927 research outputs found

    An assessment of the connection machine

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    The CM-2 is an example of a connection machine. The strengths and problems of this implementation are considered as well as important issues in the architecture and programming environment of connection machines in general. These are contrasted to the same issues in Multiple Instruction/Multiple Data (MIMD) microprocessors and multicomputers

    System software for the finite element machine

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    The Finite Element Machine is an experimental parallel computer developed at Langley Research Center to investigate the application of concurrent processing to structural engineering analysis. This report describes system-level software which has been developed to facilitate use of the machine by applications researchers. The overall software design is outlined, and several important parallel processing issues are discussed in detail, including processor management, communication, synchronization, and input/output. Based on experience using the system, the hardware architecture and software design are critiqued, and areas for further work are suggested

    Design of testbed and emulation tools

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    The research summarized was concerned with the design of testbed and emulation tools suitable to assist in projecting, with reasonable accuracy, the expected performance of highly concurrent computing systems on large, complete applications. Such testbed and emulation tools are intended for the eventual use of those exploring new concurrent system architectures and organizations, either as users or as designers of such systems. While a range of alternatives was considered, a software based set of hierarchical tools was chosen to provide maximum flexibility, to ease in moving to new computers as technology improves and to take advantage of the inherent reliability and availability of commercially available computing systems

    MPSoCBench : um framework para avaliação de ferramentas e metodologias para sistemas multiprocessados em chip

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    Orientador: Rodolfo Jardim de AzevedoTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Recentes metodologias e ferramentas de projetos de sistemas multiprocessados em chip (MPSoC) aumentam a produtividade por meio da utilização de plataformas baseadas em simuladores, antes de definir os últimos detalhes da arquitetura. No entanto, a simulação só é eficiente quando utiliza ferramentas de modelagem que suportem a descrição do comportamento do sistema em um elevado nível de abstração. A escassez de plataformas virtuais de MPSoCs que integrem hardware e software escaláveis nos motivou a desenvolver o MPSoCBench, que consiste de um conjunto escalável de MPSoCs incluindo quatro modelos de processadores (PowerPC, MIPS, SPARC e ARM), organizado em plataformas com 1, 2, 4, 8, 16, 32 e 64 núcleos, cross-compiladores, IPs, interconexões, 17 aplicações paralelas e estimativa de consumo de energia para os principais componentes (processadores, roteadores, memória principal e caches). Uma importante demanda em projetos MPSoC é atender às restrições de consumo de energia o mais cedo possível. Considerando que o desempenho do processador está diretamente relacionado ao consumo, há um crescente interesse em explorar o trade-off entre consumo de energia e desempenho, tendo em conta o domínio da aplicação alvo. Técnicas de escalabilidade dinâmica de freqüência e voltagem fundamentam-se em gerenciar o nível de tensão e frequência da CPU, permitindo que o sistema alcance apenas o desempenho suficiente para processar a carga de trabalho, reduzindo, consequentemente, o consumo de energia. Para explorar a eficiência energética e desempenho, foram adicionados recursos ao MPSoCBench, visando explorar escalabilidade dinâmica de voltaegem e frequência (DVFS) e foram validados três mecanismos com base na estimativa dinâmica de energia e taxa de uso de CPUAbstract: Recent design methodologies and tools aim at enhancing the design productivity by providing a software development platform before the definition of the final Multiprocessor System on Chip (MPSoC) architecture details. However, simulation can only be efficiently performed when using a modeling and simulation engine that supports system behavior description at a high abstraction level. The lack of MPSoC virtual platform prototyping integrating both scalable hardware and software in order to create and evaluate new methodologies and tools motivated us to develop the MPSoCBench, a scalable set of MPSoCs including four different ISAs (PowerPC, MIPS, SPARC, and ARM) organized in platforms with 1, 2, 4, 8, 16, 32, and 64 cores, cross-compilers, IPs, interconnections, 17 parallel version of software from well-known benchmarks, and power consumption estimation for main components (processors, routers, memory, and caches). An important demand in MPSoC designs is the addressing of energy consumption constraints as early as possible. Whereas processor performance comes with a high power cost, there is an increasing interest in exploring the trade-off between power and performance, taking into account the target application domain. Dynamic Voltage and Frequency Scaling techniques adaptively scale the voltage and frequency levels of the CPU allowing it to reach just enough performance to process the system workload while meeting throughput constraints, and thereby, reducing the energy consumption. To explore this wide design space for energy efficiency and performance, both for hardware and software components, we provided MPSoCBench features to explore dynamic voltage and frequency scalability (DVFS) and evaluated three mechanisms based on energy estimation and CPU usage rateDoutoradoCiência da ComputaçãoDoutora em Ciência da Computaçã

