Specognitor: Identifying Spectre Vulnerabilities via Prediction-Aware Symbolic Execution

Spectre attacks exploit speculative execution to leak sensitive information. In the last few years, a number of static side-channel detectors have been proposed to detect cache leakage in the presence of speculative execution. However, these techniques either ignore branch prediction mechanism, detect static pre-defined patterns which is not suitable for detecting new patterns, or lead to false negatives. In this paper, we illustrate the weakness of prediction-agnostic state-of-the-art approaches. We propose Specognitor, a novel prediction-aware symbolic execution engine to soundly explore program paths and detect subtle spectre variant 1 and variant 2 vulnerabilities. We propose a dynamic pattern detection mechanism to account for both existing and future vulnerabilities. Our experimental results show the effectiveness and efficiency of Specognitor in analyzing real-world cryptographic programs w.r.t. different processor families

A low-power cache system for high-performance processors

制度:新 ; 報告番号:甲3439号 ; 学位の種類:博士(工学) ; 授与年月日:12-Sep-11 ; 早大学位記番号:新576

Learning Independent Program and Architecture Representations for Generalizable Performance Modeling

This paper proposes PerfVec, a novel deep learning-based performance modeling framework that learns high-dimensional, independent/orthogonal program and microarchitecture representations. Once learned, a program representation can be used to predict its performance on any microarchitecture, and likewise, a microarchitecture representation can be applied in the performance prediction of any program. Additionally, PerfVec yields a foundation model that captures the performance essence of instructions, which can be directly used by developers in numerous performance modeling related tasks without incurring its training cost. The evaluation demonstrates that PerfVec is more general, efficient, and accurate than previous approaches

