codes are designed to allow for the correction of a single error or the detection of any double bit error within a codeword. There are a number of extensions that can be applied, such as adding an additional parity bit to those applied in the normal Hamming algorithm. Such an algorithm is capable of correcting a single bit error w hile detecting any double bit error or detecting a tripe bit error. Network Redundancy Many of the forms of data redundancy can be us ed to detect and possibly recover from faults introduced in the communication network linking system, but they are ineffective in protecting against complete failure of the link. There are however techniques available for achieving resiliency in the commun ication structures. For the two dimensional mesh, which is the form of communication network considered in this research, interstitial redundancy provides

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28 spare nodes linked into the primary mesh. The degree of redundancy is typically either a single spare for every four nodes, known as (1,4) configuration, or a spare for every node, known as a (4,4) configuration. The spare nodes are placed within the mesh, as shown in Figure 21, and can be switched in when a node or link fails. Figure 2 1. Interstitial redundancy (shaded blocks) in a twodimensional mesh network. The (4,4) configuration includes all spares and (1,4) configuration includes the two outermost spares. Another method of providing fault tolerance in the network is through f ault tolerant routing. It does not require explicitly redundant resources, although it is necessary to have additional logic built into the network stack and may be practical only with redundant virtual channels in the system to reduce contention in the face of faulty links. One of the most common fault tolerant routing protocols for mesh networks is originbased routing which, in its most basic form, can tolerate N 1 failures in an N x N network [76]. The fault tolerant origin based routing algor ithm is rather complex, but the basic steps of the algorithm are as follows. First, it maps out faulty nodes and determines the smallest square region that will encompass those nodes. The entire square region is considered faulty to simplify the routing al gorithm. It then routes towards the destination on the subnetwork directed towards the origin node until it reaches a node in the outbox which is defined as having the coordinates

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29 ( x ,y ) such that 0 x xd and 0 y yd where (0,0) is the origin and ( xd,ydReplica Coordination ) is the destination. Once in the outbox, the routing continues towards the destination until it reaches a safe node which is a node that can be reached from the destination on the subnetwork directed away from the origin node. Finally, once at the s afe node, the routing can proceed without impediment to the destination node. If the form of redundancy used includes multiple replicas, it is important to be able to coordinate them in an appropriate manner. This is a challenging task that has been a focus of research for decades. The key requirements of replication and the basic communication and consistency models for ensuring it have been solved for the most part, but there is a significant amount of work remaining in optimizing the performance and reducing the cost of the systems, as well as in handling more challenging models such as those that allow for multithreaded replicas. This section provides an overview of the basic types of replication and the fundamental properties that must be maintained for coordination. Requirements for Replication The requirements for replication vary depending on the specific model used, but in general linear izability must be maintained. This means that the replicated system must function from the point of view of the programs executing on it as if it were not replicated. Doing so ensures the system functions correctly when running legacy code and eliminates the need for the programmer to be aware of the replication [52]. The linearizability consisten cy model can be maintained under two conditions: order and atomicity. Order is maintained by forcing all dependent operations to be executed sequentially on all replicas through the use of critical sections or mutexes. Atomicity is maintained by implement ing atomic broadcast in the underlying communication primitive and ensuring that

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30 either all functional replicas execute an operation or none of them do [32] The formal definition of atomic broadcast is given by the following four properties [103]: Validit y If a correct replica executes a broadcast, then some correct replica in the group eventually delivers the message or there are no correct replicas in the group. Uniform agreement If a replica in the group delivers a message m then all correct repli cas in the group eventually deliver m Uniform integrity For any message m every replica r delivers m at most once, and only if r is in the group and m was previously broadcast to the group. Uniform total order If replica r in the group deliver mess age m before message m then no replica in the group delivers m before having previously delivered m Replication techniques are often based the concept of a deterministic state machine This means that if the replicas are all started in the same state and given the same set of input, they will progress through equivalent states and give identical output in all cases. The state machine model necessitates the elimination of nondeterminism from the inputs being fed to the replicas, as well as a method of s ynchronizing all replicas to the same state both initially and at any time a system is to be restarted after a failure or a new system is brought into an existing replication group. Forms of Replication The type of replication is typically categorized based on the number of replicas that are externally visible, the type of membership maintained, and the degree of independence of each node. The most general distinction is that of the group being either passive or active, although this is only a rough guideli ne. Passive groups only interact with the external environment through a single, primary node, whereas active groups are all visible externally. These categories can be further divided into semi active, semi passive or coordinator cohort group, which are

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31 briefly summarized below. It is also possible to have hybrid implementations that do not clearly fit into any of these defined categories but combine properties of one or more of them. Passive Replication. In passive replication, also commonly referred to a s primary/backup replication, there is the notion of a primary node that is responsible for maintaining correct operation of the replication group. It is the primary that removes all nondeterminism from the system inputs and is responsible for maintaining state in such a way that a replica can take over if a recovery is necessary. From the point of view of the external environment, the replicated group appears as a single machine. If a request is lost by the primary node due to the failure of the node or th e communications link, it must be reissued once a backup node has recovered from the failure or the link is restored. There are a number of subcategories of passive replication, as well. These are typically referred to as cold or warm. In cold passive repl ication, the primary uses checkpointing to periodically record the total state of the system and then stores all subsequent state updates to a nonvolatile memory. This enables a backup node to effect a rollback and recovery by loading the latest checkpoint ed state and applying the history of state transitions. Conversely, in warm passive replication, the backup nodes execute a short time behind the primary and are active at the time of primarys failure (note that in passive replication it is of little conc ern if a backup node is to fail given that it is opaque to the user of the system). In this way, execution is quantized into epochs and the epoch interval defines how far the backup executes behind the primary. The epoch interval is typically defined in te rms of instructions retired or branches taken. In some cases, it may still be necessary for the backup to conduct a form of rollback and recovery if the primary produces output that is committed and then fails before the state changes are

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32 propagated to the backup nodes. This inconsistency can be avoided, however, through minor changes to the protocol and at the cost of lower performance. For example, the primary could be configured to buffer all state changes and not committing output until it has been veri fied by the backup nodes within the system [49]. Semi Passive Replication. A number of other derivatives of passive replication have been developed to reduce the latency in recovering from failures. Both the semi passive replication and coordinator cohort algorithms work in much the same as the original except that the backup nodes are externally visible and receive request concurrently with the primary node. In these algorithms, the backup nodes do not actually process the incoming requests or send replies to the external environment unless the primary node fails. Because they are actively kept up to date as to the status of the primary, the recovery time is much shorter than that of a typical passive replication system [34]. Various forms of passive and se mipassive replication have proven quite useful for certain use cases [33 ] [ 79 ] [ 102]. These forms of replication are not considered further in this dissertation, however, given that it does not lend itself to the model considered in terms of recovery latency or failure transparency. Active Replication. With active replication all replicas are complete and operate independently. There is no notion of a primary node leading the execution or being solely responsible for eliminating nondeterminism in the in put. Instead, all replicas must be independently capable of implementing a deterministic state machine model and ensuring the ordering and atomicity of the actions taken. The replicas must also work together to make decisions about the values chosen for nondeterministic events.

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33 This form of replication has the highest performance in terms of failure recovery time, but it comes at the cost of a significant resource overhead since all replicas must be fully active at all times. It also requires that all nodes are capable of operating fully deterministically. This form of replication is applicable to physically lockstepped, fully deterministic processing cores, which are complex to design and expensive to deploy [ 6] [ 53] [ 82]. Semi Active Replication. The fin al form of replication considered is semi active replication which is the form of replication that will be explicitly considered for the model presented in this dissertation. As a derivative of active replication, it shares many of the same traits with th e key difference being the additional definition of leaders and followers within the replica nodes. All inputs are still delivered to all replica nodes and all actively process the requests, but the followers lag behind the leader by an epoch similar to the warm passive replication scheme described above. The leader of the group has the additional responsibility of resolving all nondeterminism from the inputs and supplying the decided values to the followers This requires additional functionality to be inc orporated into the nodes so that they can elect a leader and distinguish when a nondeterministic event occurs. The leader must also be equipped to decide on a value for the event and distribute it to the followers, which must know to wait for the value from the leader. There are numerous ways to configure a replicated system, but the protocols that are most applicable in this research are the duplex or triplex configurations that make use of semi active replication techniques. The benefit to these configura tions are that they improve the fault tolerance of the system by allowing for the comparison of outputs generated and do not require a large amount of stable storage that would be necessary for a standby backup configuration. They

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34 also simplify the goals o f providing high performance and fault recovery that is transparent to the user of the system. Group Communication and Membership The most complex aspect of the passive and semi active replication configurations is the group membership protocol and the underlying communication protocol necessary to support it. The basic roles of the membership protocol are that of determining the membership of group and designating the primary or leader node. Members of the group can join and leave as a result of node failure and subsequent recovery. In some algorithms, nodes may also be evicted from the group when other members suspect they have failed. Each change of membership resulting from the addition or removal of a member or the change of the primary node is defined as a new group view [ 67] The problem of determining group membership is not in itself difficult and choosing a primary or leader node can be as simple as selecting the node with the smallest/largest identifier. One difficulty arises from the fact that dif ferent replicas can come to different conclusions about the state of the group. This is the result of asynchrony in the system and inconsistencies that may be present in the fault detection mechanisms used by each node. For example, if the primary node of a triplex system fails after sending out an update that only reaches one of the two backup nodes, the backup nodes will be in an inconsistent state even if a new primary node is correctly selected. The way to avoid many of these problems is to ensure virt ual synchrony of the system, which is a property that requires all replicas with consecutive views to deliver the identical set of messages [11] There are a number of basic safety properties that must be provided to ensure correct operation, and they can be summarized as follows [26]:

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35 Delivery Integrity every message receive must be proceeded by a send of the same message. No Duplication Two messages received at th e same node cannot be identical. Sending View Delivery If a message is received in vi ew V it must be sent in V Same View Delivery If two nodes receive the same message, it must be in the same view. A consensus protocol is used to decide on one value from a set of proposed input values from the members of the group. There are numerous distributed consensus protocols that have been developed, each with slight variations in the conditions assumed and the properties provided. Some of the most common in literature are the Classic Paxos, Byzantine Paxos, and Chandra To ueg consensus algorithms [21] [ 30 ] [ 50] [ 71 ] [ 81] [ 103]. These are introduced in this section. The Classic Paxo s consensus protocol decides on a value based on a successful majority vote within a given view where a view is defined in much the same way as above. In this ca se, a series of views is used to give the group multiple opportunities to decide on a value. The value to be considered is proposed by a primary node where the primary is designed by some arbitrary function applied to the view number. New views can be star ted by any member of the group that believes the decision process to be stalled due to stopped or failed group members. Local timeout values are typically used for detecting a stalled decision process and may result in multiple concurrent views being initiated, each with different primary nodes, if some members are just slow and not truly failed. This is not a problem; however, as safety is preserved by ensuring that if a decision is ever made, it is unique and all later views will return the same value. U nfortunately, liveness cannot be ensured by this or any consensus algorithm if the system

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36 is asynchronous [40], but in practice it is sufficient to use local timeout values to treat very slow systems as failed. View Change p p S S Normal Operation p p p p p Figure 2 2. Cla ssic Paxos with four group members. The view change algorithm selects the primary and broadcasts it to all other members. The primary then chooses a value and attempts to get the other members to choose the same value and accept it. When successful, the fi nal decision is written back to all members and returned. The key feature of Classic Paxos is a distinction made between the value chosen in a view and the value recorded as the final decision in the group. A view will first chose a value from a set of pro posed inputs and then will attempt to get a majority of nodes to accept the value. When this occurs successfully, the decision is recorded at all nodes. If a given view fails to complete the decision process, a later view just needs to know whether a valid previous choice exists. If the previous view made a choice, it must be visible and the later view must choose the same value. If the previous view failed, however, the later view can choose any value. As shown in Figure 2 2, this process will continue unt il a chosen value is decided upon and recorded at all members of the group. The Byzantine Paxos protocol is an extension to the Classic Paxos algorithm to allow for arbitrary faults to occur in the replicas. The key addition is the absence of trust of the primary member since it may be malicious. All decisions are made only with the majority of members

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37 being in agreement, so both the steps to choose a value and to accept it are completed at all nodes rather than at only the primary, as in Classic Paxos. The result of this is that all nodes will record the final decision and any of them could return the value to the external environment. An example of Byzantine Paxos is shown in Figure 23 [71]. View Change p p S S Normal Operation p p p p p Figure 2 3. Byzantine Paxos with f our group members. The view change algorithm determines the primary without trusting the primary. The primary then chooses a value and attempts to get the other members to choose the same value and accept it. When successful, the final decision is written back to all members and returned. The Chandra Toueg algorithm is similar to the Classic Paxos algorithm in that it consists of a series of asynchronous rounds in which a primary node attempts to direct a majority of other members to decide on a value. It does not tolerate Byzantine failures. As before, if a round appears to have failed, a new round is started with a new primary. One of the key differences in this model is that the other members of the group initial provide the primary with their estimates on what the decision should be, as well as the view number in which they last updated the value. The primary awaits a majority of a given value and broadcasts it to all other members. It then waits for the other members to ack or nack the value. If it recei ves a majority of acks, it will record the final decision and broadcast it to all members. If it receives a single nack, however, it

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38 initiates a new view and the selection of a new primary [50]. The diagram in Figure 24 depicts the four basic steps of the Chandra Toueg algorithm. p S Normal Operation p p p p Round 1 Figure 2 4. Chandra Toueg algorithm with four group members. All members send the primary a value/view pair. The primary makes the choice for the view and broadcasts to all members. It then awaits a m ajority of acks and records the decision if they are received. If a single nack is received, a new view is started with a new primary. Related Work in Fault Tolerance A wide variety of redundancy techniques have been proposed for providing fault tolerance in the processor logic. As indicated previously, t hey can be generally categorized as being either hardware based or softwarebased although as in the model considered in this dissertation, there are inevitably some configurations that are a hybrid of the two They may also be subcategorized by the level at which they provide the fault tolerance. For exampl e, hardware based techniques have been proposed which replicate the entire processor core [ 2] [ 39] [ 47 ] [ 83 ] [ 109] a simplified version of the pr ocessor core [5 ] [ 124 ] or only functional blocks within the processor core [85 ], [ 89] In software based techniques, replication may be implemented at the instruction set architecture (ISA) interface [ 16] [ 94] the operating system level [ 53] [ 116] [ 121] the system call inte rface [15 ] [ 107 ] [ 115 ], or the application or compiler level [95]. These

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39 options lead to trade offs being made in terms of performance overhead, design complexity, implementation cost, and fault tolerance transparency. Hardware F ault Tolerance There are many topics to consider within the realm of hardware based fault tolerance techniques. The focus of this dissertation in on improving the reliability of the processor logic, and as such, the literature review is of previous work in that area. Of course, this form of fault tolerance should not be applied in isolation. It is necessary to ensure the reliable operation of the other components that comprise the computing platform, so a brief overview of previously proposed techniques is also provided. Processor Logic One of the original hardware based approaches for fault tolerance in processor logic is the use of a small, simple watchdog processor to monitor the control flow and memory accesses of the main processor and validate it in o rder to detect errors [ 80]. The greatest drawback to the approach is that the watchdog processor must be provided with a Structural Reference Program, which is output produced by the compiler that indicates the program structure while removing the computat ional portions of the code. More recent variations of this idea have been proposed to relax this requirement and to permit the secondary processor to also assist in recover ing from the errors. In [5 ] dynamic verification is achieved by integrating a funct ional checker processor into the commit state of the pipeline. All instructions completed in the main core are sent, along with the corresponding operands and result, to the checker core to be verified before being committed. The checker core can be simpler since it does not have to predict branch outcomes, decode instructions or resolve operands.

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40 Yet another approach that utilizes redundant hardware is the use of simultaneous multithreaded (SMT) capabilities in processors such as the IntelMore recently, chip multiprocessors (CMP) have allowed for similar multithreading across processor cores with the added benefit that a hardware fault will not cause the same error to occur in both copies of the thread [ 47]. The trade off made is that the replication must be coordinated across different cores, which results in greater latency and may stress the inter processor communications bandwidth. This is dealt with by allowing for a longer slack between the main thread and its trailing replica, as well as pipelining the inter processor communication. Pentium 4 [99]. T he duplication of hardware blocks allows multiple, identical copies of a thread to be executed with temporal redundancy and then checked against one another with a reasonable performance overhead The basic operation of the system is based on a duplicate thread that is created by the hardware without the knowledge of the operating system. The second thread lags behind the main thread while executing the same execution stream. It has a small impact on the processor bandwidth since it has the benefit of all branch outcomes and data values being determined by the main thread. There are also designs in which the processor is explicitly replicated for the purpose of improving reliability [55] T he outputs are monitored for differences and either forward error recovery is achieved by ensuring fail stop behavior at the detection of an error or backward error recovery is provided by storing known good states and rolling back to them when an error occurs This form o f processor replication has been implemented in the IBM G4 and G5 series processors with support for backward error recovery [ 112]. The IBM processors are have duplicate instruction fetch (I) and execution (E) units and a recovery (R) unit that is responsi ble

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41 for validating the output of the E unit, as well as maintaining checkpoints of the processor state in case a rollback and recovery is necessary. The approach taken by HP in its NonStop systems is a forward error scheme in which all processors act inde pendently and without shared memory. They exchange messages over a redundant bus interface and operate at a cycle level lockstep while comparison circuitry validates all outputs for consistency and special, self checking logic is used to monitor for failur es within the cores. At the occurrence of a failure, the processor is designed to fail fast and remove itself from the system until it can be replaced. These specialized systems are some of the most advanced, and correspondingly, most expensive fault tol erant computing systems to be designed [ 6] [ 9 ] [ 53]. Memory and I/O Devices In designing a highly reliable computing platform, it is insufficient to focus all the effort on improving the fault tolerance of the processing cores. It is also necessary to ensure the correct functionality of the other hardware components in the system. Fortunately, this has proven easier to accomplish and there are many proven and commonly applied techniques capable of providing very high reliability at a reasonable cost. One powerful technique that can be applied to main memory and storage devices is the RAID parity described in above. In addition to this highlevel, inter device parity generation, both main memory and storage devices also typically have lower level, intra dev ice parity generation ranging from single bit parity to powerful Hamming ECC coding [23] The hierarchical application of parity has proven quite powerful and will likely continue to deve lop into additional layers [61 ]. Another common type of protection of ten applied to computer peripherals are the various forms of linear block codes. These include the simple parity and Hamming codes introduced

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42 earlier, as well as cyclic redundancy codes (CRC) used in wired Ethernet, USB, Bluetooth, and modems, as well as R eed Solomon codes used in optical media such as CDs and DVDs. This class of algorithms produces a checksum that is appended to the data on the media and provides error detection and possibly correction capabilities. The process of encoding using cyclic c odes is done by multiplying (modulo2) the data to be protected by a generator polynomial. An nbit CRC makes use of an n+1bit generator polynomial and is capable of detecting a single error burst of size n or less where a burst is defined as the length o f consecutive bits encompassing the error. It is also capable of detecting some longer error bursts. To later decode and check for errors, the data are divided by the same polynomial constant. If the result is a nonzero value, an error is known to have oc curred. There are numerous predefined generator polynomials for various applications with the most common ranging in size from 9 bits (CRC8) to 65bits (CRC 64). There are also no limitations on the size of the data on which the algorithm is applied as it is always possible to sign extend the data to the minimum length. Reed Solomon codes are similar but function on blocks of data rather than single bits and are able to correct bursts of errors. The basic encoding process consists of representing blocks of data by a polynomial and then sampling it at a greater number of points than the degree of the polynomial used. For data represented by k symbols, each of which is m bits in size, a total of n symbols are stored where n = 2mThere are also techniques for protecting the network interfaces of the system. One such example is network adapter teaming, which involves teaming two or more physical network 1 and k < n. A maximum of ( nk )/2 faulty symbols can be corrected.

