Automatic skeleton-driven performance optimizations for transactional memory

The recent shift toward multi -core chips has pushed the burden of extracting performance to the programmer. In fact, programmers now have to be able to uncover more coarse -grain parallelism with every new generation of processors, or the performance of their applications will remain roughly the same or even degrade. Unfortunately, parallel programming is still hard and error prone. This has driven the development of many new parallel programming models that aim to make this process efficient.This thesis first combines the skeleton -based and transactional memory programming models in a new framework, called OpenSkel, in order to improve performance and programmability of parallel applications. This framework provides a single skeleton that allows the implementation of transactional worklist applications. Skeleton or pattern-based programming allows parallel programs to be expressed as specialized instances of generic communication and computation patterns. This leaves the programmer with only the implementation of the particular operations required to solve the problem at hand. Thus, this programming approach simplifies parallel programming by eliminating some of the major challenges of parallel programming, namely thread communication, scheduling and orchestration. However, the application programmer has still to correctly synchronize threads on data races. This commonly requires the use of locks to guarantee atomic access to shared data. In particular, lock programming is vulnerable to deadlocks and also limits coarse grain parallelism by blocking threads that could be potentially executed in parallel.Transactional Memory (TM) thus emerges as an attractive alternative model to simplify parallel programming by removing this burden of handling data races explicitly. This model allows programmers to write parallel code as transactions, which are then guaranteed by the runtime system to execute atomically and in isolation regardless of eventual data races. TM programming thus frees the application from deadlocks and enables the exploitation of coarse grain parallelism when transactions do not conflict very often. Nevertheless, thread management and orchestration are left for the application programmer. Fortunately, this can be naturally handled by a skeleton framework. This fact makes the combination of skeleton -based and transactional programming a natural step to improve programmability since these models complement each other. In fact, this combination releases the application programmer from dealing with thread management and data races, and also inherits the performance improvements of both models. In addition to it, a skeleton framework is also amenable to skeleton - driven iii performance optimizations that exploits the application pattern and system information.This thesis thus also presents a set of pattern- oriented optimizations that are automatically selected and applied in a significant subset of transactional memory applications that shares a common pattern called worklist. These optimizations exploit the knowledge about the worklist pattern and the TM nature of the applications to avoid transaction conflicts, to prefetch data, to reduce contention etc. Using a novel autotuning mechanism, OpenSkel dynamically selects the most suitable set of these patternoriented performance optimizations for each application and adjusts them accordingly. Experimental results on a subset of five applications from the STAMP benchmark suite show that the proposed autotuning mechanism can achieve performance improvements within 2 %, on average, of a static oracle for a 16 -core UMA (Uniform Memory Access) platform and surpasses it by 7% on average for a 32 -core NUMA (Non -Uniform Memory Access) platform.Finally, this thesis also investigates skeleton -driven system- oriented performance optimizations such as thread mapping and memory page allocation. In order to do it, the OpenSkel system and also the autotuning mechanism are extended to accommodate these optimizations. The conducted experimental results on a subset of five applications from the STAMP benchmark show that the OpenSkel framework with the extended autotuning mechanism driving both pattern and system- oriented optimizations can achieve performance improvements of up to 88 %, with an average of 46 %, over a baseline version for a 16 -core UMA platform and up to 162 %, with an average of 91 %, for a 32 -core NUMA platform

Preliminary multicore architecture for Introspective Computing