Multicore architecture optimizations for HPC applications

From single-core CPUs to detachable compute accelerators, supercomputers made a tremendous progress by using available transistors on chip and specializing hardware for a given type of computation. Today, compute nodes used in HPC employ multi-core CPUs tailored for serial execution and multiple accelerators (many-core devices or GPUs) for throughput computing. However, designing next-generation HPC system requires not only the performance improvement but also better energy efficiency. Current trend of reaching exascale level of computation asks for at least an order of magnitude increase in both of these metrics. This thesis explores HPC-specific optimizations in order to make better utilization of the available transistors and to improve performance by transparently executing parallel code across multiple GPU accelerators. First, we analyze several HPC benchmark suites, compare them against typical desktop applications, and identify the differences which advocate for proper core tailoring. Moreover, within the HPC applications, we evaluate serial and parallel code sections separately, resulting in an Asymmetric Chip Multiprocessor (ACMP) design with one core optimized for single-thread performance and many lean cores for parallel execution. Our results presented here suggests downsizing of core front-end structures providing an HPC-tailored lean core which saves 16% of the core area and 7% of power, without performance loss. Further improving an ACMP design, we identify that multiple lean cores run the same code during parallel regions. This motivated us to evaluate the idea where lean cores share the I-cache with the intent of benefiting from mutual prefetching, without increasing the average access latency. Our exploration of the multiple parameters finds the sweet spot on a wide interconnect to access the shared I-cache and the inclusion of a few line buffers to provide the required bandwidth and latency to sustain performance. The projections presented in this thesis show additional 11% area savings with a 5% energy reduction at no performance cost. These area and power savings might be attractive for many-core accelerators either for increasing the performance per area and power unit, or adding additional cores and thus improving the performance for the same hardware budget. Finally, in this thesis we study the effects of future NUMA accelerators comprised of multiple GPU devices. Reaching the limits of a single-GPU die size, next-generation GPU compute accelerators will likely embrace multi-socket designs increasing the core count and memory bandwidth. However, maintaining the UMA behavior of a single-GPU in multi-GPU systems without code rewriting stands as a challenge. We investigate multi-socket NUMA GPU designs and show that significant changes are needed to both the GPU interconnect and cache architectures to achieve performance scalability. We show that application phase effects can be exploited allowing GPU sockets to dynamically optimize their individual interconnect and cache policies, minimizing the impact of NUMA effects. Our NUMA-aware GPU outperforms a single GPU by 1.5×, 2.3×, and 3.2× while achieving 89%, 84%, and 76% of theoretical application scalability in 2, 4, and 8 sockets designs respectively. Implementable today, NUMA-aware multi-socket GPUs may be a promising candidate for performance scaling of future compute nodes used in HPC.Empezando por CPUs de un solo procesador, y pasando por aceleradores discretos, los supercomputadores han avanzado enormemente utilizando todos los transistores disponibles en el chip, y especializando los diseños para cada tipo de cálculo. Actualmente, los nodos de cálculo de un sistema de Computación de Altas Prestaciones (CAP) utilizan CPUs de múltiples procesadores, optimizados para el cálculo serial de instrucciones, y múltiples aceleradores (aceleradores gráficos, o many-core), optimizados para el cálculo paralelo. El diseño de un sistema CAP de nueva generación requiere no solo mejorar el rendimiento de cálculo, sino también mejorar la eficiencia energética. La siguiente generación de sistemas requiere mejorar un orden de magnitud en ambas métricas simultáneamente. Esta tesis doctoral explora optimizaciones específicas para sistemas CAP para hacer un mejor uso de los transistores, y para mejorar las prestaciones de forma transparente ejecutando las aplicaciones en múltiples aceleradores en paralelo. Primero, analizamos varios conjuntos de aplicaciones CAP, y las comparamos con aplicaciones para servidores y escritorio, identificando las principales diferencias que nos indican cómo ajustar la arquitectura para CAP. En las aplicaciones CAP, también analizamos la parte secuencial del código y la parte paralela de forma separada, . El resultado de este análisis nos lleva a proponer una arquitectura multiprocesador asimétrica (ACMP) , con un procesador optimizado para el código secuencial, y múltiples procesadores, más pequeños, optimizados para el procesamiento paralelo. Nuestros resultados muestran que reducir el tamaño de las estructuras del front-end (fetch, y predicción de saltos) en los procesadores paralelos nos proporciona un 16% extra de área en el chip, y una reducción de consumo del 7%. Como mejora a nuestra arquitectura ACMP, proponemos explotar el hecho de que todos los procesadores paralelos ejecutan el mismo código al mismo tiempo. Evaluamos una propuesta en que los procesadores paralelos comparten la caché de instrucciones, con la intención de que uno de ellos precargue las instrucciones para los demás procesadores (prefetching), sin aumentar la latencia media de acceso. Nuestra exploración de los distintos parámetros determina que el punto óptimo requiere una interconexión de alto ancho de banda para acceder a la caché compartida, y el uso de unos pocos line buffers para mantener el ancho de banda y la latencia necesarios. Nuestras proyecciones muestran un ahorro adicional del 11% en área y el 5% en energía, sin impacto en el rendimiento. Estos ahorros de área y energía permiten a un multiprocesador incrementar la eficiencia energética, o aumentar el rendimiento añadiendo procesador adicionales. Por último, estudiamos el efecto de usar múltiples aceleradores (GPU) en una arquitectura con tiempo de acceso a memoria no uniforme (NUMA). Una vez alcanzado el límite de número de transistores y tamaño máximo por chip, la siguiente generación de aceleradores deberá utilizar múltiples chips para aumentar el número de procesadores y el ancho de banda de acceso a memoria. Sin embargo, es muy difícil mantener la ilusión de un tiempo de acceso a memoria uniforme en un sistema multi-GPU sin reescribir el código de la aplicación. Nuestra investigación sobre sistemas multi-GPU muestra retos significativos en el diseño de la interconexión entre las GPU y la jerarquía de memorias cache. Nuestros resultados muestran que se puede explotar el comportamiento en fases de las aplicaciones para optimizar la configuración de la interconexión y las cachés de forma dinámica, minimizando el impacto de la arquitectura NUMA. Nuestro diseño mejora el rendimiento de un sistema con una única GPU en 1.5x, 2.3x y 3.2x (el 89%, 84%, y 76% del máximo teórico) usando 2, 4, y 8 GPUs en paralelo. Siendo su implementación posible hoy en dia, los nodos de cálculo con múltiples aceleradores son una alternativa atractiva para futuros sistemas CAP.Postprint (published version