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43 adapters to function as a single adapter with a single IP address. This allows for load balancing and transparent fail over in case of a network card failure. Software Fault Tolerance T here are a number of different layers at which software based fault tolerance may be implemented. The focus of t his research is on t he ISA interface, which is the lowest level of the software stack. Previous research at this and other levels is briefly considered in this section. Instruction Set Architecture An example of fault tolerance implemented at the ISA level is the hypervisor based replication presented in [ 16]. As depicted in Figure 25, this work makes use of a hypervisor to coordinate replicated execution across multiple physical systems that share a common hard disk. The form of replication implemented is a hybrid of the passive and semi active schemes. The replicas all receive inputs from the external environment and actively execute the same sequence of events. There is also the notion of a primary node that is designated a priori and is responsible for removing nondeterminism from the system inputs. Only the primary node records the output computed to the external environment. Backup SCSI Disk Controller Primary Ethernet SCSI bus Figure 2 5. Architecture of hypervisor based duplex replication model. The execution stream is partitioned into epochs defined by the instructions retired counter by initiating an interrupt whenever the counter expires. The values for all nondeterministic events that occur in the execution are decided on by the primary which executes one epoch

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44 ahead of the backup, and then distri buted to the backup for injection at the same location in the execution stream. This includes values read from the timestamp counter, DMA data, etc. External interrupts are handled by buffering the vector and delaying their injection into all nodes until the end of the epochs. The failure of the primary node is detected by a timeout in a backup node, at which point the backup node is promoted to being the primary and repeats any outstanding I/O requests that cannot be verified to have been completed by the previous leader. The main differences of this model to that considered in this dissertation are that a fail stop fault model is assumed and only simple failover to a single backup is supported. There is also the requirement in the prototype developed for the work of an external coordinator since the hypervisor i s not augmented with the capabilities necessary to function independently. The fail stop fault model limits the effectiveness of the replication and is especially limiting if the goal is to provide replication across multiple cores within a package or motherboard to protect the system from single event upsets. A number of other hypervisor based replication architectures have been proposed. These fall into two general categories either semi active v irtual lockstep designs similar to the example just given or fast checkpointing configurations in which the hypervisor sends snapshots of the state of the guest system to one or more backups in a semi passive fashion. The virtual lockstepbased work is gen erally limited to a high level design overview without specific details related to implementation [ 25], [ 31 ] [ 78 ] [ 96] [ 97]. The fast checkpointing design is based on an extension to the Xen hypervisor and addresses many of the hurdles of implementation [33]. Yet another vector for research has been in recording the deterministic execution of a guest operating system with the application of the same techniques used in virtual lockstep, but not

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45 replaying it in realtime. Instead, the recording is used to debug software, detect malware, or to simply replay precise ex ecution at a later time [37 ] [ 128] [ 129 ]. Any virtual lockstep implementation should be portable to this use case, although it may be necessary to more finely tune and possibly compress the log file associated with the recording. In virtual lockstep the log only needs to cover the span between the primary and the slowest backup replica, whereas deterministic log recording may require many minutes or even hours of logging time and result in huge storage requirements. Operating System Although there have been successful implementations of fault tolerant operating systems such as the Stratus Virtual Operating System (VOS) and the HP NonStop Kernel operating system the size and complexity of moder n operating systems limits the widespread adoption of such functionality in more common versions such as WindowsThere are challenges in maintaining application support when porting to a new operating system, as well. Even though fault tolerant operating systems attempt to maintain POSIX compliance and support ANSI compliant versions of major programming languages, the applications that can be ported are limited to those with source code available. The problem is compounded by sparse device driver support and the le arning curve associated with deploying and learning a new operating system. These limitations constrain the use of specialized fault tolerant operating systems to their current role in enterprise mainframes and make it unlikely that commodity hardware will be supported. or Linux Both the Stratus and HP implementations are tightly coupled to specialized, faulttolerant hardware, which together form a verticall y integrated platform targeted at mainframe level enterprise applications [ 6] [ 9 ] [ 53] [ 116 ] [ 125 ]

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46 Middleware Yet another option is to build a middleware layer that sits at the system call interface in the operating system and provides replica coordination to the applications above it An example of this is presented in [ 15] where a Trans parent Fault Tolerance (TFT) middleware is used to coordinate application replication above the operating system level in much the same was as [16] functioned at the ISA level. Execution is again partitioned into epochs and a deterministic state machine mo del is maintained by ensuring that all replicas begin the in the same state and receive the same sequence of deterministic inputs. All systems calls made into the operating system, as well as all exceptions and interrupts delivered to the applications, are intercepted by a designated leader node in the middleware. The leader node again executes ahead of the followers and has the responsibility of removing all nondeterminism from the system. In the case of nondeterministic systems calls, such as gettimeofday (), the leader records the transformation of state resulting from the call and forwards it to the other nodes in the replica group for injection at the same point in the execution. Exceptions are buffered and are delivered to all nodes only at the end of t he epochs when it is known to be at a deterministic point in the execution. This approach has many of the same drawbacks of the ISA model described above in that a fail stop fault model is assumed and only simple failover can be performed. One additional difficulty is a lack of predictable epoch boundaries since there is no guarantee that a system call or exception will ever occur for certain workloads. To avoid this, the authors propose the use of specialized binary object code editing to instrument the ex ecution with guaranteed epoch boundaries by decrementing a counter on each back branching instruction. Additional problems arise when considering multithreaded processes and the use of shared memory for process communication. Given the additional challenge s and the limitation of implementations being

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47 inherently OS dependent, there is little perceived benefit of a system call approach over on at the ISA level. Application/Compiler The final approach considered for software based integration of fault toleranc e is that of directly coding it into the applications There are a numerous techniques for achieving this, but most are based on modification to the compiler in an effort to relieve the programmer from having to possess the specialized skills necessary to implement fault tolerance explicitly [88 ] [ 95] [ 101 ]. In these compiler based approaches, the instructions in the program are duplicated and configured to use a different set of registers and physical memory than the original copy of the program. The out puts from both copies of the program are compared at each store instruction to ensure consistency. Additional capabilities and optimizations are possible, including varying degrees of control flow validation. For example, if the memory is protected by anot her mechanism, it is possible to share the memory among the copies of the program. It is also possible in many cases to have the compiler schedule the redundant execution during times at which the main program is stalled so as to reduce the performance pen alty. Control flow checking can be achieved by statically computing a signature for each basic block of code and then verifying it at runtime. Most approaches require some form of hardware support for the signature calculation, but there has been work on supporting it completely in software, as well [87 ] [ 88]. Unfortunately, there are a number of drawbacks to this approach. The obvious limitations are that it is limited to fault detection and is not applicable to any clo sed source applications. There are also challenges in dealing with shared memory, exception handlers, and asynchronous events such as interrupts, which require additional compiler capabilities and hardware level support to avoid loading different values in to each copy of the program.

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48 Case Study: Stratus ftServer architecture The StratusThey approach the problem by defining three fundamental components: lockstep technology, failsafe software, and ActiveService mid range server systems are illustrative of many of the most advanced hardware fault tolerance capabilities integrated into pro duction computing platforms [116] [ 117]. Unlike the topof the line Continuum series and HP NonStop servers, the ftServer line supports running commodity Windows and Linux operating systems and avoids the limitations and cost of the completely vertical options. This is the use case that is the basis for the model proposed in this dissertation. TMAll other components are replicated as well, including the motherboards, memory, I/O busses, and all peripherals such as network cards, storage devices, and remote management infra structure. The I/O subsystem is independent from the CPU and memory subsystem and the interface is bridged using a custom chipset capable of detecting and isolating faults. One of the goals of the design is to allow for the use of as many industry standard components as possible and only relying on a small amount of custom logic in each of the subsystems. The basic architecture is depicted in Figure 2 6. architecture. The lockstep technology is implemented much like that of the HP NonStop system described above and consists of fully replicated processors in either a TMR or a pair and spare configuration. In TMR, if one processor fails, it can be taken offline and the system will run as a DMR until it is repaired. If one processor fails in the pair and spare system, the pair will be brought offline and the backup pair will be put into service. The Stratus approach to failsafe software is to attempt to make the replication and all fault tolerance functionality transparent to the operating system and user software. This permits the use of a number of standard operating systems without modification. An effort was also made to

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49 allow the operating systems to make use standard, software supported fault tolerance mechanisms such as the hard disk and memory RAID and network adapter teaming. Embedded I/O PCI Disks Fault Detection and Isolation Fault Detection and Isolation Processor Chipset Memory Embedded I/O PCI Disks Fault Detection and Isolation Fault Detection and Isolation Processor Chipset Memory Multi-path I/O Lockstep Figure 2 6. Stratus architecture with lockstepped processors and independent replicated I/O subsystem bridged with fault detection and isolation chipsets. Finally, the ActiveServiceTMOverall, the Stratus system encompasses a complete set of fault tolerance and automation mechanisms and claim to support 99.999% uptime in production systems. The greatest drawbacks to their systems are the relatively high cost resulting from the use of customized chipset hardware and the limited range of applicability. It is not possible to integrate the fault tolerance mechanisms into existing hardware, and the pl atforms that are supported are limited. The goal of the model presented in this research is to achieve many of the same goals of the Stratus system while avoiding expensive and limiting hardware support. architecture consists of platform monitoring and remote support capabilities integrated throughout the platform. The goal is to automate the monitoring and repair of the system to the greatest degree possible, as well as to allow for remote troubleshooting and resolution if intervention is necessary. Fault Injection In most cases, the best method of as sessing the benefits of a fault tolerant solution is to test it since even moderately complex designs are extremely difficult to model analytically Fault

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50 injection provides a means of gathering empirical data related to the behavior of the system after th e introduction of a fault. By introducing the faults in a controlled manner, it is possible to ascertain how they propagate through the system and to determine when and how they emerge as a system failure. There are multiple levels at which to model the fa ults. They can be modeled at the transistor or wire level through RTL injection, but this is an expensive and slow process that requires having the full specification of the chip available [3] The benefit to the approach is that it is possible to directly associate an event such as a particle strike to the corresponding behavior in the device. Of course, it is not possible to do until the design is finalized and detailed analysis is done regarding the properties of the process technology used to fabricate the device Alternatively, it is possible to model the faults at the register level, which requires only the microarchitecture specification, either in the form of a software emulation model or a real physical device [48] [ 65 ] [ 73 ] [ 91] This method is less accurate in modeling the underlying effects actually introducing the faults, but it provides much of the s a me information and can be done much faster and easier. This is done by introducing a bit flip or a stuck bit into the actual register and letting it continue execution. In both approaches, it is necessary to conduct a number of trials to determine the behavior under different circumstances. With enough data, it is possible to determine the probability of a fault affecting the correct outcome of the software. One mechanism of stating this probability of incorrect behavior is the architecturally correct execution (ACE ) analysis, as described in [123]. The approach taken in this research is the latter and is most similar to [ 73 ] as it makes use of a hy pervisor to model faults at the register level by injecting them into the physical processor Previous work in the area of fault injection often focuses on a subset of the processor registers

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51 and usually limits experimentation to a few of the most critical ones in the architecture [3 ] [ 48 ] [ 73] [ 122 ] [ 123 ]. As will be shown in Chapter 6, one of the main goal s of this research is to look at all meaningful registers in the processor. Many C ore Architectures Many core is the progression of the chiplevel m ultiprocessing architecture to the point of having dozens or even hundreds of cores on a single silicon die. It is a significant change in the design of processors, which have historically scaled almost solely based on increases in the clock frequency. As modern d esigns approach fundamental barriers to frequency scaling, combined with an increasing disparity in the speed of the processor and the latency of main memory, computer architectures are increasingly rely ing on threadand appliciationlevel parall elism to offer improve ments in performance. Network on Chip Architectures One of the key architectural changes needed to support a large number of cores on a single silicon substrate is the transition to a form of distributed system. It is not practical to have a fully synchronous system as clock skew cannot be kept within an acceptable range. Instead, an array of locally synchronous devices is necessary which can be treated globally as an asynchronous system. Such a configuration necessitates a point to point communication protocol. Shared communication mediums, such as arbitrated busses or ring buffers, do not scale to deliver the necessary performance levels, so packet switched micro networks have been developed [10] [ 12] These networks onchip (NoC) a re logically similar to networks used at the macro level with a router integrated into each core and data routed over multiple hops from each source to destinat ion.

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52 The type of routing used varies based on trade offs such as predictability vs. average per formance, router complexity, and general network robustness. In order to achieve fault tolerance, a form of adaptive routing is desirable over static paths and wormhole routing (a form of cut through switching) is typically used to achieve higher bandwidth and lower latency than circuit or packet switching techniques at the cost of slightly higher energy usage when the network traffic is high [10] [ 29 ]. It works by breaking the packet into smaller units called flits with the necessary routing information provided in a short header portion of the initial flit. This allows the router to determine the next hop very quickly and begin forwarding parts of the packet before the entire packet even arrives at the node. Another challenge in supporting a large core c ount on a single chip is supplying all of the processor cores with adequate bandwidth to main memory. One likely solution is the use of a threedimensional stacked design in which the main memory is attached directly to the processor die and pac kaged in the same substrate [118 ] There are a number of processes for stacking, which can be roughly categorized as faceto face or faceto back processes. In faceto face, the tops of both chips are fused together and deep vias are used to connect the chip to the package. In face to back, the top of the first chip is fused to the back of the second chip and vias are formed to connect them. The wafers must go through a series of extra processing steps including thinning of the wafer to remove extra silicon from the back, alignment to line up the chips with the necessary submicron tolerances, planarization and polishing to atomically smooth dimensions, bonding to fuse together the copper connections, and finally any additional steps required for via formation and packa ging. The final result is an array of processor cores with very short, highbandwidth access to main memory.

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53 There are a number of methods for achieving fault tolerance within a NoC system. Both the origin based routing algorithm and the interstitial redun dancy mechanisms described earlier can be used to compensate for physical node or link failures within the network. Soft errors resulting from single event upsets and crosstalk pose an issue, as well [43]. They can be handled through the use of error corre ction coding to provide forward error correction capabilities and retransmission when the error is not correctable. The most important piece of data to protect is the header flit with the routing information because corruption in those bits can result in delivery of the data to the incorrect node, at which point the entire packet must be retransmitted even if it is otherwise correct. One common retransmission technique is to supply a three flit retransmission buffer for each node. This allows for the three cycles necessary for the transmission to the next node, the error checking, and the return of the negative acknowledgement [90]. The Polaris processor is a prototype NoC based architecture developed as a proof of concept by Intel Corporation [ 119]. It consists of 80 4GHz processing cores in a 10x8 twodimensional mesh grid. Each processor has a routing interface block (RIB) to encapsulate the data being transferred and is connected to a 5 port wormhole switched router that forwards the packets to the four neighboring cores and to the stacked main memory The design allows any core to communicate directly with any other core in the chip over a virtual channel with a bandwidth of 80GB/s. Each of the cores in the Polaris system is relatively simple and designe d specifically to achieve the goal of a teraflop level of performance in a single chip with less than 100W of power dissipation. The cores will be expanded in the future to provide a mixture of general purpose, as well as specialized computing capabilities including graphics processing, floating point, and encryption.

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54 Parallel Programming The greatest challenge in the continued advancement of overall performance in many core architectures is finding ways to take advantage of all the computing resources ava ilable. It has been shown that obtaining a noticeable benefit from more than even two cores in typical, interactive desktop applications is difficult given the limited amount of parallelism available [ 41]. Amdahls Law states that the speedup achievable wh en running on N processors is limited by the ratio of parallel tasks, P versus those that must be done serially, S. N P S P S N Speedup ) ( (5) Some proposed methods of increasing the amount of thread level parallelism are speculative prefetching and pr ocedure execution, data dependence speculation, data value prediction, and runahead execution using helper cores T hese techniques are limited in the speed up achieved and offer less than a 40% improvement on average for the SPEC CPU2000 benchmarks [66] [ 77]. Without a significant breakthrough in coding and compiler technology, programmers will be unlikely to make full use of the large number of cores available in most common, interactive applications [41] Virtualization and Logical Partitioning This s ection introduces system virtualization and logical partitioning, which are two of the technologies considered in the fault tolerant architecture to be presented in Chapter 3. The specific types of virtualization considered are based on hardware virtual machines while the form of logical partitioning considered is based on static, BIOS enabled partitioning. A brief description of each is provided with the focus being on the aspects most relevant to the replication model to be introduced in the next chapter

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55 Hardware Virtual Machines Hardware virtualization refers to the decoupling of the operating system from the physical hardware of the computer system, which is different than that of software or application virtual machines (e.g., Java) that are used to m ake an application portable across instruction set architectures In hardware virtualization, the operating system is presented with a virtual representation of the hardware that does not necessarily have to have a one to one mapping to the physical resour ces backing it. Such an abstraction provides a number of benefits including resource sharing, device and feature emulation, inter platform software portability, and others. One feature that is very beneficial to replication is the simplification of the int erface between hardware and software. The implementations of hardware virtual machines are often subcategorized as being type I or type II. Type I virtual machines are also known as bare metal hypervisors because they are installed directly on top of the hardware and must have full support for drivers, scheduling, resource sharing, etc. Examples of a type I monitors include IBM z/VM, Xen, VMware ESX Server, and Microsoft Hyper V. Type II virtual machines, on the other hand, are known as hosted hypervisor s because they are installed within a host operating system and make use of the hosts system calls to interact with the hardware. They also have the benefit of being able t o use the hosts driver base, as well as its existing scheduling and resource shari ng capabilities. Examples of typeII implementations include KVM, VMware Workstation, and SWsoft Although virtualization technologies have been in use in much the same form for over four decades, there has been a significant amount of work recently in improving the functionality, performance, and ease of hypervisor design, as well as expanding the usage models supported. The development of hardware and microcode extensions in processors and chi psets has Parallels Desktop.

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56 eliminated many of the complications prevalent in virtualizing the IntelOne of the key features provided by the Intel virtualization hard ware extensions is a new mode of operation, which is referred to as VM root mode. This mode is enabled before a guest operating system is booted. The new guest is then resumed in VM nonroot mode where it has access to all four ring levels. It is also guar anteed to exit to the hypervisor on all privileged instructions, and the processor will change the linear address space on each control transfer. When the hypervisor needs to gain control, it does a VM exit back to VM root mode. This new mode allows the hy pervisor to cleanly and efficiently host legacy operating systems x86 architecture. This included such things as ring aliasing, address space compression, and non faulting access to privileged processor state [57] A portion of the host and guest state is maintained in a reserved page of memory called the Virtual Machine Control Structure (VMCS), which is set up with a physical address mapping known t o the hypervisor and passed to the processor using a VMPTRLD instruction whenever a guest is launched for the first time on the processor. This structure stores the control, segment, instruction pointer, stack, and flag registers, as well as a number of control fields to define the types of operations that cause VM exits. Some of the fields in the VMCS are set by the hardware, such as the one indicating the version of VMCS format. Most of the values are set by the hypervisor with the VMWRITE instruction. Once all fields have been appropriately programmed by the hypervisor, the guest is set to be executed on the processor with either a VMLAUNCH instruction if it is the first time being executed on that core or a VMRESUME instruction if it has already been exe cuting there. When a guest VM exits back to the hypervisor, the fields in the VMCS have been appropriately updated by the hardware and are read by the hypervisor with a VMREAD instruction. There is some necessary guest state that is not present

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57 in the VMCS that the hypervisor must save and restore manually on each guest transition. The fact that this structure stores key state of the guests virtual processor makes it useful for detecting divergences in virtually lockstepped systems, and will be discussed i n Chapter 6. Practically all modern computing platforms provide a similar form of hardwa re based virtualization support and future systems will have support integrated throughout the entire platform including virtualization aware peripherals Those that do not can still take advantage of paravirtualization approaches in which the guest operating system is made aware it is being virtualized or the finely tuned dynamic binary translations developed to avert the portions of code that are troublesome to virtua lize [1 ] [ 74 ]. As indicated in the introduction, these advancements have significantly decreased the performance overhead of virtualization, which now approaches that of native hardware. Benchmarks run on VMwareLogi cal Partitioning ESX Server, for example, show a virtualized guest running at an average of 97% of native for the SPEC CPU2000 Integer suite, 94% to 97% of native for Netperf, and 91% of native for SPECjbb2005 [120]. Additionally, research has been done on techniques for applying virtualization to systems dynamica lly. This self virtualization transitions the operating system from running on bare hardware to running under the control of a hypervisor without disturbing the applications running in it and allows for truly native performance when the guest is not being virtualized [25]. In order to replicate the execution of a guest operating system within a single physical platform, it i s beneficial to be able to partition the system in such a way that multiple hypervisors can be executed concurrent ly. This avoids the introduction of a new single point of failure by allowing for the hypervisor itself to be replicated, in addition to the guest operating system. The partitioning and can be done through logical partitioning.