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 243-245).This thesis creates a framework for Introspective Computing. Introspective Computing is a computing paradigm characterized by self-aware software. Self-aware software systems use hardware mechanisms to observe an application's execution so that they may adapt execution to improve performance, reduce power consumption, or balance user-defined fitness criteria over time-varying conditions in a system environment. We dub our framework Partner Cores. The Partner Cores framework builds upon tiled multicore architectures [11, 10, 25, 9], closely coupling cores such that one may be used to observe and optimize execution in another. Partner cores incrementally collect and analyze execution traces from code cores then exploit knowledge of the hardware to optimize execution. This thesis develops a tiled architecture for the Partner Cores framework that we dub Evolve. Evolve provides a versatile substrate upon which software may coordinate core partnerships and various forms of parallelism. To do so, Evolve augments a basic tiled architecture with introspection hardware and programmable functional units. Partner Cores software systems on the Evolve hardware may follow the style of helper threading [13, 12, 6] or utilize the programmable functional units in each core to evolve application-specific coprocessor engines. This thesis work develops two Partner Cores software systems: the Dynamic Partner-Assisted Branch Predictor and the Introspective L2 Memory System (IL2). The branch predictor employs a partner core as a coprocessor engine for general dynamic branch prediction in a corresponding code core. The IL2 retasks the silicon resources of partner cores as banks of an on-chip, distributed, software L2 cache for code cores.(cont.) The IL2 employs aggressive, application-specific prefetchers for minimizing cache miss penalties and DRAM power consumption. Our results and future work show that the branch predictor is able to sustain prediction for code core branch frequencies as high as one every 7 instructions with no degradation in accuracy; updated prediction directions are available in a low minimum of 20-21 instructions. For the IL2, we develop a pixel block prefetcher for the image data structure used in a JPEG encoder benchmark and show that a 50% improvement in absolute performance is attainable.by Jonathan M. Eastep.S.M

Runahead threads

Los temas de investigación sobre multithreading han ganado mucho interés en la arquitectura de computadores con la aparición de procesadores multihilo y multinucleo. Los procesadores SMT (Simultaneous Multithreading) son uno de estos nuevos paradigmas, combinando la capacidad de emisión de múltiples instrucciones de los procesadores superscalares con la habilidad de explotar el paralelismo a nivel de hilos (TLP). Así, la principal característica de los procesadores SMT es ejecutar varios hilos al mismo tiempo para incrementar la utilización de las etapas del procesador mediante la compartición de recursos.Los recursos compartidos son el factor clave de los procesadores SMT, ya que esta característica conlleva tratar con importantes cuestiones pues los hilos también compiten por estos recursos en el núcleo del procesador. Si bien distintos grupos de aplicaciones se benefician de disponer de SMT, las diferentes propiedades de los hilos ejecutados pueden desbalancear la asignación de recursos entre los mismos, disminuyendo los beneficios de la ejecución multihilo. Por otro lado, el problema con la memoria está aún presente en los procesadores SMT. Estos procesadores alivian algunos de los problemas de latencia provocados por la lentitud de la memoria con respecto a la CPU. Sin embargo, hilos con grandes cargas de trabajo y con altas tasas de fallos en las caches son unas de las mayores dificultades de los procesadores SMT. Estos hilos intensivos en memoria tienden a crear importantes problemas por la contención de recursos. Por ejemplo, pueden llegar a bloquear recursos críticos debido a operaciones de larga latencia impidiendo no solo su ejecución, sino el progreso de la ejecución de los otros hilos y, por tanto, degradando el rendimiento general del sistema.El principal objetivo de esta tesis es aportar soluciones novedosas a estos problemas y que mejoren el rendimiento de los procesadores SMT. Para conseguirlo, proponemos los Runahead Threads (RaT) aplicando una ejecución especulativa basada en runahead. RaT es un mecanismo alternativo a las políticas previas de gestión de recursos las cuales usualmente restringían a los hilos intensivos en memoria para conseguir más productividad.La idea clave de RaT es transformar un hilo intensivo en memoria en un hilo ligero en el uso de recursos que progrese especulativamente. Así, cuando un hilo sufre de un acceso de larga latencia, RaT transforma dicho hilo en un hilo de runahead mientras dicho fallo está pendiente. Los principales beneficios de esta simple acción son varios. Mientras un hilo está en runahead, éste usa los diferentes recursos compartidos sin monopolizarlos o limitarlos con respecto a los otros hilos. Al mismo tiempo, esta ejecución especulativa realiza prebúsquedas a memoria que se solapan con el fallo principal, por tanto explotando el paralelismo a nivel de memoria y mejorando el rendimiento.RaT añade muy poco hardware extra y complejidad en los procesadores SMT con respecto a su implementación. A través de un mecanismo de checkpoint y lógica de control adicional, podemos dotar a los contextos hardware con la capacidad de ejecución en runahead. Por medio de