Multicore architecture optimizations for HPC applications

From single-core CPUs to detachable compute accelerators, supercomputers made a tremendous progress by using available transistors on chip and specializing hardware for a given type of computation. Today, compute nodes used in HPC employ multi-core CPUs tailored for serial execution and multiple accelerators (many-core devices or GPUs) for throughput computing. However, designing next-generation HPC system requires not only the performance improvement but also better energy efficiency. Current trend of reaching exascale level of computation asks for at least an order of magnitude increase in both of these metrics. This thesis explores HPC-specific optimizations in order to make better utilization of the available transistors and to improve performance by transparently executing parallel code across multiple GPU accelerators. First, we analyze several HPC benchmark suites, compare them against typical desktop applications, and identify the differences which advocate for proper core tailoring. Moreover, within the HPC applications, we evaluate serial and parallel code sections separately, resulting in an Asymmetric Chip Multiprocessor (ACMP) design with one core optimized for single-thread performance and many lean cores for parallel execution. Our results presented here suggests downsizing of core front-end structures providing an HPC-tailored lean core which saves 16% of the core area and 7% of power, without performance loss. Further improving an ACMP design, we identify that multiple lean cores run the same code during parallel regions. This motivated us to evaluate the idea where lean cores share the I-cache with the intent of benefiting from mutual prefetching, without increasing the average access latency. Our exploration of the multiple parameters finds the sweet spot on a wide interconnect to access the shared I-cache and the inclusion of a few line buffers to provide the required bandwidth and latency to sustain performance. The projections presented in this thesis show additional 11% area savings with a 5% energy reduction at no performance cost. These area and power savings might be attractive for many-core accelerators either for increasing the performance per area and power unit, or adding additional cores and thus improving the performance for the same hardware budget. Finally, in this thesis we study the effects of future NUMA accelerators comprised of multiple GPU devices. Reaching the limits of a single-GPU die size, next-generation GPU compute accelerators will likely embrace multi-socket designs increasing the core count and memory bandwidth. However, maintaining the UMA behavior of a single-GPU in multi-GPU systems without code rewriting stands as a challenge. We investigate multi-socket NUMA GPU designs and show that significant changes are needed to both the GPU interconnect and cache architectures to achieve performance scalability. We show that application phase effects can be exploited allowing GPU sockets to dynamically optimize their individual interconnect and cache policies, minimizing the impact of NUMA effects. Our NUMA-aware GPU outperforms a single GPU by 1.5×, 2.3×, and 3.2× while achieving 89%, 84%, and 76% of theoretical application scalability in 2, 4, and 8 sockets designs respectively. Implementable today, NUMA-aware multi-socket GPUs may be a promising candidate for performance scaling of future compute nodes used in HPC.Empezando por CPUs de un solo procesador, y pasando por aceleradores discretos, los supercomputadores han avanzado enormemente utilizando todos los transistores disponibles en el chip, y especializando los diseños para cada tipo de cálculo. Actualmente, los nodos de cálculo de un sistema de Computación de Altas Prestaciones (CAP) utilizan CPUs de múltiples procesadores, optimizados para el cálculo serial de instrucciones, y múltiples aceleradores (aceleradores gráficos, o many-core), optimizados para el cálculo paralelo. El diseño de un sistema CAP de nueva generación requiere no solo mejorar el rendimiento de cálculo, sino también mejorar la eficiencia energética. La siguiente generación de sistemas requiere mejorar un orden de magnitud en ambas métricas simultáneamente. Esta tesis doctoral explora optimizaciones específicas para sistemas CAP para hacer un mejor uso de los transistores, y para mejorar las prestaciones de forma transparente ejecutando las aplicaciones en múltiples aceleradores en paralelo. Primero, analizamos varios conjuntos de aplicaciones CAP, y las comparamos con aplicaciones para servidores y escritorio, identificando las principales diferencias que nos indican cómo ajustar la arquitectura para CAP. En las aplicaciones CAP, también analizamos la parte secuencial del código y la parte paralela de forma separada, . El resultado de este análisis nos lleva a proponer una arquitectura multiprocesador asimétrica (ACMP) , con un procesador optimizado para el código secuencial, y múltiples procesadores, más pequeños, optimizados para el procesamiento paralelo. Nuestros resultados muestran que reducir el tamaño de las estructuras del front-end (fetch, y predicción de saltos) en los procesadores paralelos nos proporciona un 16% extra de área en el chip, y una reducción de consumo del 7%. Como mejora a nuestra arquitectura ACMP, proponemos explotar el hecho de que todos los procesadores paralelos ejecutan el mismo código al mismo tiempo. Evaluamos una propuesta en que los procesadores paralelos comparten la caché de instrucciones, con la intención de que uno de ellos precargue las instrucciones para los demás procesadores (prefetching), sin aumentar la latencia media de acceso. Nuestra exploración de los distintos parámetros determina que el punto óptimo requiere una interconexión de alto ancho de banda para acceder a la caché compartida, y el uso de unos pocos line buffers para mantener el ancho de banda y la latencia necesarios. Nuestras proyecciones muestran un ahorro adicional del 11% en área y el 5% en energía, sin impacto en el rendimiento. Estos ahorros de área y energía permiten a un multiprocesador incrementar la eficiencia energética, o aumentar el rendimiento añadiendo procesador adicionales. Por último, estudiamos el efecto de usar múltiples aceleradores (GPU) en una arquitectura con tiempo de acceso a memoria no uniforme (NUMA). Una vez alcanzado el límite de número de transistores y tamaño máximo por chip, la siguiente generación de aceleradores deberá utilizar múltiples chips para aumentar el número de procesadores y el ancho de banda de acceso a memoria. Sin embargo, es muy difícil mantener la ilusión de un tiempo de acceso a memoria uniforme en un sistema multi-GPU sin reescribir el código de la aplicación. Nuestra investigación sobre sistemas multi-GPU muestra retos significativos en el diseño de la interconexión entre las GPU y la jerarquía de memorias cache. Nuestros resultados muestran que se puede explotar el comportamiento en fases de las aplicaciones para optimizar la configuración de la interconexión y las cachés de forma dinámica, minimizando el impacto de la arquitectura NUMA. Nuestro diseño mejora el rendimiento de un sistema con una única GPU en 1.5x, 2.3x y 3.2x (el 89%, 84%, y 76% del máximo teórico) usando 2, 4, y 8 GPUs en paralelo. Siendo su implementación posible hoy en dia, los nodos de cálculo con múltiples aceleradores son una alternativa atractiva para futuros sistemas CAP