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58 Logical partitioning of a sy stem involves restricting the physical resources seen by an operating system or hypervisor. The goal of the logical partitioning of the system is much more basic than that of a typical hypervisor. It is used to carve up system resources at boot time such t hat multiple guests can be restricted to independent portions of the underlying hardware. Once this task is completed, it attempts to get out of the way and allow the operating system or hypervisor in the partition to run unobstructed. It requires little or no interaction with the guests after initialization and is typically done through the platform firmware with a minimal amount of logic. Power On EFI Shell Copy EFI Shell Boot Partition 0 Disable Config Writes Boot Partition 1 Figure 2 7. Sample control flow for an EFI BIOS being logically partitioned at boot time. An example of logical part itioning is given in Figure 2 7, where an EFI compliant BIOS alter s the ACPI and ICH data reported to mask some of the available processors, memory regions, timers, and I/O devices, which can be allocated to other guests. The EFI shell spawns a copy of its elf to manage booting the second partition after the first has indicated a successful boot sequence. The challenges in logical partitioning include loading a guest OS at an alternate base address, allowing cooperative scanning of shared busses such as PCI, and allowing independent guest reboot. Similar, but more advanced partitioning support is provided in highend IBM severs and mainframes where the allocations can be made at a fine granularity and adj usted dynamically at run time [4 ] [ 56]. The use of log ical partitioning has historically been limited to mainframe

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59 systems, but as with many other such technologies, it will move into personal computers as it becomes more practical and useful That is when the personal computers have a large number of cores w ithin a single socket or motherboard. Physical Hardware Hypervisor OS 1 on Physical Hardware OS 3 on Virtual Hardware OS 2 on Virtual Hardware CPU 1 MEM 1 MEM 2 CPU 4 CPU 2 CPU 3 MEM 3 MEM 4 I/O 1 I/O 2 VCPU 1 VMEM 1 VCPU 2 VMEM 2 I/O I/O Partition 1 Partition 2 Figure 2 8. Partitioned quadcore platform with one partition hosting an OS directly and the other partition hosting a type I hypervisor that has two guest operating systems Figure 2 8 re presents how a quadcore platform might be simultaneously partitioned and virtualized. The first partition in the diagram is hosting a standard operating system directly, whereas the second partition is executing a typeI hypervisor that is running two gue sts. The partitions are not required to be symmetric but must be onto mapped to physical resources. The virtual machines, however, can virtualize hardware that does not map directly to that physically provided by the machine. The objectives of this c hapter are to provide a brief background on the key technologies discussed in the subsequent chapters, as well as to give a broad view of the general direction the computing industry is going in terms of platform architecture and reliability while calling out th e

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60 trends that support the model to be developed and analyzed in this dissertation. Relevant prior research is also summarized to provide a basis for existing mechanism and to allow comparisons to be made to the proposed methodologies.

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61 CHAPTER 3 PROPOSED F AULT TOLERANT ARCHIT ECTURE Architecture Overview The goal of the generalized system model presented in this chapter is to provide dynamic fault tolerance capabilities to the processing nodes of a many core platform without expensive changes to the underlyi ng hardware or operating system. This is achieved through replicated execution across virtually lockstepped processor cores where the coordination and fault detection logic are incorporated into the sof tware based hypervisor layer [62] [ 63 ]. This section describes the key aspects of the platform partitioning and virtualization, replica communication and coordination, and platform monitoring as they apply to fault tolerant virtual lockstep model. An effort is made to allow for flexibility in the degree of f ault tolerance provided and in the type of hypervisor required by considering the replication and communication protocols in a generic fashion. The hypervisor is also brought into the sphere of replication to avoid the introduction of a new single point of failure. Replication Model Scope As mentioned in Chapter 1, the target platforms for the proposed model are low and midrange servers that may have multiple processor sockets and a large number of total processor cores. These classes of servers are not w ell suited to being fully replicated for reasons of cost and complexity. Instead, they are better served by allocating a small percentage of the total number of cores for replicated execution. This adds little additional overhead and allows for replicated execution only when the reliability of a core is questionable or when reliable operation is most critical. Such a model also allows for an adaptable trade off to be made between performance and fault tolerance since the cores can still be used for normal execution when replicated execution is not necessary.

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62 In the semi active replication model presented, the focus is on protecting the processor cores themselves, which typically have no protection beyond parity bits on key registers. The goal of the replicat ion is to detect faulty operations and recover from them before erroneous data leave the processor. The hard disk, network interface devices, and similar peripheral I/O devices are not included in the sphere of replication. There are numerous techniques al ready commonly available for providing fault protection for these devices, several of which were mentioned briefly in Chapter 2 [59]. The main memory is also not explicitly protected, as it too can be easily protected with existing means. Unlike the other components of the platform, however, there is a degree of inherent protection provided by the replication since each replica maintains a complete memory image of the guest. A simplification in the model is made by considering only uniprocessor virtual mach ine guests. This is done because it is significantly more complex to maintain the deterministic state machine model when considering multiprocessor guests, as it is necessary for all replicas to agree on the ordering of the mutex acquisitions. Many of the t echniques necessary for achieving such coordination have been developed in other work, but the resultant impact to performance is still too high [7 ] [ 38 ] [ 54 ] [ 64 ] [ 115]. Once refined, these techniques could be applied as a direct extensi on to the model presented in this dissertation. Platform Partitioning and Virtualization The system configuration consists of a hypervisor layer on top of a partitioned, many core platform. The exact number of cores is not critical, but it is assumed that systems will generally have dozens or even hundreds of cores so that the overhead of using a small number of entire cores for replication is reasonable. There may also be multiple sockets either distributed on the same motherboard or across separate physical systems connected by a highspeed, low latency interconnect.

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63 At least one processor core and a portion of main memory must be available in a separate partition for use in hosting a replica. Depending on the degree of replication implemented, multiple replica partitions may be necessary. The p latform partitioning is done either logically or physically, although logical partitioning is preferred since it allows for replication within a single physical system. The hypervisor code is modified to provide the capabilitie s necessary for replicating executio n, and the guest virtual machine replication is initiated either statically when the guest is launched or dynamically based on input from platform level monitors that indicate the possibility of an imminent uncorrectable error. A single instance of the hypervisor is executed in the main partition, as well as one in each of the replica partitions Of course, these copies of the hypervisor are aware of one another and know how to communicate and coordinate the execution of the guests CPU 1 MEM 1 CPU 2 MEM 2 CPU 3 MEM 3 CPU 4 MEM 4 CPU M MEM M Main VMM Replica VMM OS 1 OS 2 OS 3 OS 4 OS Main Partition CPU N MEM NReplica Partition Figure 3 1. Logically partitioned many core platform with each partition hosting a hypervisor. The main partition hosts one or more guest virtual machines while the replica partition hosts a virtually lockstepped r eplica of a single virtual machine. An example of the general design is shown if Figure 31, which depicts a many core platform that is logically partitioned into two heterogeneous containers. The hypervisor in the

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64 main partition is allocated the bulk of the system resources and executes a number of different guest virtual machines in a scenario typical of a server consolidation. Additionally, the hypervisor in the replica partition executes a single, virtually lockstepped copy of one of the guest instances in the main partition. The guest or guests to be is replicated are based on the resources available, as well as platform monitoring sensors or the quality of service required for the guest. Alternatively, Figure 3 2 shows a configuration in which there is a single guest that is replicated in a quad modular redundant fashion. That is there are four processors, each in separate partitions, executing the same deterministic instruction stream. This level of replication is sufficient to achieve Byzantine levels of fault tolerance if the appropriate membership and value selection protocols are implemented in the hypervisor. Replica VMM OS 1c CPU 4 MEM 4Replica 3 Partition Replica VMM OS 1b CPU 3 MEM 3Replica 2 Partition Replica VMM OS 1a CPU 2 MEM 2Replica 1 Partition Main VMM OS 1 CPU 1 MEM 1Main Partition Figure 3 2. Logically partitioned quadcore platform with each partition hosting a hypervisor. The main partition hosts a single guest virtual machine while the three replica partitions hosts virtually lockstepped replicas of main guest. The processor cores in the physical system do not necessarily have to reside in the same sock et and may instead be distributed across sockets on the mother board A multisocket design

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65 offers an additional level of protection in case a faul t causes the failure of the entire chip. It comes at the cost of additional communication latency, reduced inter processor bandwidth, and a lower degree of node connectivity [44] [ 45]. Socket 2 Socket 1 CPU 1 MEM 1 CPU 2 MEM 2 Main VMM Replica VMM OS 1 OS 2 OS Main Partition CPU 4 MEM 4 Replica Partition CPU 3 MEM 3 Socket 1 CPU 1 MEM 1 CPU 2 MEM 2 Main VMM Replica VMM OS 1 OS 2 OS Main Partition CPU 2 MEM 2 Replica Partition CPU 1 MEM 1 System 2 System 1 CPU 1 MEM 1 CPU 2 MEM 2 Main VMM Replica VMM OS 1 OS 2 OS Main Partition CPU 2 MEM 2 Replica Partition CPU 1 MEM 1 Figure 3 3. Physical many core processor arrangement options include single socket, multisocket, or networked systems. This design could also be trivially extended even further to support virtual lockstep execution across separate physical s ystems if a very high speed, low latency communications channel such as Infiniband is available. The diagrams in Figure 33 summarize these three options. It should be noted that the networked configuration is not the focus of this research and

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66 all optimiz ations are meant to improve the performance of single socket many core, and possibly multisocket platforms, but the communication protocols considered do not fundamentally inhibit the networked machine configuration. Platform Monitoring Platform level mon itoring consists of fault detection and other sensor circuitry embedded throughout the platform, which varies by system. Examples of this include parity bits in the cache and memory regions, as well as within some processor logic structures. It also includ es temperature monitors in the processor, motherboard, memory devices, and chassis. More advanced approaches are also possible, such as the use of processor built in self testing (BIST) logic to check for failures and wear out throughout the processor [108]. Most server platforms consolidate the monitoring facilities using a baseboard management controller (BMC) microcontroller and expose them through the Intelligent Platform Monitoring Interface (IPMI). The specific forms of platform monitoring supported a nd the triggers used to determine when to initiate replicated execution must be considered on an individual basis and integrated appropriately. Fault Model and Fault Tolerance Overview This section describes the fault model considered, as well as the fault tolerance capabilities provided by the replicated virtual lockstep execution. The limitations of the fault detection mechanisms are also discussed. Fault Models The fault models typically considered in computing platforms can be roughly categorized into t wo general types. The first is the fail stop fault model, in which an operating system is expected to execute correctly until an uncorrectable error leads to a failure. At that point, the system will stop functioning and the failure will be immediately app arent. The second case is the

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67 Byzantine fault model, where the operating system may fail in an arbitrary fashion that is not necessarily detectable. Not only that, but it may also be malicious and purposely attempt to deliver incorrect results. Neither of the fault models is completely accurate in describing the behavior of most realworld systems. Because of this, an intermediate model is considered in this dissertation. A fault is assumed to not immediately cause a system failure or to even be detectable. It is also presumed that there is not a blatant malicious attack being conducted at the hardware level in order to circumvent the fault detection logic. In fact, in real systems, this is almost always the case. For example, a single faulty bit in a random register of an IntelEven behavior officially designated to be undefined by Intel will almost always follow a valid sequence of events and fail with an undefined opcode (UD#) exception, a general protection (GP#) exception, or possibly cause a machine check exception (MCE). In fact, the system may never crash, as the fau lt may be masked in such a way that it becomes benign, or it may corrupt the processor state in such a way that the error goes undetected and lies dormant until a later time. The second case is silent data corruption and is the most concerning since it res ults in incorrect results being produced without any indication they are erroneous. processor is unlikely to cause an immediate system crash on the subsequent instruction, but it is also unlikely that the processor will behave in a completely random or malicious fashion. Faults are considered at the granularity of bits in registers of the processor. This is in contrast to gate level faults, such as those modeled using register transfer lang uage (RTL) specifications for processors. For the purposes of this dissertation, the main source of the faults is considered to be transient bit flips resulting from single event upset events in the logic. However, the model does also protect against multibit events, as well as intermittent and wear out faults

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68 that cause incorrect values to be recorded in the registers. Some indirect protection is provided against faulty bits in memory or cache structures for values that are eventually propagated to the pr ocessor registers and result in the generation of faulty output. Fault Tolerance Capabilities The fault tolerance capabilities considered in this model are all based on the replication of system execution across disparate processor cores and vary from simp le error detection via duplex configurations to arbitrary error detection and correction with Byzantine capable configurations. Again, the sphere of replication extends fully only to the processor cores themselves, as well as any uncore features (i.e., not computing engines) that may be present within the processor die. In general, the detection of errors in replicated systems is achieved by comparing the pin level outputs generated by the processor cores and monitoring for inconsistencies. This method of fault detection is supported in the proposed virtual lockstep model. An example is given in Figure 3 4 where the accesses to the output value buffer are depicted for a duplex system consisting of a primary and a single backup. The primary inserts values wri tten to I/O ports and through memory mapped I/O into the buffer. Then, then the backup reaches the same point in the execution, it retrieves the values and compares them to those that it has generated. If true determinism is maintained, the values should be the same. If they are not, a divergence is detected. Unfortunately, it i s not possible to know exactly when the fault occurred. For example, if a particle strike causes a bit to flip in a processor register, a number of instructions are likely to be executed before the value in the register is read. Alternatively, the faulty value may not be immediately read at all and instead be written back to memory and not accessed until much later and via a different register. It is only when the value from the regis ter is used, and the result is

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69 seen as output from the processor, that the error will be manifested in a detectable form. That is, as depicted in the figure, the fault may be injected some time before the first output divergence. In the example given, ther e are two OUT instructions which still match, as well as an MMIO operation. It is not until the third OUT instruction that the fault has propagated to the value being written, at which point it becomes detectable. ... I/O Value Fault Injected Primary Backup Output Buffer Slot 1 Output Buffer Slot n Output Buffer Slot 1 Delay I/O Value I/O Value I/O Value I/O Value MMIO ValueValue Mismatch I/O Value I/O Value I/O Value I/O Value I/O Value MMIO Value MMIO Value MMIO Value MMIO Value I/O Value Figure 3 4. Fault detection inherent in virtual lockstep output value buffer. Divergence is detected when backup generates value that differs from the current head of the buffer. An obvious limitation of the basic duplex output value comparisons are that even when an error is detected, it i s not possible to know which replica is correct and what the true value should be. In order to support fault correction, the next level of fault tolerance complexity is necessary. It involves triplex configurations and the trivial combinations, such as the pair and spare scheme introduced in Chapter 2. This is supported by simply having more backup replicas and designating a node or a piece of logic as a voter. The voter is responsible for determining the value based on the majority of the replicas and appropria tely directing the hypervisors to shut down faulty guest and reintegrate fresh replicas.

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70 Even more advanced configurations are those that are capable of coping with the Byzantine fault model in which the mechanism used to determine the outcome of a vote ar e not trustworthy, and of course involve more replicas. The Byzantine capable models function in much the same way as the duplex and triplex models by comparing the outputs of all the replicas and choosing the value that achieves the majority of votes. The main difference is that multiple rounds of voting may be necessary in order to come to a consensus. A summary of the overhead and capabilities of these configurations is given in Table 3 1. Table 3 1. Replication configuration and capability summary Redu ndancy Total Nodes Quorum Fault Tolerance Duplex 2 2 1 detected Triplex 3 2 1 corrected Pair and spare 4 2 1 corrected Byzantine Paxos 3 f +1 2 f +1 f corrected (Byzantine) The main limitations determining the maximum degree of fault tolerance are the le vels of system resources available, i.e., processing cores and memory, and the amount of bandwidth available between the cores. Byzantine capable fault tolerance requires not only a very high level of system resources, but the number of messages passed bet ween systems is extremely high. It is anticipated that triple modular or other lower order forms of n modular redundancy will define the limits of practicality for most scenarios and are the focus of the configurations considered later in the prototype imp lementation. There is an additional method of fault detection inherent in the virtual lockstep model. The values stored by the primary in the input buffers can actually be used to detect divergences, as well. This works because the primary replica places t he values it has chosen for nondeterministic events such as I/O inputs, MMIO reads, and values returned by reading the timestamp counter

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71 with RDTSC. The backup replicas do not have a way of verifying these values, and in fact, it is expected that the value s differ from those that the backup generates since that i s the point of using the buffer. I/O ... I/O I/O I/O I/O MMIO MMIO MMIO I/O RDTSC RDTSC I/O I/O I/O I/O MMIO MMIO RDTSC I/O Fault Injected Primary Backup Input Buffer Slot 1 Input Buffer Slot n Input Buffer Slot 1 Delay Input Type Mismatch Figure 3 5. Fault detection inherent in virtual lockstep input value buffer. Divergence is detected when backup requests input value for a different operation than is at the current head of the buffer. What the backup can verify is the ordering of the types of operations. An example is given in Figure 3 5 where the injection of a fault eventually propagates through the system and causes the backup replica to reach a n I/O based IN instruction that the primary did not have. Instead, the primary reached a memory mapped I/O read and stored those results in the buffer. At this point, it is known that the backup execution has diverged. It should be noted that the fault may have caused the backup to receive different values than it otherwise would for the operations prior to this detection point, but these go undetected as long as the type of operation matches since these input values are always overwritten. There is a minor optimization possible in some cases, for which scrutinizing the value is beneficial even if the types match. For example, if the access types are both I/O IN operations, but the ports being read from do not match, that is also enough information to indica te a divergence.

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72 The detection of errors at the processor I/O inputs and outputs is not ideal; however, especially if the goal is to determine the source of the error or to avoid checkpointing system states that include the fault. One method of catching the problem earlier is to compare the internal state of the processors at regular intervals [110]. This technique is covered in more detail in Chapter 6. Virtual Lockstep Overview Virtual lockstep involves replicating the execution of complete guest operatin g systems under the control of a hypervisor. This section describes the basic requirements necessary to achieve such replication. These general principles form the basis for the prototype developed in Chapter 4. Deterministic Execution In order to run repl icas in virtual lockstep, it is necessary to implement a form of deterministic state machine by removing all nondeterminism from the execution of the guest virtual machine [104]. This includes synchronous sources such as instructions that access the timestamp counter or read in data from an I/O port, as well as asynchronous sources, such as external interrupts. Direct memory access (DMA) replication must be dealt with as a combination of both cases (i.e., a nondeterministic I/O operation that occurs asynchr onously). The replicas must be synchronized by the hypervisor based on deterministic points in the execution. There are natural points in most execution that can be used. For example, an access to a control register or a write to an I/O port will occur at the same point in the execution if everything up to that point is also deterministic. The problem is that some guests may not have any such synchronization points, or may not have a high enough frequency. A common mechanism for achieving an acceptably high rate of such deterministic points is to program

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73 counters in the processor to expire at regular intervals based on the retirement of certain types of instructions. The novel mechanism used in the virtual lockstep prototype developed is to use VM exits from VM nonroot mode to VM root mode as the synchronization points. That is, each time a VM exit occurs that transfers control back to the hypervisor at a point in the execution that is guaranteed to be deterministic, a counter is incremented and the hypervis or is given the opportunity to inject asynchronous events, such as virtual interrupts into the guest. This ensures that the asynchronous events occur deterministically in all replicas. This mechanism does imply that a steady stream of deterministic VM exits must be ensured. The details on how this is dealt with are deferred to the design specifications in the next chapter. Data from the synchronous, nondeterministic instructions, which include those that do string or value I/O operations, memory mapped I/O or read the hardware timestamp counter, must be copied from the primary replica to the one or more backup replicas. This is achieved with a buffer that is shared among all hypervisors in a typical producer/consumer fashion. The primary signals the backup (s) when an item is available, and when a backup gets to the same synchronous instruction, it retrieves the data stored in the buffer and verifies it matches the type of operation it expects. It then either uses the input it received or verifies the output it produced, depending on the direction of the event. For basic n modular redundancy, the buffer is placed in a central location that is accessible by all replicas and may be accessed over a network connection. In Byzantine capable redundancy configurations, each replica maintains a local buffer that is kept up to date using a distributed consensus protocol.