RaT, contribuímos a aliviar simultaneamente dos problemas en el contexto de los procesadores SMT. Primero, RaT reduce el problema de los accesos de larga latencia en los SMT mediante el paralelismo a nivel de memoria (MLP). Un hilo prebusca datos en paralelo en vez de estar parado debido a un fallo de L2 mejorando su rendimiento individual. Segundo, RaT evita que los hilos bloqueen recursos bajo fallos de larga latencia. RaT asegura que el hilo intensivo en memoria recicle más rápido los recursos compartidos que usa debido a la naturaleza de la ejecución especulativa.La principal limitación de RaT es que los hilos especulativos pueden ejecutar instrucciones extras cuando no realizan prebúsqueda e innecesariamente consumir recursos de ejecución en el procesador SMT. Este inconveniente resulta en hilos de runahead ineficientes pues no contribuyen a la ganancia de rendimiento e incrementan el consumo de energía debido al número extra de instrucciones especulativas. Por consiguiente, en esta tesis también estudiamos diferentes soluciones dirigidas a solventar esta desventaja del mecanismo RaT. El resultado es un conjunto de soluciones complementarias para mejorar la eficiencia de RaT en términos de consumo de potencia y gasto energético.Por un lado, mejoramos la eficiencia de RaT aplicando ciertas técnicas basadas en el análisis semántico del código ejecutado por los hilos en runahead. Proponemos diferentes técnicas que analizan y controlan la utilidad de ciertos patrones de código durante la ejecución en runahead. Por medio de un análisis dinámico, los hilos en runahead supervisan la utilidad de ejecutar los bucles y subrutinas dependiendo de las oportunidades de prebúsqueda. Así, RaT decide cual de estas estructuras de programa ejecutar dependiendo de la información de utilidad obtenida, decidiendo entre parar o saltar el bucle o la subrutina para reducir el número de las instrucciones no útiles. Entre las técnicas propuestas, conseguimos reducir las instrucciones especulativas y la energía gastada mientras obtenemos rendimientos similares a la técnica RaT original.Por otro lado, también proponemos lo que denominamos hilos de runahead eficientes. Esta propuesta se basa en una técnica más fina que cubre todo el rango de ejecución en runahead, independientemente de las características del programa ejecutado. La idea principal es averiguar "cuando" y "durante cuanto" un hilo en runahead debe ser ejecutado prediciendo lo que denominamos distancia útil de runahead. Los resultados muestran que la mejor de estas propuestas basadas en la predicción de la distancia de runahead reducen significativamente el número de instrucciones extras así como también el consumo de potencia. Asimismo, conseguimos mantener los beneficios de rendimiento de los hilos en runahead, mejorando de esta forma la eficiencia energética de los procesadores SMT usando el mecanismo RaT.La evolución de RaT desarrollada durante toda esta investigación nos proporciona no sólo una propuesta orientada a un mayor rendimiento sino también una forma eficiente de usar los recursos compartidos en los procesadores SMT en presencia de operaciones de memoria de larga latencia.Dado que los diseños SMT en el futuro estarán orientados a optimizar una combinación de rendimiento individual en las aplicaciones, la productividad y el consumo de energía, los mecanismos basados en RaT aquí propuestos son interesantes opciones que proporcionan un mejor balance de rendimiento y energía que las propuestas previas en esta área.Research on multithreading topics has gained a lot of interest in the computer architecture community due to new commercial multithreaded and multicore processors. Simultaneous Multithreading (SMT) is one of these relatively new paradigms, which combines the multiple instruction issue features of superscalar processors with the ability of multithreaded architectures to exploit thread level parallelism (TLP). The main feature of SMT processors is to execute multiple threads that increase the utilization of the pipeline by sharing many more resources than in other types of processors.Shared resources are the key of simultaneous multithreading, what makes the technique worthwhile.This feature also entails important challenges to deal with because threads also compete for resources in the processor core. On the one hand, although certain types and mixes of applications truly benefit from SMT, the different features of threads can unbalance the resource allocation among threads, diminishing the benefit of multithreaded execution. On the other hand, the memory wall problem is still present in these processors. SMT processors alleviate some of the latency problems arisen by main memory's slowness relative to the CPUs. Nevertheless, threads with high cache miss rates that use large working sets are one of the major pitfalls of SMT processors. These memory intensive threads tend to use processor and memory resources poorly creating the highest resource contention problems. Memory intensive threads can clog up shared resources due to long latency memory operations without