    Invasive compute balancing for applications with shared and hybrid parallelization

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    This is the author manuscript. The final version is available from the publisher via the DOI in this record.Achieving high scalability with dynamically adaptive algorithms in high-performance computing (HPC) is a non-trivial task. The invasive paradigm using compute migration represents an efficient alternative to classical data migration approaches for such algorithms in HPC. We present a core-distribution scheduler which realizes the migration of computational power by distributing the cores depending on the requirements specified by one or more parallel program instances. We validate our approach with different benchmark suites for simulations with artificial workload as well as applications based on dynamically adaptive shallow water simulations, and investigate concurrently executed adaptivity parameter studies on realistic Tsunami simulations. The invasive approach results in significantly faster overall execution times and higher hardware utilization than alternative approaches. A dynamic resource management is therefore mandatory for a more efficient execution of scenarios similar to our simulations, e.g. several Tsunami simulations in urgent computing, to overcome strong scalability challenges in the area of HPC. The optimizations obtained by invasive migration of cores can be generalized to similar classes of algorithms with dynamic resource requirements.This work was supported by the German Research Foundation (DFG) as part of the Transregional Collaborative Research Centre ”Invasive Computing” (SFB/TR 89)

    Design of Efficient TLB-based Data Classification Mechanisms in Chip Multiprocessors