Interval simulation: raising the level of abstraction in architectural simulation

Detailed architectural simulators suffer from a long development cycle and extremely long evaluation times. This longstanding problem is further exacerbated in the multi-core processor era. Existing solutions address the simulation problem by either sampling the simulated instruction stream or by mapping the simulation models on FPGAs; these approaches achieve substantial simulation speedups while simulating performance in a cycle-accurate manner This paper proposes interval simulation which rakes a completely different approach: interval simulation raises the level of abstraction and replaces the core-level cycle-accurate simulation model by a mechanistic analytical model. The analytical model estimates core-level performance by analyzing intervals, or the timing between two miss events (branch mispredictions and TLB/cache misses); the miss events are determined through simulation of the memory hierarchy, cache coherence protocol, interconnection network and branch predictor By raising the level of abstraction, interval simulation reduces both development time and evaluation time. Our experimental results using the SPEC CPU2000 and PARSEC benchmark suites and the MS multi-core simulator show good accuracy up to eight cores (average error of 4.6% and max error of 11% for the multi-threaded full-system workloads), while achieving a one order of magnitude simulation speedup compared to cycle-accurate simulation. Moreover interval simulation is easy to implement: our implementation of the mechanistic analytical model incurs only one thousand lines of code. Its high accuracy, fast simulation speed and ease-of-use make interval simulation a useful complement to the architect's toolbox for exploring system-level and high-level micro-architecture trade-offs

Real-time trace decoding and monitoring for safety and security in embedded systems