making progress on a SMT processor, thereby hindering overall system performance.The main goal of this thesis is to alleviate these shortcomings on SMT scenarios. To accomplish this, the key contribution of this thesis is the application of the paradigm of Runahead execution in the design of multithreaded processors by Runahead Threads (RaT). RaT shows to be a promising alternative to prior SMT resource management mechanisms which usually restrict memory bound threads in order to get higher throughputs.The idea of RaT is to transform a memory intensive thread into a light-consumer resource thread by allowing that thread to progress speculatively. Therefore, as soon as a thread undergoes a long latency load, RaT transforms the thread to a runahead thread while it has that long latency miss outstanding. The main benefits of this simple action performed by RaT are twofold. While being a runahead thread, this thread uses the different shared resources without monopolizing or limiting the available resources for other threads. At the same time, this fast speculative thread issues prefetches that overlap other memory accesses with the main miss, thereby exploiting the memory level parallelism.Regarding implementation issues, RaT adds very little extra hardware cost and complexity to an existing SMT processor. Through a simple checkpoint mechanism and little additional control logic, we can equip the hardware contexts with the runahead thread capability. Therefore, by means of runahead threads, we contribute to alleviate simultaneously the two shortcomings in the context of SMT processor improving the performance. First, RaT alleviates the long latency load problem on SMT processors by exposing memory level parallelism (MLP). A thread prefetches data in parallel (if MLP is available) improving its individual performance rather than be stalled on an L2 miss. Second, RaT prevents threads from clogging resources on long latency loads. RaT ensures that the L2-missing thread recycles faster the shared resources it uses by the nature of runahead speculative execution. This avoids memory intensive threads clogging the important processor resources up.The main limitation of RaT though is that runahead threads can execute useless instructions and unnecessarily consume execution resources on the SMT processor when there is no prefetching to be exploited. This drawback results in inefficient runahead threads which do not contribute to the performance gain and increase dynamic energy consumption due to the number of extra speculatively executed instructions. Therefore, we also propose different solutions aimed at this major disadvantage of the Runahead Threads mechanism. The result of the research on this line is a set of complementary solutions to enhance RaT in terms of power consumption and energy efficiency.On the one hand, code semantic-aware Runahead threads improve the efficiency of RaT using coarse-grain code semantic analysis at runtime. We provide different techniques that analyze the usefulness of certain code patterns during runahead thread execution. The code patterns selected to perform that analysis are loops and subroutines. By means of the proposed coarse grain analysis, runahead threads oversee the usefulness of loops or subroutines depending on the prefetches opportunities during their executions. Thus, runahead threads decide which of these particular program structures execute depending on the obtained usefulness information, deciding either stall or skip the loop or subroutine executions to reduce the number of useless runahead instructions. Some of the proposed techniques reduce the speculative instruction and wasted energy while achieving similar performance to RaT.On the other hand, the efficient Runahead thread proposal is another contribution focused on improving RaT efficiency. This approach is based on a generic technique which covers all runahead thread executions, independently of the executed program characteristics as code semantic-aware runahead threads are. The key idea behind this new scheme is to find out --when' and --how long' a thread should be executed in runahead mode by predicting the useful runahead distance. The results show that the best of these approaches based on the runahead distance prediction significantly reduces the number of extra speculative instructions executed in runahead threads, as well as the power consumption. Likewise, it maintains the performance benefits of the runahead threads, thereby improving the energy-efficiency of SMT processors using the RaT mechanism.The evolution of Runahead Threads developed in this research provides not only a high performance but also an efficient way of using shared resources in SMT processors in the presence of long latency memory operations. As designers of future SMT systems will be increasingly required to optimize for a combination of single thread performance, total throughput, and energy consumption, RaT-based mechanisms are promising options that provide better performance and energy balance than previous proposals in the field