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74 The asynchronous, nondeterministic events (i.e., external interrupts) are captured by the primary and placed into a second shared buffer. Their delive ry into the primary is delayed until the first instruction following a deterministic point in the execution for which the guest is ready to accept the interrupt. If both of the requirements are met, the event is injected and its details are recorded in the shared buffer. The backup replicas peek at this buffer to determine the point at which they must inject the next event, which is defined by the deterministic event count. When a replica arrives at the target position, the interrupt event is removed from t he shared buffer and injected. It is assured that the event will be deliverable, unless a fault has occurred, since the state of the system is, by definition, identical to the primary. Platform Partitioning Requirements If the system is to be physically pa rtitioned across two or more complete systems, it is necessary to have a high speed, low latency communication protocol for transferring data between the replicas. This can be a high speed network, Infiniband, fibre channel, or similar technology. If the i nterface is too slow or has a high latency, it can have a severe negative impact on the performance of the guest. Alternatively, a logically partitioned platform is well suited with a shared memory form of inter process communication. These differences can be reconciled such that a single implementation can be either physically or logically partitioned by implementing the communication protocol used by the hypervisors with a socket interface. The socket addressing scheme can be easily change from local path names (AF_UNIX) to Internet addresses (AF_INET). One form of logical partitioning is based on using firmware to partition the system resources at boot time. Specifically, a modified Extensible Firmware Interface (EFI) capable BIOS is used to boot two or more operating systems, or in this case, hypervisors on the same

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75 physical system. Each of the hypervisors is booted with its own view of the system, which consists of an exclusive portion of the total processor, memory, and I/O resources, as well as support logic to deal with the sharing of certain features that must be common across partitions, such as timers and the PCI bus. The boot flow of a modified EFI BIOS was given previously in Figure 2 7. There are certain requirements that must be met by the guests of the logical partitions to function correctly while sharing the physical resources. The memory resources can be split up through the descriptor tables and the hard disks by the controllers. The guests must then be capable of being loaded at nonstandard address locations, as well. This requires the hypervisor, or the host operating system in the case of a type II configuration, to be modified with the necessary bootstrap support. It is also necessary for all partitioned guests to be capable of sharing th e system timers and probing the PCI bus in a safe manner. These difficulties may be simplified by making the hypervisor logical partition aware. The hypervisor or the host operating system of the hypervisor can be modified to be loadable at alternate base addresses and to probe the PCI bus in a safe manner. Hypervisor Requirements There are numerous subtle variations in the goals of virtualization software in modern platforms, which has led to dozens of variations in hypervisor design. They all function in much the same way, however. This section details the specific hypervisor features that are considered and how they relate to the model presented. The general virtual lockstepbased replication model presented is quite flexible in the type of virtual machin e monitors supported. As long as a hypervisor supports true system virtualization it should be portable to a virtual lockstep implementation. It makes little difference whether the hypervisor used is a typeI or type II implementation, or if it is paravirtualized or

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76 supports hardware virtualization extensions. The hypervisor must maintain control over all nondeterministic state presented to the guest it is hosting, however. This includes features such as direct memory access (DMA) done by I/O devices. If th e hypervisor does gain control for all such events, it is possible to make that state deterministic and support virtual lockstep. In addition to DMA, an example of a feature that is not supported is the case where the physical hardware interrupts are sent directly through the guests interrupt descriptor table. Doing so allows for interrupts to be seen at nondeterministic points in the guest execution, which is not permissible. In terms of practicality, there are a number of considerations to be made in hypervisor selection, however. The low performance overhead of system virtualization plays a key role in determining the usefulness of the system. As mentioned previously, however, the performance of many modern hypervisors approaches that of bare hardware. A nother consideration is the complexity of the virtual hardware interface. The more complex this interface is, the more difficult it is to obtain fully deterministic operation. A final consideration is the portability and general availability of the impleme ntation. It is often desirable to use a hypervisor that has been ported to a wide range of architectures and is widely available for use. As was mentioned in the review of virtualization technology, practically all modern processors have a high degree of h ardware support. The benefits of a hardware based virtualization approach tend to outweigh the other virtualization options. Such systems are typically much simpler than those that rely on paravirtualization or advanced dynamic binary translation technique s. In general, they can also be made to perform quite well with much less programming effort than those that do not use the hardware extensions. Also, the performance of the hypervisors on those platforms continue to improve with each new generation of pr ocessor

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77 technology, regardless of any additional effort in tuning the software, as the hardware capabilities are improved. An example of this trend of hardware enhancement is shown in Figure 36 which shows nearly a 6x reduction in VT x transition times in terms of processor cycles from the first generation of processors to support the virtualization extensions [35]. These transition time reductions directly improve virtualization performance clockfor clock without any changes to the hypervisor code. Clear ly, the latest designs have much less total room for improvement available, but a reasonable reduction is still possible. Figure 3 6. VT x transition latencies for five generations of Intel XeonThis chapter defined the specific goals of th e virtual lockstep based replicated execution, which are to allow for a flexible mechanism for trading off performance for fault tolerance within the processor cores without the need for new hardware or operating system capabilities. The key aspects of the virtual lockstep operation, including the general requirements for achieving deterministic operation, partitioning the platform, and incorporating virtualization were also introduced. These principles are put into practice in the next chapter in which a prototype is developed. processors.

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78 CHAPTER 4 TEST PLATFORM OVERVI EW The focus of this chapter is on the design and implementation of a proof of concept virtual machine monitor design that incorporates the ideas presented in the previous chapter. Based on the considerations detailed there, KVM, an open source type II (hosted) hypervisor that supports hardware virtualization extensions has been chosen for implementation of the prototype [68]. An overview of the test platform hardware is provided, which is followed by an introduction to the KVM hypervisor, including a discussion of many of the key challenges of enabling virtual lockstep execution. Details regarding the specific guest operating systems considered as replication targets and the corresponding detailed perf ormance benchmarks are deferred to Chapter 5. System Overview The basic components of the main test platform used for the virtual lockstep prototype development and testing are depicted in Figure 41, below. The underlying hardware is based on quadcore In tel Xeon processors with support for IntelThese platforms were used both because they are representative of the class of machines targeted for the virtual lockstep, albeit with fewer cores than future designs, and for their support for VT x extensions. The single socket part is from a newer generation of process technology which has reduced overhead for the virtualization features, namely the time to transition between Virtualization Technology extensions. The detailed specifications for the two specific systems used for development and data collection are given in Table 4 1. There is a singlesocket, quad core platform that is representative of an entry level server and a dual socket, quad core platform that is representative of a mid range server.

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79 VM ro ot mode and VM nonroot mode and the speed of accesses to the VMCS structure. These transition times and VMCS access times were detailed in Chapter 3. CPU 1 MEM 1 CPU 2 MEM 2 KVMMAIN KVMREP OS 1 OS 2 OS 1R Main Partition CPU 4 MEM 4Replica Partition COMM CPU 3 MEM 3 Figure 4 1. High level overview of test platform used for virtual lockstep prototype development and te sting. For a given system, one or more processors, as well as portion of the system memory, are reserved for use as replica partitions. A Linux based operating system is installed, which hosts a version of the KVM hypervisor that is modified to support vir tual lockstep functionality. There is a single primary instance of the hypervisor and one or more backup replicas that repeat the execution of the primary and check the processor state and output for errors. The replicas are configured to communicate using bounded broadcast buffers that are placed in a shared memory region. This allows for very fast access times to the buffer, which represent the speeds at which communication occurs in a logically partitioned platformpossibly a networkonchip design. Of c ourse systems that instead communicate over a standard network connection are expected to have a significantly higher latency and lower bandwidth but may still exhibit acceptable performance overhead [102].

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80 Table 4 1. Prototype platform hardware and softwa re specifications Platform A Platform B Processors Xeon X3360 2.83GHz (4 cores) Dual Xeon E5345 2.33GHz (8 cores) Process Technology 45nm 65nm Chipset Intel X38 Intel 5000X Memory 8GB DDR 3 1333MHz 6GB FB DIMM 667MHz Hard Drives 640GB SATA 4x 250GB SATA in RAID 10 Host Operating System Ubuntu 7.04 x86_64 Ubuntu 7.04 x86_64 Host Kernel Custom Linux 2.6.25 Custom Linux 2.6.24 The prototype is not meant to represent an ideal implementation of the virtual lockstep model proposed in the previous chapt er. It is, however, designed to be sufficient in supporting the validation of the goals outlined for the dissertation, which are to demonstrate a generalized hypervisor based replication model where the hypervisor is protected, support multiple degrees of replication up to arbitrary nmodular redundancy with the possibility of extending to Byzantine levels, and to demonstrate the viability and performance on real hardware. This analysis is done in the next chapter. The prototype also supports fault injection and the proposed fault detection latency reduction fingerprinting mechanisms, which are covered in detail in Chapter 6. KVM Hypervisor Overview The KVM hypervisor is a hosted implementation with support for hardware virtualization extensions and broad availability through the inclusion in the mainline Linux kernel since version 2.6.20. It was chosen for the prototype because it is open source, supports hardware virtualization acceleration, and runs on most modern platforms including Intel and AMD x86,

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81 Int el IA64, PowerPC, Sparc, and IBM s390. This means that the functionality proven in this dissertation using the prototype on the Intel x86 architecture can be extended directly to a number of additional architectures. This section gives a brief overview of the architecture of KVM and the key aspects requiring modification to support virtual lockstepped replication. The release of KVM initially used for the prototype was version 7. This was an early release of the hypervisor and had only very basic hardware s upport and moderate performance overhead. The latest release the prototype has been ported to is version 33, which is a fairly mature release of the core code base. Later versions of the hypervisor add some additional performance improvements, but are more focused on adding support for more advanced virtualization features that are more difficult to support with virtual lockstep, and a number of additional hardware architectures such as IA64 and PowerPC. For these reasons, KVM 33 is used for the remainder of the document as the stable version for which the detailed description, as well as all performance and capability testing are based on. KVM Components KVM is composed of a small kernel driver component and a Qemubased user space component. The kernel com ponent is split into two subcomponents: one that is a generic kernel module and another that is specific to the type of hardware virtualization extensions supported. Since the test platform is based on an Intelbased processor, the kernel component speci fic to the IntelOne of the major benefits of KVM over other open source hypervisors is its relatively small code base. The version used for the prototype has fewer than 20k lines of code in the kernel dri ver components. The code that is of concern for the prototype implementation is an even smaller number given that much of it is for supporting the AMD V Virtualization Technology extensions is required. TM virtualization

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82 extensions, which are not considered. The size of the Qemubased user space component is much larger at approximately 300k lines of code, but only a small portion of that is even used when KVM is enabled and a smaller subset still is applicable to the prototype. Much of the code in Qemu is for delivering fully emulated execution. By making use of VMX capabilities, KVM supports a new mode of execution in addition to kernel and user mode, which is called guest mode. This is another term for VM nonroot mode and is enabled by the hypervisor executing a VMLAUNCH or VMRESUME instruction and is us ed to execute non I/O code directly on the processor. Kernel mode, which refers to VM root mode, handles VM entries and exits to and from guest mode and user mode is used to perform the I/O operations on behalf of the guest with the help of the Qemu compon ent. The guest virtual machine executes in the context of a normal Linux process that can be controlled by all the normal process related utilities (e.g., kill,top, taskset, etc.), so pinning a guest to a specific processor core is trivial. The basic archi tecture of KVM is depicted in Figure 42 where two normal Linux processes are executing concurrently with two KVM virtual machine guest processes. Each guest process has a Qemu based user space component and the Linux kernel has the two kernel drivers, one for generic functionality and the other for Intel VMXspecific functionality. Figure 4 2. High level overview of KVM hypervisor architecture.

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83 KVM Implementation Details The basis for the KVM hypervisor is Qemu, which was originally designed as a process or virtualizer and emulator with the goal of supporting cross platform execution. It consists of a CPU emulator, emulated device models, a debugger, and a user interface. It makes use of powerful optimizations in the CPU emulator to support relatively fast emulated execution, but this functionality is not used with KVM. The remaining subsystems are used, however. The devices models provide virtual VGA, serial, parallel, PS/2, IDE, SCSI, NIC, and other devices which are connected to the host platform by way of generic block, character, and network devices. The BIOS model is also carried over from the Qemu project, although it originated in the Bochs emulator. The majority of the control of the hypervisor occurs in user space (ring 3), through an application programming interface (API) specific to KVM. The API is defined by a system call (IOCTL) interface is exposed through the /dev filesystem in the host operating system. The IOCTL interface is a standard mechanism for communicating with a kernel driver runnin g in ring 0. It allows for calls to be made into the generic kernel module, which uses the architecture specific module to service the request. The controls are divided into three categories: system level, virtual machine level, and vcpulevel. The system level controls are for functions such as determining the API version or creating a new virtual machine. The virtual machine level controls offer functionality such as creating a new virtual CPU (VCPU) and configuring the guest memory regions. Finally, the vcpulevel interface is used for the main execution of the guest including the main Run and Interrupt commands, as well as commands to get/set registers and model specific registers (MSRs) and translate memory addresses. The architecturespecific module is responsible for resuming the guest into guest mode using virtualization instructions defined by that architecture.

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84 It is also responsible for handling VM exits back to VM root mode. A diagram of the KVM hypervisor interfaces just described is given in Figure 4 3. Figure 4 3. Interface diagram of the KVM hypervisor. Hardware Features and Limitations The implementation of the virtual lockstep prototype depends on specific hardware functionality being available. The key components considered are the perform ance counters, virtualization extensions, interrupt handling and delivery mechanisms, and an inter process communication infrastructure. It is wellknown that the performance counter and interrupt delivery components are not 100% accurate at the instruction level and special care must be taken to ensure correct functionality when being used in the context of deterministic execution [37].

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85 Performance Counters The performance counter infrastructure has been present in some form or another in the Intel process ors since the introduction of the Pentium Pro (P6 family) chip. It consists of a set of model specific registers (MSRs) that are used to select the events to be monitored and maintain a count of the events. The first implementation supported the monitoring of two types of events using 40bit counters. They could be programmed to count either the events themselves by incrementing each time an event occurs or the length of the events by counting the number of processor cycles that occur while an event is tru e. The capabilities were greatly enhanced for the Pentium 4 (NetburstTM family) chips with a total of 18 counters supported, but were then simplified again when transitioning to the simpler and faster CoreTMFor the purposes of the prototype, only the Core based family of chips. TMbased functionality is considered. One of the benefits of these versions is that the counters required for enabling deterministic execution have been specified as architectural which means that their behavior is guaranteed to be consistent across processor implementations. Prior to this, all performance monitoring capabilities were nonarchitectural and could vary by processor model. Additionally, the later generations of CoreTMThe key challenge in using the performance counters for stopping at deterministic positions in guest operating systems is that they are not designed for such purposes. Rather t hey are meant for performance profiling, which does not require perfect accuracy. The events are processors have further extended the performance m onitoring capabilities. All Xeon processors produced using the 45nm or later process technologies include support for automatically saving and restoring the performance counter registers when transitioning between VM root and nonroot modes. This simplifie s programming of the counters to increment only during the execution of the guest operating system and not during the execution of the hypervisor, which would be nondeterministic.

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86 counted by programming the event select MSRs to the appropr iate event. Once programmed, there are two general methods of accessing the count values: instrumentation and interrupt sampling. Instrumentation involves using an instruction such as RDPMC to read the performance counters. The major drawback to this appr oach is that it introduces additional instructions into the execution just to read the counters. In modern out of order designs, it is inaccurate for the purposes of deterministic execution and is not considered for this research. I nterrupt sampling is ba sed on the processor generating a performance monitoring interrupt (PMI) on the overflow of a performance counter. The interrupt sampling mechanism is used to generate PMIs at regular, although not perfectly deterministic intervals. The guests are then single stepped forward to points that are deterministic. They can be single stepped by an instruction at a time by setting the trap flag bit in the EFLAGS register or by a branch at a time by setting the branch trap flag in the DBGCTRL register. The generaliz ed method of using the performance counters to generate deterministic VM exits is depicted in Figure 4 4 and is summarized as follows: 1. Program the counter to C NT in the primary and ( CNT BUFF) in the backups where CNT represents the number of events befor e triggering the PMI and BUFF represents a buffer period for which the backup should be stopped short of the primary so that it does not mistakenly miss the point at which the primary stopped. 2. Record the instruction pointer at the point the primary replica is stopped due to the PMI. 3. Stop a backup replica at a point slightly behind the primary using a PMI. 4. Single step a backup replica forward until it reaches the same point in the execution at which the primary stopped, based on the instruction pointer.

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87 Ther e is an additional challenge that an interrupt or exception is counted as an instruction by the PMC hardware. This can cause inaccuracies when attempting to make the execution deterministic and must be accounted for. An additional challenging aspect of ins truction performance monitoring is the fact that instructions with the repeat string operand prefix (REP) are counted as a single instruction for each repetition. The problem with this is that an interrupt can occur between iterations, which can lead to an unstable execution position. Specifically, the injection of the interrupt would not oc cur on an instruction boundary. Primary replica epoch Backup replica epoch PMI TF Deterministic point Figure 4 4. Deterministic VM exit generation using performance monitor interrupts. These challenges make ensuring perfectly determinist ic PMI behavior very difficult and the prototype currently does not have full support for this feature. This feature is certainly a requirement for a productionlevel implementation of virtual lockstep, however, and has been shown to work properly when use d for similar deterministic execution applications [37]. Future processors will likely make the capability even more accurate and easier to use for this application.

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88 Virtualization Hardware Extensions The Intel Virtualization Technology extensions are a r elatively new addition to the processor hardware and were introduced in the later models of the Netburst based Pentium 4 microprocessors and later updated and improved for the CoreTMThe key benefits of the virtualization extensions are the simplification of the virtual machine monitor design and the improved levels of pe rformance typically seen over softwareonly mechanisms. The hypervisor maintains complete control over the guest operating system by defining entry and exit controls, as well as controls that specifically select which events cause VM exits to VM root mode. These controls are stored in the virtual machine control structure (VMCS), and the exit controls are summarized below. Additionally, there are certain instructions or operations that always cause VM exits. The combination of these controls ensures that the hypervisor can regain control of the platform for any type of event that might be nondeterministic. based chips. They were covered briefly earlier, but there are some specif ic attributes of the VMX hardware that are important for the project and a more detailed analysis is provided here. Pin based: Determine if external interrupts and non maskable interrupts (NMIs) cause VM exits or are delivered through the guests interrupt descriptor t able (IDT). Processor based: Determine a number of exit reasons, including control register (CR) accesses, MSR and I/O accesses, and specific instructions such as HLT, INVLPG, MWAIT, RDPMC, RDTSC, MONITOR, and PAUSE. There are also a number of controls fo r TSC offsetting, interrupt window exit, and TPR shadowing. Exception bitmap: Bitmap representing exceptions with vectors 0 31. There are certain aspects of the VMX capabilities that are not supported for deterministic execution in the prototype, however For example, interrupt and page fault delivery directly to a guest operating system is fully supported in the virtualization hardware, but allowing these

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89 operations would introduce nondeterminism into the system. Therefore, these capabilities are disable d. Interrupt Delivery One of the most important considerations in deterministic replicated execution is interrupt delivery. Interrupts are asynchronous events that can occur at almost any point in the execution stream and are often dependent on the specifi c state of the processor at the time they are handled. Therefore, delivering an interrupt even a single instruction before or after it was delivered in another replica is likely to cause a divergence in behavior. The benefit of the hypervisor based approac h is that nondeterministic interrupt arrival can be dealt with relatively cleanly. This is possible because physical interrupts can be programmed to always cause VM exits to the hypervisor, which can then inject them at deterministic points using virtual i nterrupt injection. The hypervisor can request exits on all interrupts simply by setting the exception control to exit on all vectors. It can also request notification of all external interrupts and NMIs by setting the appropriate bit in the pinbased con trol register. Finally, the remaining interrupts types, such as INIT and SIPI, are handled since they cause exits unconditionally. The difficulty comes with stopping the guest execution at exactly the same instruction boundary in all replicas so that inter rupts can be delivered. The approach taken in the prototype is to use the boundaries defined by existing deterministic VM exits as the point of interrupt injection. This technique is insufficient for some workloads since there is no guarantee that an appropriate rate of deterministic VM exits will occur. This technique can be further enhanced, however, with the use of performance monitoring interrupts and single stepping, as described above, to ensure a minimum rate of deterministic VM exits.