Integrated circuits and systems can be found almost everywhere in today’s world. As their use increases, they need to be made safer and more perfor mant to meet current demands in processing power. FPGA integrated SoCs can provide the ideal trade-off between performance, adaptability, and energy usage. One of today’s vital challenges lies in updating existing fault tolerance techniques for these new systems while utilizing all available processing capa bilities, such as multi-core and heterogeneous processing units. Control-flow monitoring is one of the primary mechanisms described for error detection at the software architectural level for the highest grade of hazard level clas sifications (e.g., ASIL D) described in industry safety standards ISO-26262. Control-flow errors are also known to compose the majority of detected errors for ICs and embedded systems in safety-critical and risk-susceptible environ ments [5]. Software-based monitoring methods remain the most popular [6–8]. However, recent studies show that the overheads they impose make actual reliability gains negligible [9, 10]. This work proposes and demonstrates a new control flow checking method implemented in FPGA for multi-core embedded systems called control-flow trace checker (CFTC). CFTC uses existing trace and debug subsystems of modern processors to rebuild their execution states. It can iden tify any errors in real-time by comparing executed states to a set of permitted state transitions determined statically. This novel implementation weighs hardware resource trade-offs to target mul tiple independent tasks in multi-core embedded applications, as well as single core systems. The proposed system is entirely implemented in hardware and isolated from all monitored software components, requiring 2.4% of the target FPGA platform resources to protect an execution unit in its entirety. There fore, it avoids undesired overheads and maintains deterministic error detection latencies, which guarantees reliability improvements without impairing the target software system. Finally, CFTC is evaluated under different software i Resumo fault-injection scenarios, achieving detection rates of 100% of all control-flow errors to wrong destinations and 98% of all injected faults to program binaries. All detection times are further analyzed and precisely described by a model based on the monitor’s resources and speed and the software application’s control-flow structure and binary characteristics.Circuitos integrados estão presentes em quase todos sistemas complexos do mundo moderno. Conforme sua frequência de uso aumenta, eles precisam se tornar mais seguros e performantes para conseguir atender as novas demandas em potência de processamento. Sistemas em Chip integrados com FPGAs conseguem prover o balanço perfeito entre desempenho, adaptabilidade, e uso de energia. Um dos maiores desafios agora é a necessidade de atualizar técnicas de tolerância à falhas para estes novos sistemas, aproveitando os novos avanços em capacidade de processamento. Monitoramento de fluxo de controle é um dos principais mecanismos para a detecção de erros em nível de software para sistemas classificados como de alto risco (e.g. ASIL D), descrito em padrões de segurança como o ISO-26262. Estes erros são conhecidos por compor a maioria dos erros detectados em sistemas integrados [5]. Embora métodos de monitoramento baseados em software continuem sendo os mais populares [6–8], estudos recentes mostram que seus custos adicionais, em termos de performance e área, diminuem consideravelmente seus ganhos reais em confiabilidade [9, 10]. Propomos aqui um novo método de monitora mento de fluxo de controle implementado em FPGA para sistemas embarcados multi-core. Este método usa subsistemas de trace e execução de código para reconstruir o estado atual do processador, identificando erros através de com parações entre diferentes estados de execução da CPU. Propomos uma implementação que considera trade-offs no uso de recuros de sistema para monitorar múltiplas tarefas independetes. Nossa abordagem suporta o monitoramento de sistemas simples e também de sistemas multi-core multitarefa. Por fim, nossa técnica é totalmente implementada em hardware, evitando o uso de unidades de processamento de software que possa adicionar custos indesejáveis à aplicação em perda de confiabilidade. Propomos, assim, um mecanismo de verificação de fluxo de controle, escalável e extensível, para proteção de sistemas embarcados críticos e multi-core

Real-Time Trace Decoding and Monitoring for Safety and Security in Embedded Systems