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    Most of the data referenced by sequential and parallel applications running in current chip multiprocessors are referenced by a single thread, i.e., private. Recent proposals leverage this observation to improve many aspects of chip multiprocessors, such as reducing coherence overhead or the access latency to distributed caches. The effectiveness of those proposals depends to a large extent on the amount of detected private data. However, the mechanisms proposed so far either do not consider either thread migration or the private use of data within different application phases, or do entail high overhead. As a result, a considerable amount of private data is not detected. In order to increase the detection of private data, this thesis proposes a TLB-based mechanism that is able to account for both thread migration and private application phases with low overhead. Classification status in the proposed TLB-based classification mechanisms is determined by the presence of the page translation stored in other core's TLBs. The classification schemes are analyzed in multilevel TLB hierarchies, for systems with both private and distributed shared last-level TLBs. This thesis introduces a page classification approach based on inspecting other core's TLBs upon every TLB miss. In particular, the proposed classification approach is based on exchange and count of tokens. Token counting on TLBs is a natural and efficient way for classifying memory pages. It does not require the use of complex and undesirable persistent requests or arbitration, since when two ormore TLBs race for accessing a page, tokens are appropriately distributed classifying the page as shared. However, TLB-based ability to classify private pages is strongly dependent on TLB size, as it relies on the presence of a page translation in the system TLBs. To overcome that, different TLB usage predictors (UP) have been proposed, which allow a page classification unaffected by TLB size. Specifically, this thesis introduces a predictor that obtains system-wide page usage information by either employing a shared last-level TLB structure (SUP) or cooperative TLBs working together (CUP).La mayor parte de los datos referenciados por aplicaciones paralelas y secuenciales que se ejecutan enCMPs actuales son referenciadas por un único hilo, es decir, son privados. Recientemente, algunas propuestas aprovechan esta observación para mejorar muchos aspectos de los CMPs, como por ejemplo reducir el sobrecoste de la coherencia o la latencia de los accesos a cachés distribuidas. La efectividad de estas propuestas depende en gran medida de la cantidad de datos que son considerados privados. Sin embargo, los mecanismos propuestos hasta la fecha no consideran la migración de hilos de ejecución ni las fases de una aplicación. Por tanto, una cantidad considerable de datos privados no se detecta apropiadamente. Con el fin de aumentar la detección de datos privados, proponemos un mecanismo basado en las TLBs, capaz de reclasificar los datos a privado, y que detecta la migración de los hilos de ejecución sin añadir complejidad al sistema. Los mecanismos de clasificación en las TLBs se han analizado en estructuras de varios niveles, incluyendo TLBs privadas y con un último nivel de TLB compartido y distribuido. Esta tesis también presenta un mecanismo de clasificación de páginas basado en la inspección de las TLBs de otros núcleos tras cada fallo de TLB. De forma particular, el mecanismo propuesto se basa en el intercambio y el cuenteo de tokens (testigos). Contar tokens en las TLBs supone una forma natural y eficiente para la clasificación de páginas de memoria. Además, evita el uso de solicitudes persistentes o arbitraje alguno, ya que si dos o más TLBs compiten para acceder a una página, los tokens se distribuyen apropiadamente y la clasifican como compartida. Sin embargo, la habilidad de los mecanismos basados en TLB para clasificar páginas privadas depende del tamaño de las TLBs. La clasificación basada en las TLBs se basa en la presencia de una traducción en las TLBs del sistema. Para evitarlo, se han propuesto diversos predictores de uso en las TLBs (UP), los cuales permiten una clasificación independiente del tamaño de las TLBs. En concreto, esta tesis presenta un sistema mediante el que se obtiene información de uso de página a nivel de sistema con la ayuda de un nivel de TLB compartida (SUP) o mediante TLBs cooperando juntas (CUP).La major part de les dades referenciades per aplicacions paral·leles i seqüencials que s'executen en CMPs actuals són referenciades per un sol fil, és a dir, són privades. Recentment, algunes propostes aprofiten aquesta observació per a millorar molts aspectes dels CMPs, com és reduir el sobrecost de la coherència o la latència d'accés a memòries cau distribuïdes. L'efectivitat d'aquestes propostes depen en gran mesura de la quantitat de dades detectades com a privades. No obstant això, els mecanismes proposats fins a la data no consideren la migració de fils d'execució ni les fases d'una aplicació. Per tant, una quantitat considerable de dades privades no es detecta apropiadament. A fi d'augmentar la detecció de dades privades, aquesta tesi proposa un mecanisme basat en les TLBs, capaç de reclassificar les dades com a privades, i que detecta la migració dels fils d'execució sense afegir complexitat al sistema. Els mecanismes de classificació en les TLBs s'han analitzat en estructures de diversos nivells, incloent-hi sistemes amb TLBs d'últimnivell compartides i distribuïdes. Aquesta tesi presenta un mecanisme de classificació de pàgines basat en inspeccionar les TLBs d'altres nuclis després de cada fallada de TLB. Concretament, el mecanisme proposat es basa en l'intercanvi i el compte de tokens. Comptar tokens en les TLBs suposa una forma natural i eficient per a la classificació de pàgines de memòria. A més, evita l'ús de sol·licituds persistents o arbitratge, ja que si dues o més TLBs competeixen per a accedir a una pàgina, els tokens es distribueixen apropiadament i la classifiquen com a compartida. No obstant això, l'habilitat dels mecanismes basats en TLB per a classificar pàgines privades depenen de la grandària de les TLBs. La classificació basada en les TLBs resta en la presència d'una traducció en les TLBs del sistema. Per a evitar-ho, s'han proposat diversos predictors d'ús en les TLBs (UP), els quals permeten una classificació independent de la grandària de les TLBs. Específicament, aquesta tesi introdueix un predictor que obté informació d'ús de la pàgina a escala de sistema mitjançant un nivell de TLB compartida (SUP) or mitjançant TLBs cooperant juntes (CUP).Esteve García, A. (2017). Design of Efficient TLB-based Data Classification Mechanisms in Chip Multiprocessors [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86136TESI

    Anatomy of a message in the Alewife multiprocessor

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    Shared-memory provides a uniform and attractive mechanism for communication. For efficiency, it is often implemented with a layer of interpretive hardware on top of a message-passing communications network. This interpretive layer is responsible for data location, data movement, and cache coherence. It uses patterns of communication that benefit common programming styles, but which are only heuristics. This suggests that certain styles of communication may benefit from direct access to the underlying communications substrate. The Alewife machine, a shared-memory multiprocessor being built at MIT, provides such an interface. The interface is an integral part of the shared memory implementation and affords direct, user-level access to the network queues, supports an efficient DMA mechanism, and includes fast trap handling for message reception. This paper discusses the design and implementation of the Alewife message-passing interface and addresses the issues and advantages of using such an interface to complement hardware-synthesized shared memory.National Science Foundation (U.S.) (Grant MIP-9012773)United States. Defense Advanced Research Projects Agency (Contract N00014-87-K-0825

    Code Generation and Global Optimization Techniques for a Reconfigurable PRAM-NUMA Multicore Architecture

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