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90 Communication Infrastructure The inter replica communication considered for the prototype consists of a basic POSIX shared memory protocol, which does not allow for communication across network devices. The shared memory regions are configured as a series of bounded broadcast buffers accessed in a producer/consumer fashion. The primary replica places data to be shared with the backups there and once all of the backups have retrieved the data, the slot is reused. Accesses to the buffers are protected using a pthread mutex and condition variable. The specific hardware configurations supported with this form of IPC are summarized as follows: Intra die: processor cores are on the same silicon die Inter die: processor cores are on the same substrate but not the same die Inter socket: processor cores are on the same motherboard but not the same socket Prototype Implementation Details This section details the specific mechanisms used in achieving replicated execution in the KVM based prototype. This includes the capabilities nece ssary to record and replay a deterministic execution, as well as the logic to detect divergences between the replicas. A number of challenges were encountered during development in which the only timely solutions found involved the introduction of a limita tion in the prototype that did not impact the goals of the research but impacted the resultant performance or restricted the models capabilities in some way. The limitations are described in detail in this section and relaxing them is left as future work. In modifying the KVM hypervisor to support virtual lockstep, an effort is made to incorporate as many policy changes as possible into the user space portion of KVM while only putting the minimal necessary mechanisms into the kernel modules. The performanc e may be

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91 slightly lower than implementing everything in the kernel modules, but it allows for more safety and a cleaner, more flexible, and more portable implementation. Guest State Replication The first step in implementing replicated execution is to star t with a common base among all replicas. A benefit of a hypervisor based approach is that the static replication of a guest virtual machine image is trivial, even if the guest is not in a shutdown state. The entire state of the guest is represented by the data structures maintained by the virtual machine monitor, the data in the memory region reserved for the guest, and the virtual hard disk image used as the guests backing store. Static replication of the full guest image is as simple as replicating this information. For the purposes of the prototype, only static replication is considered and is done by using the hypervisors ability to snapshot the full state of the system to a single QCow2 file [68]. Guest state replication becomes significantly more com plicated if it is to be done dynamically. The challenge arises because the data to be replicated are constantly changing as the guest is executing. The most straightforward method is to begin execution of the new machine on the destination node and then re trieve all pages from the source node on page faults. Although this is relatively simple to implement, the performance is significantly affected because of the high overhead of every page fault. There is another well known method of achieving pseudolive migration of a guest, which involves statically replicating all data and then tracking the changes that dirty pages of memory. These dirty pages are iteratively synchronized across replicas until they represent a sufficiently small amount, at which point th e guests are suspended for a very short time and the remaining data are synchronized. The total downtime necessary for the final synchronization is on the order of 10s to 100s of milliseconds, which is a short enough

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92 time as to not disrupt active network connections or other functionality that would disrupt quality of service [27 ] [ 86]. Guest Synchronization There are several levels of synchronization that must be achieved depending on the degree of replication that is considered. The most basic system i s a duplex, or two node configuration, which consists of a single primary and a single backup. The replicas are implicitly synchronized based on their accesses to the shared buffers used for storing information related to nondeterministic operations. The primary can only insert an item into a slot of the buffer if it is not already full; otherwise, it stalls until the backup retrieves its next item. Similarly, the backup can only retrieve an item if the buffer is not empty and stalls if it is. Access to the shared buffers is moderated using a pthread mutex and a condition variable that is signaled whenever action is taken by a replica. This basic producer/consumer model is rather trivially extended to nmodular redundancy by allowing for an arbitrary number of backup nodes to retrieve each item. The primary records for each slot the number of backups that must retrieve the item and cannot reuse a slot until they all do. An example of this is given in Figure 45 in which there is a single primary inserting at the point marked as in There are two backup replicas that are retrieving items at two different positions out[0] and out[1] The drawback is that the entire system is slowed to the speed of the slowest backup whenever buffer space is unavailable. This is mitigated to a large extend by having a reasonable size buffer. In the prototype buffers are typically sized to 50,000 entries with a single entry being a maximum of 1KB in size. There are separate buffers created for the I/O values and the interrupts deli vered to the primary replica. The I/O value buffer stores buffer items containing the values the primary uses for its I/O string and value operations, memory mapped I/O, and RDTSC accesses. These are

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93 implicitly ordered by the fact that the backup replicas should always require the same sequence of events as long as a divergence has not occurred. The interrupt buffer stores information about the interrupts injected into the primary. Keeping these items in a separate buffer makes it easier for the backup to determine when to inject the next interrupt. Unlike values for the synchronous operations, the hypervisor managing the backup replica does not receive a VM exit when an interrupt injection is required. Instead, it must regularly peek into the interrupt buff er to determine when it needs to inject the next virtual interrupt. When it arrives at the correct position in the instruction stream, the buffer item is removed and the correct vector is injected into the guest. in out[0] out[1] Figure 4 5. Circular bounded broadcast buffer with primary inserting at in and two backup replicas retrieving from out pointers. Deterministic Execution There is significant complexity in ensuring deterministic execution, even within the constraints provided by considering a uniprocessor guest wi th the simplified virtual machine interface. A number of the specific issues and challenges to be addressed in this have been introduced in previous sections. These will be discussed here in more detail.

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94 D ND ND D EINTR 1 Inj1Pr D EINTR 2 NDInj2 D PD PD DInj1Ba D PDInj2 Figure 4 6. Deterministic execution and interrupt delivery with epochs defined by the deterministic VM exits. Figure 4 6 is provided to clarify the basic mechanims of virtual lockstep execution. The figure demonstrates a dup lex configuration with a primary and a single backup replica. The flow along the x axis represents time that is partitioned into epochs based on deterministic VM exits to the hypervisor. The se epoch boundaries are indicated with vertical dashed lines. I nterrupts being delivered to the primary system are represented by arrows labeled wit h EINTR and may be timer interrupts, for example. These interrupts are acknowledged on the physical platform and handled by the hypervisor, but they are not immediately delivered to the guest operating system, even in the primary. They must be delayed unti l an epoch boundary. Ideally, multiple interrupts could be delivered consecutively at a boundary, but most systems will likely support only one. D ND ND D ND EINTR 1 DPr1,2Pr3Ba1,2Ba3epoch1epoch2epoch3Pr Ba Ba D D PD D D PD D D PD D PD D PD D PD D Time EINTR 2 EINTR 3 Figure 4 7. Deterministic execution and interrupt delivery with epochs defined by performance counter interrupt generation.

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95 The execution of the instruction stream is labeled as D for deterministic operations, such as calculations, and ND for nondeterministic operations, such as reading a timestamp. In the backup replica, the ND operations have values defined by the primary and are labeled PD for pseudodeterministic. Finally, the Inj labels at the epoch boundaries represent the actual points of injection of the virtual interrupt into the guest operating system. The next diagram, shown in Figure 47 demonstrates a more idealized case that is made possible by PMI generation from the performance counters. In this case, the epoch sizes can be made regular in duration and minimal rate of them can be assured. This figure also demonstrates how a second backup would be integrated. It would simply execute concurrently with the first backup. This model is not fully realized in the prototype, so the remainder of the discussion is based on the first model, which synchronizes based on existing VM exits. Another mechanism found to introduce nondeterminism into the prototype is the use of Unix signals to break out of the main execution loop. This is shown in Figure 48, which is a flowchart of the main execution loop of KVM [68]. It indicates at a high level the transitions from k ernel mode to guest mode in which the guest executes and then drops back to kernel mode to handle the VM exit. If the VM exit was due to an I/O operation, the flow drops back out to use mode to handle it using the Qemu device model. When thi s completes, th e cycle resumes. There is another reason to drop out to Qemu, however, which is if a Unix signal indicates a userspace Qemu device is ready. Breaking out of the kernel execution loop gives the hypervisor the chance to do additional processing, which change s the state of the system. This causes issues since all signal delivery is nondeterministic. In order to ensure determinism, the execution is only allowed to return back to the user space at deterministic opportunities. This delays the delivery of some eve nts and has an impact on guest performance, which is analyzed in the next chapter.

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96 I/O Handle I/O Signal Pending YES Handle Exit Execute Natively in Guest Mode Enter Guest Mode Issue Guest Execution IOCTL NO YES NO User Mode Kernel Mode Guest Mode Figure 4 8. KVM execution loop diagram [68]. Prototype Limitations This section summarizes the limitations introduced into the prototype developed as a research test vehicle. Again, these are limitations that detract from the system executing some workloads and performing with minimal overhead, but it does not interfere with the stated goals of this research. A number of limitations of the prototype have already been presented. First, there are the restrictions that only Intelbased virtualization is supported and guests must be uniprocessor. The use of existing VM exits as injection points for virtual interrupts is also a

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97 limiting factor since a minimal rate of deterministic exits is not guaranteed. There are also extra restrictions placed on the scheduling due to signals. Another limitation placed on the system is the requirement that the replicated guest disk image is hosted in a ramdisk, which is a portion of main memory used as secondary storage. This is due to the nondeterminism seen when handling host page faults and has been attributed to differences in timing when accesses the hard drive. By placing the guest disk images in a ramdisk, the host does not have to fault pages in. The virtualized guest still has page faults, but these are deterministic. The final limitation applied to the prototype is that the KVM hypervisor that is in control of the virtual lockstep is not fully replicated. The Qeme process, which is user space portion of the hypervisor that encapsulates the state of the device models, as well as the majority of the replication, is fully replicated in the prototype. The kernel portion of KVM is not, however. This limitation is due to the form of inter process communication used and the desire to execute virtual lockstep within a single physical machine. By implementing the broadcast buffer logic as in a socket based protocol, it is possible to support execution across physical machines or logical partitions. Layered Virtualization One possible extension to the model as it has been presented is that of layered, or recursive virtualization [42] A limitation is imposed by the current model in that a guest virtual machine that makes use of the hardware virtualiz ation extensions cannot be supported in a fault tolerant partition. The introduction of the KVM hypervisor at the lowest level precludes a replicated guest from using the virtualization hardware since recursive virtualization or sharing of the virtualization resources is not supported.

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98 One technique for resolving this issue is through software based recursive virtualization. This involves having the lowest level hypervisor, the modified KVM hypervisor in this case, virtualize the processors virtualization hardware. This not only allows for the execution of an arbitrary guest in the system, but supports a hypervisor as a replicated guest, which may then have multiple subguests that are full virtual machines. Through the transitivity of the relationship, all of the subguests are fully protected by the fault tolerance measures applied to the guest hypervisor The requirements for layered virtualization in Intel architectures are relatively straightforward in their simplest form. It is necessary to emulate the ten VMX instructions and the virtual machine control structure (VMCS). The emulation of the instructions is trivial in all cases except for VMLAUNCH and VMRESUME and can be done by enabling VM exiting on VMX instructions, performing the necessary steps for emulation, and adjusting the instruction pointer. The emulation of the VMLAUNCH and VMRESUME instructions, as well as the emulation of a VM exit are summarized below. The guest hypervisors accesses to the VMCS are handled as they normally would be by allo wing it to read and write to the VMCS area that it set up in its own memory. This VMCS area becomes a virtual VMCS that maintains the state of the system from the point of view of that guest hypervisor. Then when the guest hypervisor attempts to launch a subguest, the guest state values of the VMCS are copied to the true VMCS with the exception of the few components that must be maintained by the true hypervisor (e.g., CR0, CR3, EFER, entry control, and exit control fields). The host state fields of the tr ue VMCS are filled in with values from the true hypervisor so that it regains control on the subsequent VM exit. Finally, when the

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99 VM exit does occur, the guest state fields and the exit reason information are copied back to the virtual VMCS. If the guest hypervisor needs to be rescheduled, then the host state fields of the virtual VMCS are used as the guest state fields of the true VMCS. When the VM exit occurs for that execution, the guest state fields of the true VMCS are copied back to the host state fi elds of the virtual VMCS. Again, the true hypervisor needs to maintain control of key fields of the VMCS, but the bulk of the data are passed through directly in this fashion. This chapter covered the development of a virtual lockstep prototype designed to prove out the model presented in the previous chapter and allow for collection of real performance and fault tolerance data. The key capabilities are support for fully deterministic execution of a standard Linux operating system, an arbitrary number of ba ckup replicas, and a powerful interface for fault injection and monitoring. These features are put to the test in the next chapter where the performance of prototype is analyzed and in Chapter 6 where the fault injection capabilities are considered.

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100 CHAPTER 5 RELIABILITY MODEL AND PERFORMANCE RESULT S The goal of this chapter is to summarize the metrics used to analyze the performance of the proof of concept hypervisor design presented in the previous chapter. The performance is assessed using empirical d ata collected from a variety of benchmarks and unit tests executed on real hardware. The tests are chosen to evaluate the feasibility and practically of applying virtual lockstep technology across a variety of different workloads. Prototype Test Platform T his section introduces the benchmarks considered in testing the prototype and gives a short explanation of the guest operating systems on which they are executed. All tests are executed on the hardware that was detailed in the previous chapter and are done with the guest operating system pinned to a single core and with no other applications running in the background. A number of different guest operating systems are considered when testing the performance of the virtual lockstep model, which is necessary t o assess its potential across a wide range of possible workloads. The kernels of different operating systems are tuned to certain use cases and can often vary quite dramatically in their behavior. For example, an operating system that is geared towards use r interactivity and video playback is typically configured with a higher rate of timer interrupts than one designed for general purpose server applications. An operating system for embedded or mobile applications may have an even lower rate to conserve pow er. The disk and network driver behavior may also vary significantly based on the oper ating system and driver design. The guest operating systems considered throughout the benchmarking workloads are categorized as follows:

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101 32bit Windows 64bit Windows guest (home user based) 64bit Linux guest (home user based) guest (server based) 64bit Linux guest (server based) 32bit Linux guest (simple, textbased) The reason for these choices of guest operating systems is to encompass the vast majority of possible system types. Even though the focus of the fault tolerance model is on low to mid range servers, there is future applicability in all areas of computing as the logic error rates and the processor core counts continue to rise. Different operating systems also tend to exhibit significantly different behaviors, some of which may be affected a great deal more than other by the side effects of ensuring deterministic operation. The specific Windowsbased guest operating systems used are a 32bit version of Win dows XP SP3 and a 64bit version of Windows Server 2008. This encompasses both the older kernel used in Windows XP and the latest kernel used in Windows Server 2008, which is the same as that used in Windows Vista SP1. The 64bit enterprise version of Linux is CentOS Server 5.2, which is the binary equivalent of Red Hat Enterprise LinuxThe minimal Slackware based Linux is used in more of the benchmarks and test cases than others for a number of reasons. First, is that being much smaller allows for more copies to reside (RHE L) Server 5.2 is used as the Linux server product and is based on a stable kernel that has performance parameters tuned to servers. The 64bit consumer desktop ve rsion of Linux considered is Ubuntu 8.04 Desktop edition, which is based on a much later kernel and is tuned to multimedia and Internet applications. Finally, t he 32bit text only version of Linux is a minimal Slackware 10.2 installation and is representative of a b asic server or embedded system.

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102 in the ramdisk necessary fo r the prototype. Additionally, by being based on a simpler operating system, it is easier to understand the effects introduced by virtual lockstep in the hypervisor. Finally, having the operating system source code available for inspection makes debugging problems easier. For example, by printing the address of the instruction pointer at all points of synchronization in the virtual lockstep model, it is straightforward to associate specific operations in question to highlevel code on the operating system and gain more context about what is happening. All guest operating systems are configured with 1GB of main memory except for the simple Slackware guest which is given only 128MB of memory, again to reduce the footprint necessary in the ramdisk area. Each has an IDE disk model and a single Intel e1000based gigabit network interface card (NIC) model which are standard devices provided by the Qemu userspace device models. The guests are stored in filebacked Qcow2 based images that support checkpointing and r esuming. This consists of storing the running state of the guest to a portion of the guest image, which allows resuming it at the same state, including the processes that were running and the state stored in main memory. In most cases, the benchmarks are m ost interesting if they generate a high level of virtual machine monitor interaction. The networkand diskintensive workloads are generally considered the best at fulfilling this requirement since they generate a high rate of interrupts and generally req uire VM exits on all input and output generated. The specific I/O based benchmarks used for the Linux systems are DBench and TBench version 3.5, which are based on the Samba Netbench suite. DBench models the disk accesses of a Netbench run while ignoring t he network traffic, while TBench models only the network accesses and does not complete the disk accesses. The corresponding benchmarks used for Windows are IOMeter for driving a high disk access

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103 rate and NTTCP, which drives a high synthetic network load. The reason for choosing these particular benchmarks is to achieve the highest sustained throughput of disk or network transactions, which lead to a similarly high level of VM exits and hypervisor interaction. Additionally, the SQLite database benchmark is executed on the Linux platforms and models insertions into a database, which is an I/O intensive process. It is executed using the standard parameters defined in the Phoronix Test Suite version 1.6 [72]. Workloads that are more processor intensive, howeve r, can for the most part be executed directly on the physical hardware with little involvement by the hypervisor. This results in a lower VM exit rate and less interaction between replicas. These types of benchmarks are used to determine the general perfor mance overhead of the replication protocols. Super Pi is a program that calculates the digits of pi to an arbitrary level of accuracy. It is used as a very processor intensive workload on both WindowsFinally, code compilation is selected as a reasonable compromise between purely processor and I/O intensive behavior. Both the standard Linux kernel and the MySQL software suite are targets for compilation. The Linux kernel is compiled single threaded and using the default compiler and config file from the guest operating system and the MySQL software suite is compiled us ing the standardized benchmark parameters defined by the Phoronix Test Suite. To clarify, the SQLite benchmark is a SQL databasebased benchmark, whereas the MySQL benchmark is strictly a standardized compilationbased benchmark. Overall, the Linux kernel compile is used most often throughout the testing given its interesting behavior profile, especially in a virtualized context, and historical use as a benchmark. and Linux platforms. The SPEC CPU2000 integer and floa ting point benchmark suites are also used for some tests since they are an industry standard and provide well known patterns of behavior.

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104 Replication and Synchronization Overhead The first step in replicating a guest operating syste m is replicating its state across multiple cores. The state includes all information necessary to run the guest, including the secondary storage and the dynamic memory image if the guest is saved in a running state. This section analyzes the size of the st ate images and the performance costs associated with doing the replication and maintaining synchronized state. Replication and Reintegration Costs The initial data considered are that of the static replication costs for typical guest configurations. The go al of this analysis is to estimate the typical memory footprint of an operating system, as well as to determine the approximate replication time. These values are representative of the time necessary to do the initial guest copy when the system triggers th e dynamic creation of a new replica based on an executing guest image. It also represents the approximate amount of information necessary for transfer during the reintegration process following a replica failure. Table 5 1 shows the size of the compressed snapshots associated with the guest operating systems, as well as the time required to generate and subsequently duplicate the image on the hard disk or ramdisk. The replication times are included for both types of media because the prototype executes gues ts in a ramdisk and because the speed of the ramdisk storage is much more representative of the speed of hard disk technology in the near future, when the virtual lockstep model is expected to be most useful. In fact, there are already products that provide a battery backup and allow using DRAM as a replacement for a standard SATA drive, and with new breakthroughs in technologies such as solid state disks (SSD) and phase change memory (PCM), secondary storage will soon have bandwidth and latency performance approaching that of modern main memory [58] [ 70 ].