Integrated circuits and systems can be found almost everywhere in today’s world. As their use increases, they need to be made safer and more perfor mant to meet current demands in processing power. FPGA integrated SoCs can provide the ideal trade-off between performance, adaptability, and energy usage. One of today’s vital challenges lies in updating existing fault tolerance techniques for these new systems while utilizing all available processing capa bilities, such as multi-core and heterogeneous processing units. Control-flow monitoring is one of the primary mechanisms described for error detection at the software architectural level for the highest grade of hazard level clas sifications (e.g., ASIL D) described in industry safety standards ISO-26262. Control-flow errors are also known to compose the majority of detected errors for ICs and embedded systems in safety-critical and risk-susceptible environ ments [5]. Software-based monitoring methods remain the most popular [6–8]. However, recent studies show that the overheads they impose make actual reliability gains negligible [9, 10]. This work proposes and demonstrates a new control flow checking method implemented in FPGA for multi-core embedded systems called control-flow trace checker (CFTC). CFTC uses existing trace and debug subsystems of modern processors to rebuild their execution states. It can iden tify any errors in real-time by comparing executed states to a set of permitted state transitions determined statically. This novel implementation weighs hardware resource trade-offs to target mul tiple independent tasks in multi-core embedded applications, as well as single core systems. The proposed system is entirely implemented in hardware and isolated from all monitored software components, requiring 2.4% of the target FPGA platform resources to protect an execution unit in its entirety. There fore, it avoids undesired overheads and maintains deterministic error detection latencies, which guarantees reliability improvements without impairing the target software system. Finally, CFTC is evaluated under different software i Resumo fault-injection scenarios, achieving detection rates of 100% of all control-flow errors to wrong destinations and 98% of all injected faults to program binaries. All detection times are further analyzed and precisely described by a model based on the monitor’s resources and speed and the software application’s control-flow structure and binary characteristics.Circuitos integrados estão presentes em quase todos sistemas complexos do mundo moderno. Conforme sua frequência de uso aumenta, eles precisam se tornar mais seguros e performantes para conseguir atender as novas demandas em potência de processamento. Sistemas em Chip integrados com FPGAs conseguem prover o balanço perfeito entre desempenho, adaptabilidade, e uso de energia. Um dos maiores desafios agora é a necessidade de atualizar técnicas de tolerância à falhas para estes novos sistemas, aproveitando os novos avanços em capacidade de processamento. Monitoramento de fluxo de controle é um dos principais mecanismos para a detecção de erros em nível de software para sistemas classificados como de alto risco (e.g. ASIL D), descrito em padrões de segurança como o ISO-26262. Estes erros são conhecidos por compor a maioria dos erros detectados em sistemas integrados [5]. Embora métodos de monitoramento baseados em software continuem sendo os mais populares [6–8], estudos recentes mostram que seus custos adicionais, em termos de performance e área, diminuem consideravelmente seus ganhos reais em confiabilidade [9, 10]. Propomos aqui um novo método de monitora mento de fluxo de controle implementado em FPGA para sistemas embarcados multi-core. Este método usa subsistemas de trace e execução de código para reconstruir o estado atual do processador, identificando erros através de com parações entre diferentes estados de execução da CPU. Propomos uma implementação que considera trade-offs no uso de recuros de sistema para monitorar múltiplas tarefas independetes. Nossa abordagem suporta o monitoramento de sistemas simples e também de sistemas multi-core multitarefa. Por fim, nossa técnica é totalmente implementada em hardware, evitando o uso de unidades de processamento de software que possa adicionar custos indesejáveis à aplicação em perda de confiabilidade. Propomos, assim, um mecanismo de verificação de fluxo de controle, escalável e extensível, para proteção de sistemas embarcados críticos e multi-core

The Fast, Efficient, and Representative Benchmarking of Future Microarchitectures.

A methodology is introduced to reduce the overall simulation time of large benchmarking suites. Previous work shows that it is possible to simulate only small sections of a benchmark's dynamic instruction stream in detail, without sacrificing accuracy in simulation results with respect to overall behavior. As benchmarking suites increase in size, many such techniques still require a great deal of simulation time to complete. The methods presented in this dissertation build on this previous work by converting representative sections of a benchmark's execution into either augmented binaries or intrinsically checkpointed assembly code. This new code can then serve as a replacement for the original benchmark. In addition, a methodology is proposed that creates new benchmark binaries that no longer need input files or system calls in order to execute properly. Since the new benchmarks only contain portions of the original benchmarks and input data is effectively hidden within them, corporations can safely release benchmarks to the public created using their own internal, proprietary test programs without the fear of losing sensitive information. Simulations of the new benchmarks are much faster, require less overhead, and still properly represent the original benchmark's execution profile. Results show that benchmarks created using these techniques are very portable and accurately predict the performance of the original benchmark. An average error rate of less than 5% is achieved when compared to the original representative sections. In addition, a speedup of roughly 60x per benchmark is achieved when the new benchmarks are executed serially and 1000x when they are executed in parallel. This translates into a reduction in simulation time from months to minutes and greatly decreases the amount of time necessary to test a new design.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/60726/1/jringenb_1.pd