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105 Table 5 1. Guest static snapshot replication size, image size, and state transfer time for a variety of guest operating systems. Operating System Size (MB) Generation (ms) Hard Disk ( m s) Ramdisk (ms) Sl ackware 10.2 6.6 1,220 73 22 CentOS 5.2 54 12,320 600 180 Ubuntu 8.04 91 18,910 1011 303 Windows 57 XP SP3 9,980 633 190 Windows Server 107 2008 16,550 1189 357 It is clear that even the smallest guest image requires a long enough state captur e time to cause a noticeable disruption if done with the source guest halted. The state transfer times on a standard hard disk are high enough at over a half second for most guests to be troublesome, and the larger guests have a total state replication time that simply would not allow them to be done in a transparent fashion using a stopand copy approach, even with very fast processors and ramdisk based transfer rates. The results of the state transfer benchmarks indicate that it is beneficial to do the in itial and reintegration replication while the guests are online, which is similar to what is done in live migration [27 ] [ 86]. The online copying done in a live migration allows the source to continue to execute, at least with degraded performance, for mo st of the state capture and transfer time and only pause for a very short interval to synchronize the last of the state. Fortunately, live migration is wellsupported in most modern hypervisors and extended it for this purpose should be straightforward. Th e next step in determining the feasibility of a replicated system is an estimation of the required capacity of the communication backbone. The estimates are based on the number of replicas, the size of the data transferred between replicas, and the rate of transfers necessary.

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106 These values vary depending on the level of replication applied, the fault tolerance protocol implemented, the guest operating system behavior, and the workloads that are being replicated. The worst case workloads are those that have the highest rate of nondeterministic events and require the most data to be transferred. The types of data that must be communicated from a primary to the backup replicas includes all nondeterministic values read in, as well as timer events, interrupts, ex ceptions, I/O, and MMIO data. Additionally, the values transferred via DMA need to be included if DMA is supported. The first data, presented in Figure 51, are the total VM exit rates for a number of operating system and benchmark combinations. The values represent a normalized VM exit rate for all exit reasons, averaged over the entire benchmark. The highest exit rates exceed 180,000 per second and are not constrained to a single operating system or benchmark. The MySQL compilation and SQLite benchmarks both approach this value, while the kernel compilation benchmark averages about 60,000 exits per second. The diskbased benchmarks tend to a lower rate and clock in at around 20,000 exits per second, although the Windows Server 2008 IOMeter benchmark hit 100,000 per second. As expected, the compute operating systems. In summary, this analysis shows that there is easily three order of magnitude variation between the expected VM exit rates for various workloads and that, in the worst case, it is not unreasonable to expect a quarter million to occur every second. Many of these exits are lightweight and do not require a transition to user space, but adding even a small amount of overhead could ha ve a severe impact to performance. Fortunately, many of these exits are already fully deterministic and only a small subset of them must be intercepted for virtual lockstep.

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107 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000 Exits / second Figure 5 1. VM exits per second for various combinations of operating system and benchmark. The next set of data, presented in Figure 5 2 break the VM exit reasons down into the specific types that require intervention when implementing virtual lockstep. These are exits for which values of nondeterministic operations must be recorded and transferred from the primary to the backups. They are categorized by the buffer item types defined in the previous chapter and multiplied by the size of the data that must be transferred. In the case of RDTSC, each exit is multiplied by 8 bytes since this is the size of the value returned to the guest. For the I/O and MMIO operations, the actual size of the data is tracked and accrued, and for interrupt operations the size of the instruction pointer, as well as the interruption info register are conside red. The result is the steady state bandwidth necessary to maintain virtual lockstep, assuming no compression is used.

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108 0 100 200 300 400 500 600 700 800 900 Kilobytes / second I/O Read I/O Write MMIO Read MMIO Write RDTSC Interrupt Figure 5 2. Total bytes per second of nondeterministic data for various combinations of operating system and benchmark. In most cases, the rate maxes out at approximately 100 KB/s, although a few benchmarks stand out. Namely, the SQLite benchmarks on the Linux guests and the IOZone benchmark on the Windows Server 2008 guest. In all of these cases, there is a very high rate of RDTSC opera tions with over 80,000 per second for the SQLite benchmark running on the Ubuntu Linux guest resulting in a bandwidth requirement of approximately 640 KB/s just for passing timestamp counter values. Interestingly, Windows XP does not show the same behavior as Windows Server 2008 with regard to reading the timestamp counter, even for the same benchmark. It apparently uses another means of synchronization. The other benchmark that stands out is the NTTCP network benchmarks which show a very high rate of vir tual interrupts

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109 and MMIO accesses, which again indicates how different operating systems can essentially do the same thing in significantly different ways. In addition to anticipating the total bandwidth necessary for various workloads, additional conclusi ons can be drawn from this last set of data. The first is the property just described, which is that different operating systems often demonstrate very different behavior for similar, or even identical, workloads. As such, any productionlevel implementation of virtual lockstep must take this into account and find the true worst case scenarios while avoiding optimizing for a single operating system or a handful of workloads Additionally, it is apparent that some hardware support may be beneficial to reduce the overhead of RDTSC, and possibly virtual interrupt injection operations. For example, if a deterministic RDTSC operation could be developed or a method of reducing at least some of the interrupts that must be recorded, the data rate could be substantia lly reduced in the worst case benchmarks. Virtual Lockstep Benefit Analysis To estimate the benefit of incorporating the hypervisor into the sphere of replication, data are presented which show the percentage of time a guest is running on a processor (laun ched time) versus the time it is under the control of the hypervisor. The launched time is defined to be the time the processor is executing code on behalf of the guest and is derived by instrumenting the hypervisor to record the hardware timestamp counter before each guest resume and again at each VM exit. These values are summed over the entire benchmark execution and compared to the total execution time. The guest is pinned to a single processor and the host in which the hypervisor is running is otherwis e unloaded. This method of accounting results in a worst case view given that all idle time, such as when the guest is waiting on the completion of I/O operations or otherwise halted, is allocated to the hypervisor. It does, however, give insight into the nonnegligible time

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110 spent executing hypervisor code in some workloads and the need for protection so that it does not become a new single point of failure within the system. 0 20 40 60 80 100 120 140 Runtime (s) Hypervisor Runtime Guest Runtime Figure 5 3. Total runtime for various combinations of operating system and benchmark broken down by time spent running in the guest and time spent in the hypervisor. The guest launched rates range from less than 9% for the Slackware guest executing the DBench benchmark up to more than 99% in some of the strictly cpubound workloads. T his means that the time spent in the hypervisor range from approximately 1% to 91% with an average of 39% across all workloads. These are the times at which the replicated guest is not executing on the processor, so a fault in the processor may not directl y affect the state of the guest but instead bring down the hypervisor itself or possibly the whole platform if it is not also replicated. The launch rate data are summarized in Figure 5 3 where the values are presented as the number of seconds of the total runtime spent in each of the two domains.

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111 Additional information about the VM exit behavior and the time spent in the hypervisor is given in Figures 5 4 and 55. The labels in the legends for these figures are defined in Table 5 2. Table 5 2. Definition of exit reason labels. VM Exit Name Description EXCEP Exception A processor exception, such as page fault INTR External Interrupt Physical interrupt from the platform INTR_WIN Interrupt Window Indicates guest can accept virtual interrupt CPUID CPUID Guest requested information about the CPU HLT Halt Guest executed a halt instruction INVLPG Invalidate Page Guest requested page of TLB to be flushed RDTSC Read Timestamp Guest read the timestamp counter register CR Control Register Access Guest r ead or wrote a control register I/O I/O Access Guest did an IN or OUT I/O operation MSR MSR Access Guest accessed model specific register TPR Task Priority Register Guest accessed or set the task priority register APIC APIC Access Guest read or wro te an APIC register The data presented in Figure 54 break down the percentage of each type of unique exit reason. There are a surprisingly few unique types of exits, although a many of them have a large number of subcategories. For example, there are m any different exception reasons that can occur, but most of the ones seen are page faults. There are also multiple control or registers that may be accessed and many different I/O ports or operations that are possible. This level of granularity does offer a reasonable level of insight into the behavior, however. It is apparent that the page faults, I/O operations, APIC accesses, and timestamp counter accesses make up the bulk of the

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112 exits in most benchmarks. This narrows down the scope of the performance tuning to only a few different operations. As long as minimal overhead is added to each of these operations, the total performance impact should also be minimal. Fortunately, the only exit type that is nondeterministic in most cases is the timestamp counter read, which is validated by the bandwidth estimation previously discussed in Figure 52. There are some instances where page fault handling may occur nondeterministically, likely due to spurious page faults, but this should be manageable by most hypervisor s. The I/O operations also require intervention to record the values of the operations. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % of Total Exits EXCEP INTR INTR_WIN CPUID HLT INVLPG RDTSC CR I/O MSR TPR APIC Figure 5 4. Break down of the VM exit reasons while executing the test workloads. Figure 5 5 breaks down the percentage of time spent by the hypervisor in the handling of each of the VM exit reasons that showed up as a non negligible percentage of the total time. The

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113 remaining reasons account for the few plots that dont extend the full length of the y axis. In the case of the I/O bound workloads it is apparent that much of the time is spent with the processor waiting in a halted state for the work to do and a smaller percentage of the time handling page faults and accessing the APIC. There is also obvious variation across operating systems. For example, Windows Server 2008 does not halt during the I/O Zone benchmark as Windows 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % Total Handling Time EXCEP INTR INTR_WIN CPUID HLT INVLPG RDTSC CR I/O MSR APIC XP does. Figure 5 5. Percentage of total runtime spent in the hypervisor broken down by the specific exit reasons while executing the test workloads. Many of t he cpu bound workloads, on the other hand, are dominated by I/O operations and page faults, with some time spent also accessing the APIC and control registers. The few items that stand out are the high overhead of handling all the page faults in the MySQL compilation, as well as the expe cted high rate of I/O writes that occ ur during the SQLite benchmark. These data

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114 indicate that in some of the worst case benchmarks in terms of total VM exits, there is a significant amount of time that is spent halted, which should act as a buffer to offse t the extra processing requited for virtual lockstep operation. It also shows that much of the remaining time spent in the hypervisor is allocated to handling the I/O operations, which is where much of the recording is done for virtual lockstep. As long as the inter replica communication buffer as fast as or faster than the I/O devices in the platform, the resultant handling time should be no more than half speed. Virtual Lockstep Performance Overhead The data presented in this section indicate the performa nce overheads seen in the virtual lockstep prototype. The comparisons are made by evaluating the performance of the guest operating system being virtualized using the standard KVM 33 hypervisor versus the performance of the same guest image running on the virtual lockstep capable version of KVM 33. All benchmarking is done using the test platforms described in the previous chapter and the guest operating system used is a standard installation of the 32bit Slackware 10.2 Linux distribution. The data present ed in Tabl e 5 3 indicate the percentage of performance overhead introduced in a standard Linux kernel compilation. The kernels used include the version 2.4.31 kernel that is part of the Slackware 10.2 operating system, as well as a Linux 2.6.20 kernel downloaded from the public Linux repository. The compilation times are recorded separately for the primary and the backup replica since the backup tends to lag slightly behind the primary. Times are given for the virtualized case, which is running the standard KVM hypervisor, and the lockstepped case, which makes use of the custom KVM hypervisor with virtual lockstep support. The rate of deterministic exits is also given, which gives an indication of the rate at which

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115 interrupts can be injected into the guest. Finally, the percentage overhead in terms of additional compile time is given. The 2.4.31 kernel is much smaller and simpler than the 2.6.20 kernel and incidentally has a much higher percentage overhead associated with it. The first indication of the reason for this is seen in the deterministic VM exit rate, which is significantly lower than for the larger kernel compile. This means interrupts are delayed by a larger amount, on average. Table 5 3. Virtual lockstep performance overhead summary. Primary Virtu alized Lockstepped Det. VM Exits Exits/s Overhead Linux 2.4.31 128.5s 135.1s 568K 4,204 5.1% Linux 2.6.20 255.3s 258.8s 1.568M 6,059 1.4% Backup Linux 2.4.31 128.5s 135.6s 568K 4,189 5.5% Linux 2.6.20 255.3s 259.2s 1.568M 6,049 1.5% The data pr esented in Figure 56 demonstrate the performance of the virtual lockstep replica under varying degrees of fault tolerance, as well as varying sizes of the inter replica bounded broadcast buffer. The same kernel compile benchmark is used as the previous te sts, although the execution is done on the faster of the two hardware platforms used in testing, which results in the numbers being slightly faster. The values are also the average of at least 30 runs of each configuration and have a very low variance. The configurations considered range from a single backup (dual modular redundant) up to three backups (quad modular redundant), which is the limit of the quadcore hardware being used. The size of the buffer is varied from 5,000 entries up to 80,000 entries. Given that each

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116 buffer entry is approximately 1KB in size, the total size of the buffer then ranges from approximately 5MB to 80MB. 0 20 40 60 80 100 120 140 DMR 5k DMR 10k DMR 20k DMR 40k TMR 5k TMR 10k TMR 20k TMR 40k QMR 5k QMR 10k QMR 20k QMR 40k QMR 80k Time (s) Primary Time Backup 1 Time Backup 2 Time Backup 3 Time Figure 5 6. Total runtime of primary and either one replica (dual modular redundant), two replicas, (triple modular redundant), or three replicas (quad modular redundant) with a shared buffer size ranging from 5,000 entries to 80,000 entries. It is apparent that the coordination of the extra replicas has a small performance penalty associated with it. That is the single back up configuration runs slightly faster in all cases than a dual backup configuration. These both execute slightly faster than the triple backup configuration. Also, while increasing the size of the buffer shows little benefit when a single backup is used, i t does offer a noticeable improvement for the other levels of redundancy, at least to an extent. The performance of the primary continues to improve as the buffer is increased since it allows the backups to lag further behind, but what really matters is th e overall runtime in

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117 which all replicas finish the task. The optimal overall runtime for the dual backup case is at 10,000 entries, while performance continues to improve in the triple backup case all the way out to 40,000 entries. Most importantly, these data indicate that higher degrees of replication are practical in terms of performance, although they are quite expensive in terms of additional hardware. It is reassuring, however, for very high levels of redundancy to be transistor count limited rather t han transistor performance limited, given that Moores Law and the direction of the industry is to continually improve the transistor counts. Additionally, the data indicate that tuning of the buffer size plays an important role in optimizing performance a nd that bigger doesnt always result in better overall performance. This chapter covered the benchmarking done for the initial scoping of the virtual lockstep prototype, as well as the real world performance data gathered from the prototype implementation. The goals of the initial benchmarks were to highlight important parameters related to realizing virtual lockstep. This included determining which types of VM exits are nondeterministic, the average rate of these exits, and the total number of bytes expect ed to be transferred in both initiating and maintaining virtual lockstep. Then, in analyzing the performance of the working prototype, data were presented that gauge the performance penalty incurred when compared to standard virtualization. The parameters of the replication were also varied to demonstrate the high degrees of replication are practical from a performance perspective and that the tuning of the communication buffer is an important part of determining the overall virtual lockstep performance.

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118 CHAPTER 6 FAULT INJECTION AND VIRTUAL PROCESSOR ST ATE FINGERPRINTING This chapter covers an enhancement to the virtual lockstep model in which faults in the system are detected much sooner than by the typical method of monitoring the output generated by t he processor. The values in the registers representing the state of the virtual processor are hashed into unique fingerprints that are regularly compared across replicas. The benefits of this approach are analyzed using a powerful register based fault inje ction capability that is made possible by the virtual lockstep model. Fault Injection Model In order to test the efficacy of the proposed fault detection mechanism, it is necessary to have a fault injection infrastructure in place. The model of fault injec tion considered is based on the perturbation of processor register state in the form of single event upsets (SEUs) that represent a particle striking a bit and causing the value to change or possibly a bit failing to due to wear out effects. The model take s advantage of the control the hypervisor maintains over the state of the guest operating system to introduce the bit failures by changing the values stored in system registers. Fault Injection Details As described previously, the hypervisor is responsible for maintaining the virtual processor state representing the guest system it is hosting, and in order to improve performance, some of the state handling may be done with hardware assistance. In fact, in KVM based virtual lockstep prototype many of the reg ister values representing the virtual processor state of the guest are stored in the VMCS structure. Those that are not must be manually saved and restored by the hypervisor each time the guest exits to the hypervisor or is resumed, respectively. Additiona lly, most hypervisors, including KVM, already have mechanisms defined for consolidating the guest

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119 state so that it can be migrated to another system or a snapshot can be saved for recovery at a later time. Injecting a fault into a register of a running gue st virtual machine is relatively straightforward. The virtual machine model has a clear boundary defining when the guest state is transferred to the processor for the resumption of execution. Fault injection is done by modifying the hypervisor to access th e register at this point and inject a bit flip by doing an exclusive OR operation on the register with a bitmask that has a one set for the bit position that has been targeted for corruption. The faulty register is then loaded into a physical register on t he processor and execution progresses as if the bit had been struck by a particle. Stuckat and multibit faults can modeled in a similar fashion by changing the logic operation or bit mask being applied to the register. Fault Propagation Analysis In order to detect the divergence in behavior the fault causes, if any, it is necessary to have a baseline to compare the execution to. Unfortunately, this is not as simple as executing the benchmark on the system once and then comparing the behavior to a second r un when a fault is injected. The reason is that guest execution varies slightly each time it is run. For example, asynchronous events, such as interrupts, are delivered at different points in time and values read from input sources, such as the timestamp c ounters, vary by run. The problem is that all of these types of nondeterministic events that cause divergence in behavior cannot be distinguished from a divergence that is caused solely from the injection of a faulty bit. This is where the virtual lockste p functionality comes into play. The technique proposed in this dissertation is to execute a duplex system in virtual lockstep so that it has all of the nondeterminism removed and then inject faults into only the backup replica while the primary continues to define the behavior of the system. Alternatively, a deterministic recording could be

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120 taken and then replayed multiple times with a different fault injected each time. In either case, the execution is known to be repeatable. When a divergence does occur, it can be attributed to the bit flip, at least up to the point at which an incorrect type of value is passed from the primary to the backup. As described in Chapter 3, if the backup diverges in such a way that it arrives at a point of requiring a value for a particular type of operation, but the next operation for which the primary has defined a value f or is of another type, it does not prove beneficial to continue execution. The act of giving the backup the values in a different order than was defined by the primary does not provide additional useful information since that in itself is expected to cause a divergence. In fact, the primary may not have even defined such a value. Specifically, the behavior of interest is the execution of the backup from the point of the fault injection until the point at which it either fails or requires the introduction of an additional form of nondeterminism. Of course, the execution may not diverge, in which case the fault was either masked or planted as SDC waiting to be e xposed at a later time. Processor State Comparisons A major limitation of detecting fault using the comparison of deterministic input value types and output values is the delay possible from the point of injection until the error is observed. This delay ma kes checkpoint and restore operations much less efficient since there is a significant chance that the checkpoints may be recorded with the fault present but not yet exposed [24] This results in having to maintain multiple checkpoints and having to iterat ively try recovering from them until one is found that is old enough to not contain the fault. Additionally, the average detection delay limits the rate at which checkpoints can be taken. This is troublesome since highspeed checkpointing is considered to be a possible mechanism for achieving virtual lockstep like operation for multiprocessor guests. One technique that can be

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121 used for reducing the fault detection delay is to monitor the internal processor state at regular intervals. The processor state b eing considered is composed of the registers in the processor core. This section introduces virtual processor state fingerprinting, which takes advantage of the processor state structures maintained by the hypervisor to detect divergence before they appear at the I/O interface of the processor. Virtual Processor State Fingerprinting Since the hypervisor must maintain the register state of its virtual guests, it is straightforward to access this information on any VM exit and compare it across replicas. The size and number of registers vary by architecture, and even by model within a given architecture, but the total size of all the registers in most modern processors is on the order of kilobytes. This makes it impractical to transfer and compare the complete register state among all replicas. Since the goal is to detect faults significantly earlier than I/O based comparisons, the state must be compared very often ideally on every VM exit. If this were the case, the amount of data transferred for the state com parisons would far outweigh the amount of data required to maintain virtual lockstep. Processor state fingerprinting is an optimization that can be applied to reduce the amount of data being transferred between processors. It also simplifies the comparison at the cost of extra computation necessary to compute the fingerprint. It works by hashing the register state of the virtual processor into a unique fingerprint that is transferred and compared. The one major drawback of this approach is that it loses inf ormation about exactly which state has diverged, but this is typically not necessary to have. Simply knowing that an error is present is sufficient information to trigger a rollback to a known good state.

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122 Hashing Details There are countless different hashi ng algorithms that could be applied to the virtual processor state, ranging from simple bit level operations to advanced cryptographic coding such as SHA 2. In most cases, the simple hashes are sufficient given that aliasing is not a critical problem. In t he unlikely event that a faulty processor state does happen to hash to the same value as the nonfaulty state for one of the state comparisons, it will merely delay detection until the next comparison. The hashing algorithm used for the prototype is a very simple additive and multiplicative algorithm that was developed by Robert Sedgewick and is defined in Figure 6 1 [105]. Figure 6 1. Robert Sedgewick hash function code. In Table 6 1, the performance of the RSHash algorithm is compared to cryptographic SHA hash algorithms. The algorithms are tested by hashing a single 4KB page of memory that has been filled with random data and averaged over 1,000 trials. The 4KB memory size is representative of the maximum size of the VMCS, and as such, the typical size of the memory region used in processor state fingerprinting. It is apparent that the overhead of the SHA routines is simply too high to be practical for highspeed fault detection. unsigned int RSHash ( char str unsigned int len ) { unsigned int b = 378551 ; unsigned int a = 63689 ; unsigned int hash = 0 ; unsigned int i = 0 ; for ( i = 0 ; i < len ; str ++, i ++) { hash = hash a + (* str ); a = a b ; } return hash ; }

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123 Table 6 1. Hashing performance of various algori thms for a random 4KB page of memory Algorithm Hash time (s) RS 128 0.57 SHA 224 8.28 SHA 256 8.39 Fingerprinting Optimizations There are a number of additional optimizations that are applicable to the virtual processor state fingerprinting process. The first is the use of hardware based virtualization extensions and data structures to facilitate hardware based performance enhancements. As described in Chapter 2, the Intel architecture defines the VMCS is used to store the most important virtual proce ssor state of a guest, as well as a number of control and status fields. This structure is stored in memory and is under full control of the hardware. In fact, the hypervisor does not even know the layout of the memory and must use accessor instructions to read from it and write to it. The fact that it is controlled by hardware makes it simple to optimize with specialized hardware or microcode. For example, circuitry could be added to the chip to do the fingerprinting or it could be done with an idle core on the processor. This significantly reduces the overhead associated with doing the hashing. The second optimization is the possibility of selective state filtering based on fault detection behavior analysis. As is demonstrated later in this chapter with the data collected using the prototype hypervisor, not all state is necessary to achieve the benefits of early fault detection. That is, there are certain registers, or in the case of the prototype, certain VMCS fields that are more sensitive to fault injection than others. By conducting many trials while injecting faults at random points i n the execution of programs, it i s possible to determine which registers or fields

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124 most often fail. The hashing can be further optimized by only including these items in the computation. Yet another optimization is in the transfer of the fingerprint among replicas in a system that is configured with triplex or greater level of redundancy. Rather than having all replicas send the fingerprint to all other replicas, any diverge nces can be stored within the buffer. This works by locking the broadcast buffer entries and having the first backup to detect a divergence store the fingerprint it generated along with the fingerprint that was stored there by the primary. When the next ba ckup accesses that position, it detects the additional fingerprint value and is able to vote on which is correct. Of course, if the second backup detects a divergence that the first did not, it will store its fin gerprint value there but it will no t matter since a majority of replicas have already proceeded past that point. KVM Prototype Fault Injection Fault Injection Overview For the purposes of data collection in this research, the targets for fault injection are limited to the system, control, and genera l purpose registers in the processor. T hese are summarized in Table 6 2, which uses a common shorthand representation that is read as R[S,D]I is RSI and RDI. The injection of faults into memory regions such as the stack, heap, or active memory of the guest are interesting but are not within the scope of this work. Such modeling could easily be done using the same technique described above, but it is assumed that the memory is already well protected by ECC within the modules and possibly mirroring across modules. The two bit positions targeted for fault injection in most registers are 4 and 16. The main reasoning for this is to flip both a lower order bit so that the affected value, often an address, will move only a small amount (e.g., between two and 16 ins tructions in the case of RIP), as well as a higher order bit to cause a more significant change in the value. For registers in which bits are

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125 defined for special purposes, such as the control registers and the RFLAGS register, all meaningful (i.e., not res erved) individual bits have been targeted. This targeted approach provides more concise information with fewer runs than fault injection methods that randomly inject into all bits in all registers. It is especially useful to be able to relate functionally significant bits such as those in the control registers to the behavior observers after the fault injection. Table 6 2. Fault injection target registers and their inclusion in the VMCS Register VMCS Description RIP, RSP Y Instruction and Stack Pointers RBP N Base Pointer RFLAGS Y Flags Register R[S,D]I Y String Op Source and Destination CR[0,3,4] Y Control Registers [C,D,E,F,G,S]S Y Segment Register Base Pointers TR Y Task Register [I,L,G]DTR Y Descriptor Table Base Pointers R[A,B,C,D]X N General Purpose Registers The data presented below are based on faults that are injected during a standard compilation of the Linux 2.4.31 kernel. The time of the injection is varied randomly for each trial and repeated a minimum of 500 times for each bit positi on. The compilation is run for 10,000 deterministic exits as a warmup phase plus a random number of additional deterministic exits from 1 to 216 before the fault is injected into the bit After injection, the guest is run for at least

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126 100,000 additional deterministic exits, which is on the order of the runtime considered in related work [73] [ 75] [ 100]. There is a possibility that a fault injection into a guest may cause the host platform to crash or hang, especially when it causes a significant disrupt ion to the platform, such as changing the paging mode. Once the paging mode is changed, the page tables are walked incorrectly by the hardware and may direct certain operations to invalid portions of memory or memory that belongs to another guest Behavior in which the host kernel was corrupted and crashed was observed approximately 2% of the fault injection trials targeting the CR0 and CR3 control registers and occasionally for some of the RFLAG register bits. The detailed results are provided in the next section of this chapter. These fatal host kernel crashes may be reduced or avoided by implementing certain protection mechanisms in the fault injection architecture [73]. Protection on real hardware is possible by replicating across physically or logically partitioned systems so that the memory regions of the hosts are protected from one another. This eliminates the possibility of the guest affecting the memory of other hypervisors or other guest virtual machines. It is for this extra degree of protection t hat partitioned replication is the preferred configuration for the generalized virtual lockstep model. Fault Injection Performance Results The results of fault injection into the virtual lockstep prototype are detailed in the following graphs. These result s are based on single bit flip injection into registers of the backup replica while executing a kernel compile in a Slackware 10.2 guest virtual machine. The registers injected into are labeled in the plots according to the n omenclature defined in Table 6 2, and the bit positions targeted are labeled in braces and are based on the bit selection process defined previously.

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127 The first fault injection data considered are presented in Figures 6 2 through 67 and are the highlevel behavior of the guest virtual machine after the fault injection. These are categorized into one of four categories: Crash, No Crash, H ang and Lockstep Fail The Crash case means that the guest failed in some fashion in which the hypervisor and the guest kernel are aware of the crash. A n example of this is when Linux does a core dump and shuts down or the equivalent is a WindowsThe lockstep failure happens when a divergence in execution occurs between the replicas that causes different types of deterministic exit reasons to be generated. For example, if the primary replica generates a RDTSC value but the backup has diverged in such a way that it requires an I/O value instead of the RDTSC, the system is shut down. It does not make sense to provide the deterministic values out of order, as they may not even exist. blue screen. The few cases in which the host kernel crashes are also included in this category. No Crash means that the kernel compile continued for at least th e 100,000 additional deterministic VM exits after injection, or until completion of the compilation. In other words, the guest ran apparently unaffected with the detection of a fault by the inherent mechanisms of virtual lockstep. T he Hang category include s cases in which the guest gets into an endless loop and does not crash but instead hangs the CPU it is executing on. Finally, the Lockstep Fail category defines cases in which virtual lockstep can no longer be maintained. Guest hangs are limited to the process encapsulating the virtual machine and are detected using a form of software watchdog timer that looks at the number of total VM exits and compares it against the pre determined upper bound on the number of VM exits that should occur during the kernel compilation. This works since the total VM exit count continues to i ncrement, due to platform external interrupts for example, even if the guest execution is stuck in a loop.

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128 When the total number of VM exits reaches 50% more than a target value that was determined from preliminary test executions a special VM exit reason that has been defined explicitly for this purpose is taken to force the hypervisor out of kernel mode and allow the guest to be cleanly killed. If this were not done, the Qemu process encapsulating the virtual machine would be uninterruptible and as such, not killable without resetting the physical platform. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % Trials Register [bit] Crash No Crash Lockstep Fail Hang Figure 6 2. Fault injection failure distribution for control registers. Figure 6 2 depicts the failure distribution of the system control registers and Tables 63 through 65 describes the meaning of the bits considered in these registers. As their name suggests, t he control registers control the operating mode of the processor. CR0 has controls for paging, memory caching and write protection, floating point ope ration, and task switching. As seen in t he results t his register is obviously very sensitive to fault injection and crashes the guest

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129 nearly 100% of the time, while occasionally bringing down the host with it. The two bits that stand out slightly for crashing the host platform are bit 0, which changes the execution mode of the processor, and bit 31, which changes the paging mode of the processor. These are both very disruptive changes and it is actually surprising that the host is not affected more often given that no special support was impleme nted for protecting it. Table 6 3. Control register CR0 bit descriptions Bit Description 0 PE Executes in real mode when clear and protected mode when set 1 MP Defines interaction of WAIT/FWAIT instructions with task switch flag 2 EM Disables fl oating point support when set 3 TS Allows delayed saving of floating point state on task switch 16 WP Write protects user mode read only pages from supervisor mode writes 31 PG Enables memory paging when set and disables it when clear The CR3 re gister contains the base address of the guests memory region, as well as flags controlling the caching behavior of the chip. Not surprisingly, the bits controlling the caching behavior, bits 3 and 4, are not very sensitive and only very rarely cause a dis ruption. The higher order bits, which are those defining the base address for memory paging hierarchy do however, cause the system to fail if they are altered again bringing d own the host from time to time. There is little difference in the degree to whic h the paging base which is defined by the higher order bits of the register, is altered, as both bit positions result in essentially equivalent behavior in terms of crashing Table 6 4. Control register CR3 bit descriptions Bit Description

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130 3 PWT Contr ols whether paging is write through or write back 4 PCD Controls whether the page directory is cacheable or not 16 Bit 5 of the page directory base used to define root of page hierarchy 24 Bit 13 of the page directory base used to define root of page hierarchy Finally, t he CR4 register has flags that enable architectural extensions such as virtual 8086 mode and physical address extensions (PAE) in 32bit platforms. As with other control registers, these bits are very sensitive and nearly always cause the guest to crash or hang. It is notable that bit 5, which enables PAE mode to change the paging hierarchy add an additional level stands out as causing significantly more system hangs more than the other bit positions Table 6 5. Control register CR4 bi t descriptions Bit Description 0 VME Enables interrupt and exception handling of virtual 8086 mode when set 1 VIF Enables support for virtual interrupt flag 4 PSE Enables 4MB pages when set and 4KB when clear 5 PAE Enables 36 bit addressing ex tensions when set and 32 bit addressing when clear 7 PGE Enables global paging when set, which avoids flushing TLB entries Overall, with the exception of the caching control bits in CR3, the control register bits are clearly critical to correct system operation and a bit flip in any of the defined bit positions is detrimental. It should be noted that all reserved bit fields have been excluded from testing. Ideally, these should not affect correct system operation, but their behavior is designated as undefined by Intel. There are also a number of bits that have been excluded from CR0 and CR4, which are for processor functionality that is not expected to be exercised by the software used to conduct the tests.

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131 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% CS[4] CS[16] DS[4] DS[16] ES[4] ES[16] SS[4] SS[16] FS[4] FS[16] GS[4] GS[16] % Trials Register[bit] Crash No Crash Lockstep Fail Hang Figure 6 3. Fault injection failure distribu tion for segment registers. The segment base registers are considered in Figure 6 3. These are part of the series of registers that define each segment used in the processor. In addition to the base registers, there are corresponding limit and access right registers which are not considered in the fault injection testing. The base registers identify the beginning addresses for each segment and are used as an offset for indexing into the memory regions they define. The CS, DS, and SS registers are defined as the code segment, data segment, and stack segment, respectively. The remainder, ES, FS, and GS are additional data segments that may or may not be use by software. This description aligns well with the results of the fault injection in which CS, DS, and SS practically always cause a crash, where ES, FS, and GS result in a guest failure at a much lower rate.

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132 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% GDTR[4] GDTR[16] IDTR[4] IDTR[16] LDTR[4] LDTR[16] TR[4] TR[16] % Trials Register[bit] Crash No Crash Lockstep Fail Hang Figure 6 4. Fault injection failure distribution for system descriptor table s and the task register Data for t he descriptor tables and the task reg ister are depicted in Figure 6 4. These registers are for memory management and define the location of the related data structures. The global descriptor table register (GDTR) contains the base address of the GDT, which is a list of segment descriptors tha t are accessible by all programs. Similarly, the local descriptor table register (LDTR) contains the segment descriptors local to each task. The interrupt descriptor table register (IDTR) is a special set of descriptors, specific to interrupt handling rout ines, and finally the task register (TR) is used to store the segment selector and descriptor for a new tasks task state segment (TSS) when a task switch occurs. Again, much like the control registers, these are very critical registers and are highly sens itive to alteration. A single bit flip repositions the tables and likely destroys every entry contained within them.

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133 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% RAX[4] RAX[16] RBX[4] RBX[16] RCX[4] RCX[16] RDX[4] RDX[16] % Trials Register[bit] Crash No Crash Lockstep Fail Hang Figure 6 5. Fault injection failure distribution for general purpose registers. As indicated by their name, the general purpose registers (GPRs) in Figure 6 5 are used for a variety of operations. The general usage model is as follows: RAX is the accumulator for ALU operations, RBX is a pointer into the data segment, RCX is a counter, and RDX is an I/O pointer. In general, faults in these r egisters only results in crashes or failed lockstep execution, about 5% of the time. This is not surprising since a fault is significantly more localized than it is with a segment base or a control register. A fault introduced into one of these registers likely just causes a single value to be changed, an incorrect memory address to be accessed, or a loop to be executed an incorrect number of times. There seems to be little correlation between the bit position and the rate of failure. That is the higher bi t causes a higher failure rate in RAX and RBX, but a lower failure rate in RCX and RDX. None of these fault types appear to lead to

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134 system hangs or crashes and instead the faults that are detected are done so by the virtual lockstep process. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% RBP[4] RBP[16] RSP[4] RSP[16] RIP[4] RIP[16] RSI[4] RSI[16] RDI[4] RDI[16] % Trials Register[bit] Crash No Crash Lockstep Fail Hang Figure 6 6. Fault injection failure distribution for various system registers. Next is Figure 6 6, which includes additional system registers. In particular, there is the base pointer (RBP), stack pointer (RSP), instruction pointer (RIP), and string source (RSI) and destination (RDI) registers. These each serve unique purposes. RBP points to data on the stack, RSP points to the stack itself, RIP indicates the next instruction to be executed, and RSI and RDI indicate the source and destination for string operations. The most c ritical registers are RSP and RIP, whi ch cause guest failure with a high probability. It is observed that moving RSP even a small amount, by altering bit 4 versus bit 16, is enough to cause a crash is most cases. On the other hand, moving the RIP by only 16 bytes,

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135 which represents only a few instructions is less likely to cause a failure than moving it by 64KB. It does make sense that skipping or repeating a few instructions is less critical to system stability than jumping much further Finally, RB P and the string pointer registers are used much less often in the benchmark considered, and correspondingly, cause the guest to fail at a much lower rate. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % Trials Register[bit] Crash No Crash Lockstep Fail Hang Figure 6 7. Fault injection failure distribution for the RFLAG register. Finally, Figure 6 7 displ ays the results for fault injection into the RFLAGS register. This is a single register that contains a large number of status, control and systems flags. There are bits used to indicate the interruptibility of the guest, the nesting level of tasks, the st atus of arithmetic operations, the direction of string operations, and a number of other system properties. The rate of the faults being detected in the guest is an average of approximately 39 %. Bit 17 (VM), which determines if the processor is in virtual8086 mode does cause the host to crash occasionally and

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136 the guest to crash every time. The least sensitive bits are bit 4 which is the adjust flag commonly used in binary coded decimal (BCD) arithmetic, and bit 16, which controls the resume behavior after a debug exception These bits are not expected to be used by the benchmark and apparently dont propagate the faulty value to other fields. Table 6 5. RFLAGS register bit descriptions Bit Description 0 CF Indicates carry from arithmetic operation or o verflow from unsigned operations 2 PF Indicates results of arithmetic operation has an even number of 1 bits 4 AF Indicates carry/borrow from 3 rd 6 bit of result and is used mostly for BCD arithmetic ZF Indicates results of arithmetic operation is zero 7 SF Indicates if most significant bit of result is set or clear 8 TF Enables single step mode in the processor when set 9 IF Indicates if processor will respond to maskable external interrupts 10 DF Controls the direction of string opera tions 11 OF Indicates the results of arithmetic operation is too large/small to fit in operand 12 IOPL (low) Low bit defining I/O privilege level of current task 13 IOPL (high) High bit defining I/O privilege level of current task 14 NT Used to nest interruption and calls to tasks 16 RF Controls restarting of instructions following a debug exception 17 VM Enable virtual 8086 mode when set 18 AC Used to check alignment of data and generate an exception if it is not aligned 19 VIF Cont rols the interruptibility of the virtual guest 20 VIP Indicates a virtual interrupt is pending for a guest

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137 21 ID Indicates support for the CPUID instruction Virtual Processor State Fingerprinting Results The data presented in Figure 68 are the ave rage time to fault detection. The purpose of this analysis is to estimate the approximate length of time it takes the system to detect the introduction of a fault The basis for this test is to determine the delay from the point at which a fault y bit value is injected into the backup of a duplex system until it is either detected by processor state fingerprinting or causes a system crash or general failur e of virtual lockstep. 1 10 100 1000 10000 100000 Average Std Dev Figure 6 8. Average time to fault detection measured in deterministic VM exits. The time is measured in deterministic VM exits, which is a count of the number of exits that occur at deterministic points in the execution. This is not an absolute measurement of time, but it does give an indication of the relative difference in time to detection. The first thing to note

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138 is the high standard deviation. This comes from the detection time being generally very short and occasionally very long. Most faults are detected with one or two VM exits because they lead to behavior that breaks virtual lockstep or appear as differences in the VMCS fields, but if the fault is masked in such a way that it doesnt show up in a VMCS register, the time to detection can be hundreds of thousands of VM exits. Not surprisingly, the registers such as the GPRs, which are not included in the VMCS, are the ones that generally have the greatest time to detection. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % Better or Worse with Fingerprinting Register Total Better Total Worse Figure 6 9. Percent of trials in which fingerprinting based fault detection detected the fault either before (better) or after (worse) than it was detected via I/O comparisons or system crash. The detection was concurrent for the remainder of the trials. T he data in Figure 6 9 summarize the benefit provided by using virtual processor state fingerprinting as a means of reducing detection latency. The performa nce is considered better if the fingerprint comparison detects the fault at the same VM exit or sooner than it otherwise

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139 would have been and worse if it does not detect it before the virtual lockstep fails or the system crashes. For the remainder of the tr ials, the fingerprint comparison detected the injection of the fault at the same time as the system I/O comparisons done by the virtual lockstep code By conducting the state comparison on every deterministic VM exit, over half of the different fault types are detected sooner than they otherwise would be. It is most beneficial in cases, such as faults in the instruction and stack pointers, where the fault is catastrophic but allows the system to execute for some time before failure. As indicated previously, reducing the length of time for which the system is running with faulty state improves the likelihood of successful recovery to a previous checkpoint. The final figures presented in this chapter are use d to present the case for possible optimization of th e virtual processor state fingerprinting technique. The idea is to look at which fields of the VMCS are the first to indicate a discrepancy after a fault is injected. All fields of the VMCS are considered regardless of whether they directly represent regi ster values, control fields, or various status indicators. For example, the VM exit qualification ( EXIT_QUAL ) field is unique to the VMCS and virtualization. It includes additional information for certain VM exit reasons. For a control register access exit it includes the instruction operands and type, as well as the direction of the access. Obviously, this field is useful for indicating a divergence since, even if the divergence results in the same type of exit being taken, this field will still likely di ffer. The goal of the analysis is to find a smaller subset of the VMCS fields that need to be included in the fingerprint hash while maintaining essentially equivalent fault detection capabilities. If a particular VMCS field never emerges as an indication of divergence between

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140 replicas, there is no benefit in including it in the fingerprint. This simple optimization reduces the fingerprinting overhead both in terms of overall performance o verhead and additional power requirements. The data presented in Figure 6 10 s ummarize these results at a high level by averaging the first fields to fail across groups of registers and then summarizing for all registers The values in the graph indicate the percentage of guest failures in which a given VMCS field indicated a divergence. This includes only the VMCS fields that are first to fail. In other words, after the fa ult is injected the fields are from the next VM exit to show one or more inconsistencies All inconsistent fields on that first exit are counted. The sys tem may continue to execute, however, with additional VMCS fields becoming corrupted on subsequent VM exits. These are not included in the results presented, but offer a means of improving the probability that the fault is detected if the faulty fields dur ing an earlier exit were not included in the hash. Additionally, the guest may simply fail before a VM exit even occurs. This type of failure is included in the data summary by contributing to the total number of trials but no VMCS fields are attributed t o the fault detection since they didnt have the opportunity to do so. In summary, the values in Figure 610 indicate the failures for which the given VMCS fields were the first to detect the introduction of the fault. Overall, only 22 different fields out of a total of 117 unique fields (19%) in the VMCS provided a nonnegligible level of fault detection. Many of these uniquely detected over 25% of the faults before they otherwise would have been detected and some were much higher than that The most usef ul in detecting faults is the exit qualification field that mentioned previously, as well as the RFLAGS, RIP, and RSP register fields and the exception error code, VM exit instruction length, and exit reason fields.

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141 The single best field, averaged across all fault types is the RIP, which was the first to detect roughly one third of all fault injections. 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% Control Regs Segment Regs Task Regs GP Regs System Regs RFLAGS ALL Regs % of Failures that VMCS Field Differed CR0 CR0_SHADOW EXCEP_BITMAP EXIT_QUAL FS_SELECTOR GS_SELECTOR INTR_INFO RFLAGS RIP RSP EXCEP_ERR_CODE ENTRY_INTR_INFO EXIT_INST_LEN EXIT_REASON LDTR_BASE IDTR_BASE SS_BASE FS_BASE ES_BASE GS_BASE GDTR_BASE TR_BASE Figure 6 10. Fingerprinting optimization showing first fields to indicate failure on average for all registers. Of course, the more specialized VMCS field s like the segment base fields were useful for detecting faults injected into those specific registers. The reason these specialized registers are surprisingly low in coverage as shown in the graph is due to the faults in the registers causing guest crashe s before a VM exit even occurs. The only time the VMCS fields are beneficial, and necessary, is when the system is not fail stop and continues to run with faulty entries. In this case, the VMCS fields will detect the discrepancy. The general purpose regist ers have very low coverage since they are not included in the VMCS in any form. The only way for the fingerprint to detect the fault in this registers is if it

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142 propagates to a register that is included or if it disrupts the system such that a control or st atus field of the VMCS is affected. Based on the summary, the most useful fields are the exit qualification, for the reasons described previously, as well as the RFLAGS, RIP, and RSP registers. The exit reason and exit instruction length fields are also us eful, all because they are easily disrupted by changes in execution. The total size of the 22 fields is only 140 bytes on a 64bit platform, of which 64 bytes represents the segment base registers. The size would increase if other parts of the segment regi sters were subject to fault injection. The bottom line, however, is that the total size of the general purpose fields that detect errors in the majority of cases is only 76 bytes, which represents a very small amount of data to generate a hash based on. If additional coverage is added for all segment registers, the amount of data would grow by a significant amount, but it was shown that faults in these registers often result in failstop behavior and so would not benefit from the VMCS hash anyway. The data presented in Figures 611 through 614 break down the VMCS field fingerprinting at the level of individual bits for several registers. A dditional registers are presented in the appendix. The purpose of this analysis is to associate particular bits to the f ault detection behavior The register considered in Figure 611 is the control register CR0, which controls the operating mode and the state of the processor. The description of the individual bits considered for this and other control registers we re summa rized previously in Table s 6 3 through 65. In all cases, the goal is to inject faults into all bits of the registers that define specific behavior, as well as to inject into both high and low bits of ranges used for addresses and values.

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143 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% CR0[0] CR0[1] CR0[2] CR0[3] CR0[16] CR0[31] % of Failures that VMCS Field Differed CR0 CR0_SHADOW EXCEP_BITMAP EXIT_QUAL FS_SELECTOR GS_SELECTOR INTR_INFO RFLAGS RIP RSP EXCEP_ERR_CODE EXIT_INST_LEN EXIT_REASON Figure 6 11. Fi ngerprinting optimization showing first fields to indicate failure for CR0 register. The first item that stands out in looking at the CR0 register bits in Figure 6 11 is that bit 1, the monitor coprocessor bit, is only ever detected by the CR0 VMCS field. This means that it does not cause the fault to propagate to other registers or fields. The paging and protection control bits (bit 0 and bit 31), however, lead to divergent data in a number of other VMCS fields with a very high probability. In fact, they a re rarely detected by the CR0 VMCS field and more often lead to exits in which the exit qualification or RIP have diverged. The remaining bits, controlling the write protection, task switch and emulation behavior, are generally limited to detection by the CR0 VMCS field and occasionally cause disruption in the other fields. The next figure, Figure 6 12, breaks down the fault detection behavior for the segment registers. It is immediately apparent that there is little difference between the high and low bits of

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144 the register s, except for one important point. The rate of detection is much lower for the high bit in the ES, FS, and GS registers. It is likely due to the system crashing more rapidly in these cases, so a VM exit doesnt occur. As stated above, when this occurs the trial is counted but no VMCS fields are attributed to detecting the error since they were not necessary. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% CS[4] CS[16] DS[4] DS[16] ES[4] ES[16] SS[4] SS[16] FS[4] FS[16] GS[4] GS[16] % of Failures that VMCS Field Differed CR0 CR0_SHADOW CS_BASE EXCEP_BITMAP EXIT_QUAL FS_SELECTOR GS_SELECTOR INTR_INFO RFLAGS RIP RSP EXCEP_ERR_CODE ENTRY_INTR_INFO EXIT_INST_LEN EXIT_REASON SS_BASE FS_BASE ES_BASE DS_BASE GS_BASE Figure 6 12. Fingerprinting optimization showing first fields to indicate failure for the segment registers. T here are some significa nt differences between the different segment registers. The less used registers, which consist of ES, FG, and GS, are again less likely to cause a disruption to propagate to additional fields. Instead, the most likely source of detection in these cases com es from monitoring the VMCS field that contains the actual register at fault. The remaining segment registers, CS, DS, and SS, are all used very often and lead to significant corruption of the VMCS with the most commonly affected fields being the same as those seen i n the control registers.

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145 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% RAX[4] RAX[16] RBX[4] RBX[16] RCX[4] RCX[16] RDX[4] RDX[16] % of Failures that VMCS Field Differed EXIT_QUAL RFLAGS RIP RSP EXCEP_ERR_CODE ENTRY_INTR_INFO EXIT_INST_LEN EXIT_REASON Figure 6 13. Fingerprinting optimization showing first fields to indicate failure for the general purpose registers. Figure 6 13 presents the same data for the general purpose registers. As indicated previously, these registers demonstrate a much lower rate of detection since they are not presently part of the VMCS. Yet agai n, a handful of system register fields consisting of RIP, RSP, and RFLAGS, as well as the exit qualification field offer the highest rates of fault detection. These results do lend some support to possibly of including the general purpose registers into the fingerprint hash directly. This could be done by simply extending the VMCS to include these fields and not requiring the hypervisor to save and re store these values. Additionally, a custom hardware mechanism designed for hashing these values in addition to those in the VMCS could be developed.

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146 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% RBP[4] RBP[16] RSP[4] RSP[16] RIP[4] RIP[16] RSI[4] RSI[16] RDI[4] RDI[16] % of Failures that VMCS Field Differed CR0 CR0_SHADOW EXCEP_BITMAP EXIT_QUAL FS_SELECTOR GS_SELECTOR INTR_INFO RFLAGS RIP RSP EXCEP_ERR_CODE ENTRY_INTR_INFO EXIT_INST_LEN EXIT_REASON Figure 6 14. Fingerprinting optimization showing first fields to indicate failure for the system register s. The final fault detection data presented in this chapter is in Figure 614 and consists of the results for the system registers. Clearly, the RSP and RIP VMCS fields are well suited at not only detecting faults injected into other registers but into the RSP and RIP registers themselves. The remaining registers are detected at a much lower rate. This is attributable to a combination of the registers being used less often by software, the system crashing before a VM exit occurs, or the divergence causing a failure of the virtual lockstep mechanism before the fault could be detected by the fingerprint comparisons. As was shown in Figure 69, the string registers had some of the highest rates of inherent virtual lockstep failure prior to the fingerprint based detection.

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147 In conclusion, the goal of this chapter was to explore the benefits of using virtual lockstep to conduct fault injection experiments in real hardware, as well as to assess the benefits of using VMCS hashing as a means of early fault detection. The data indicate a clear benefit to the fingerprint based detection in terms of reducing the time to detection. It is also apparent that hashing the entire VMCS structure is of little benefit. The detection capabilities are essentially equivalent when considering less than 20% of the total fields. In fact, it is shown that by considering only a single field, the instruction pointer, roughly one third of the total errors across all registers a re detected by the processor state fingerprint Note that additional data for the registers not included in this chapter are included in the appendix.

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148 CHAPTER 7 SUMMARY AND FUTURE W ORK Summary The main goals of this dissertation are to present a generic model for the application of virtual lockstep execution to commodity computing platforms, implement a proof of concept based on a full featured hypervisor and real hardware, and to demonstrate its use as a fault injection test vehicle for assessing the architectural vulnerability factor of the processor. The motivations for this work are to develop a mechanism for dealing with increasing rates of faults in processors, as well as for use in achieving arbitrarily high levels of fault tolerance for critical applications. The practicality and cost of the design are considere d to be important factors and an effort is made to ensure the approach is feasible in the real world. The proposed virtual lockstep technique can be applied without the need for changes to the existing hardware, operating system, or application software. A dditionally, it allows for relatively easy porting across all major processor architectures since the hypervisor code is already supported. There is a specific focus on applying the technique to many core processors, especially within a single physical pla tform. This reduces the implementation cost and expands the applicability. It also allows for flexibility in the trade off of performance for reliability by supporting the assignment of processor cores to either normal or replicated execution based on the requirements at the time. Also, given that Moores Law will continue to provide more cores in the processor and extracting very high degrees of parallelism from software is very difficult, it is expected that idle compute resources will be readily availabl e to achieve highly reliable replicated execution with minimal degradation in performance. It also offers the opportunity for the integration of

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149 specialized processing units for tasks such as virtual processor state fingerprinting that are optimized in ter ms of functional capabilities as well as power usage. Logical partitioning is presented as a means of allowing for complete replication within a single physical platform while integrating the hypervisor into the sphere of replication and avoiding the introduction of a significant single point of failure. The historical challenges of such partitioning are discussed, and methods of avoiding them through modification of the hypervisor are presented. The key benefit of logical partitioning is that it allows for the kernel of the hypervisor to be replicated within a single physical system, which protects the system from faults that may cause the corruption of state outside the region reserved for a guest virtual machine. For example, if a bit flip that causes the paging mode of the processor to change may cause corruption of the hypervisor hosting the guest, or even one of the replicated guests in the system. By strengthening the boundaries between guests and fully replicating the hypervisor, a crash can be contai ned to a single replica. Virtual lockstepped operation is achieved by using a hypervisor layer to simplify the hardware/software interface, eliminate nondeterministic behavior, and coordinate the replicated execution stream. This approach is simpler and le ss expensive than other replication techniques such as replicating at the process level in the operating system It is also more flexible than expensive, specialized systems which support cycle level lockstep at the hardware level. The general virtual loc kstep requirements of the platform and of the hypervisor are explained, and are then made concrete with the detailed design overview of a prototype hypervisor with virtual lockstep support. The prototype hypervisor is used both to assess the performance ov erhead of virtual lockstep on real hardware and to validate the use of virtual processor state fingerprinting to

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150 reduce fault detection times. The viable performance of multiple, concurrent backup replicas is demonstrated and the sensitivity of factors suc h as workload type and communication buffer size are explored. Additionally, the prototype serve s as a means of determining the processor vulnerability to single event upsets through fault injection into t he backup replica of a virtuall lockstepped system Future Work T here are a number of extensions to be m ade to the base model presented in addition to relaxing the limitations described in Chapter 4. O ne of the most important being support for multiprocessor guests. To date, such support appears unlikely to be possible with acceptable performance overhead, but possible hardware extensions or new mechanisms of dealing with race recording may make it a reality. Other examples of possible extensions are support for additional hypervisors and architectures t esting capabilities to differentiate soft errors from hard or intermittent faults, and communication buffer enhancements targeted to replicas distributed across a LAN or WAN There is also significant work to be done in prototyping and optimizing additiona l replication models and incorporating fast checkpointing and restore. Full support for Byzantine fault tolerance requires the integration of an appropriate inter replica communication and coordination protocols as well as optimizations to reduce the amou nt of data transferred among the replicas to make it practical Most live migration algorithms are also limited to transferring the virtual processor and memory state and required shared storage. Support for fast migration, snapshotting, and mirroring of t he guest storage is a key lacking technology, which limits the performance of the dynamic guest replication and subsequent reintegration after a failure. The creation of a new virtualization aware file system or an extension of an existing file system that already supports these capabilities are possible avenues of research in this area.

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151 V irtual lockstep based fault injection may also be extended rather trivially to model a much larger range of fault types and targets. Repeatable execution is a powerful too l for gaining insight into incorrect actions taken by a guest since there is a standard to compare the execution against. Such a technique could be used to derive detailed fault sensitivity behavior of the processor registers and caches, as well as to test faults injected directly into memory. The early fault detection mechanism based in fingerprinting virtual processor state could be optimized using one or more of the techniques suggested earlier. Examples of this include implementing specialized hardware based hashing circuitry or scheduling idle cores to do the work. Additionally, the components of the fingerprint could be extended, further optimized or even made dynamic based on additional fault injection trials.

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152 APPENDIX FINGERPRINTING BASED FAULT D ETECTION RESULTS The f igu res in this appendix present the remainder of the fault injection results that were not included in Chapter 6 These graphs represent the first VMCS fields to indicate failure after the injection of a fault into a register in the s ystem. The goal of this analysis is to determine the key fields that should be incorporated into the virtual processor state hash fingerprint. The CR3 control register is shown if Figure A 1and exhibits many of the same fields that the other control regist ers did. The reason bits 3 and 4 have such a low detection rate is due to their very low failure rate. The other bits, which are part of the address defining the root of the memory hierarchy do fail quite often and are also detected quite reliably due to differences in the VM exit reason and exit qualification fields, as well as the RIP, RSP, and RFLAGS fields. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% CR3[3] CR3[4] CR3[16] CR3[24] % of Failures that VMCS Field Differed CR0 CR0_SHADOW EXCEP_BITMAP EXIT_QUAL FS_SELECTOR GS_SELECTOR INTR_INFO RFLAGS RIP RSP EXCEP_ERR_CODE EXIT_INST_LEN EXIT_REASON Figure A 1. Fingerprinting optimization showing first fields to indicate failure for CR3 register.

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153 The results for the CR4 control register are summarized in Figure A 2. Bit 5, the control for PAE paging mode, shows a very similar signature to CR3 and the other control registers, but the remaining bits are rarely detected by the fingerprint comparisons. This is not because of limitations of the fing erprints, however, but because the guest reliably fa ils after faults are injected into these bits before a single VM exit even occurs In other words, the system does demonstrate the highly desirable fail stop behavio r when these bits are corrupted. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% CR4[0] CR4[1] CR4[4] CR4[5] CR4[7] % of Failures that VMCS Field Differed CR0 CR0_SHADOW EXCEP_BITMAP EXIT_QUAL FS_SELECTOR GS_SELECTOR INTR_INFO RFLAGS RIP RSP EXCEP_ERR_CODE EXIT_INST_LEN EXIT_REASON Figu re A 2. Fingerprinting optimization showing first fields to indicate failure for CR4 register. Figure A 3 shows similar data for the system descriptor tables and the task register. In all cases, the VMCS field specific to the fault targ et is best at detect ing failure. With the except of the local descriptor table, the same fields that have generally proven most useful in detecting faults are also seen here. Again, it appears to be the case that the faults in the LDTR register

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154 cause the system to fail prior to a single VM exit. The ones that dont cause this early failure, also dont cause fault propagation to other registers and so are not detected by the corresponding VMCS fields. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% GDTR[4] GDTR[16] IDTR[4] IDTR[16] LDTR[4] LDTR[16] TR[4] TR[16] % of Failures that VMCS Field Differed CR0 CR0_SHADOW EXCEP_BITMAP EXIT_QUAL FS_SELECTOR GS_SELECTOR INTR_INFO RFLAGS RIP RSP EXCEP_ERR_CODE EXIT_INST_LEN EXIT_REASON LDTR_BASE IDTR_BASE GDTR_BASE TR_BASE Figure A 3. Fingerprinting optimization showing first fields to indicate fa ilure for descriptor tables and task register The final fingerprint based fault detection data given are for the bits of the RFLAGS register. In this case, there is quite a variation across bits, which is not unexpected given that the bits have quite unique roles. In all cases, the most useful field in the fingerprint is the RFLAGS register, itself. In fact, in most cases, it is the only field to indicate the presence of the fault. The three bit positions that stand out are 10, 14, and 17, which control the direction of string operations, the nesting level of tasks, and the enabling of virtual 8086 mode. These are all operations that are expected to be highly disruptive to execution and as such appear to propagate

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155 errors to other registers. The reason for f aults in many of the other bits, such as the carry flag or parity flag, bits 0 and 2, respectively, to be rarely detected is not due to their tendency to crash the system but instead because they are often overwritten by arithmetic operations that do no cause VM exits. This is a limitation of the currently fingerprinting model since the resulting arithmetic operations may result in SDC. One extension that is expected to reduce the probability of such SDC is the inclusion of the general purpose registers in the VMCS, and consequently, in the generation of the fingerprint. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % of Failures that VMCS Field Differed CR0 CR0_SHADOW EXCEP_BITMAP EXIT_QUAL FS_SELECTOR GS_SELECTOR INTR_INFO RFLAGS RIP RSP EXCEP_ERR_CODE EXIT_INST_LEN EXIT_REASON Figure A 4. Fingerprinting optimization showing first fields to indicate failure for RFLAGS register.

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166 BIOGRAPHICAL SKETCH Casey Jeffery was born and raised in the Black Hills region of South Dakota He completed his B.S degree in c omputer e ngineering at the South Dakota School of Mines and Technology in Rapid City During his sophomore year, he took a semester off to intern at Intel Corporation. This internship was very successful and prompted him to continue interning at various Intel groups and plant si tes throughout the U.S. every year since. After graduation in 2002, he moved to Gainesville to attend the University of Florida and began work on a M.S. degree in c omputer e ngineering in the Department of Electrical and Computer Engineering. After a year o f general studies, he joined the ACIS lab and worked with Prof. Renato Figueiredo on research geared towards improving fault tolerance in nanoscale memory devices. He then continued to work in the ACIS l ab for the Ph.D. program starting in 2005, but switched his focus from nanoscale memory technology to virtualization technology The following year h e was fortunate enough to land an internship with the creators of Intel Virtualization Technology, the Core Virtualization Research (CVR) group in Hillsboro, O R. He completed two internships with the group before joining as a full time research scientist in early 2008.