2,227 research outputs found

    Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code

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    This paper introduces Tiramisu, a polyhedral framework designed to generate high performance code for multiple platforms including multicores, GPUs, and distributed machines. Tiramisu introduces a scheduling language with novel extensions to explicitly manage the complexities that arise when targeting these systems. The framework is designed for the areas of image processing, stencils, linear algebra and deep learning. Tiramisu has two main features: it relies on a flexible representation based on the polyhedral model and it has a rich scheduling language allowing fine-grained control of optimizations. Tiramisu uses a four-level intermediate representation that allows full separation between the algorithms, loop transformations, data layouts, and communication. This separation simplifies targeting multiple hardware architectures with the same algorithm. We evaluate Tiramisu by writing a set of image processing, deep learning, and linear algebra benchmarks and compare them with state-of-the-art compilers and hand-tuned libraries. We show that Tiramisu matches or outperforms existing compilers and libraries on different hardware architectures, including multicore CPUs, GPUs, and distributed machines.Comment: arXiv admin note: substantial text overlap with arXiv:1803.0041

    Peachy Parallel Assignments (EduHPC 2018)

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    Peachy Parallel Assignments are a resource for instructors teaching parallel and distributed programming. These are high-quality assignments, previously tested in class, that are readily adoptable. This collection of assignments includes implementing a subset of OpenMP using pthreads, creating an animated fractal, image processing using histogram equalization, simulating a storm of high-energy particles, and solving the wave equation in a variety of settings. All of these come with sample assignment sheets and the necessary starter code.Departamento de Informática (Arquitectura y Tecnología de Computadores, Ciencias de la Computación e Inteligencia Artificial, Lenguajes y Sistemas Informáticos)Facilitar la inclusión de ejercicios prácticos de programación paralela en cursos de Computación Paralela o de alto rendimiento (HPC)Comunicación en congreso: Descripción de ejercicios prácticos con acceso a material ya desarrollado y probado

    Communion: a new strategy for memory management in high-performance computer systems

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    Modern computers present a big gap between peak performance and sustained performance. There are many reasons for this situation, but mainly involving an inefficient usage of computational resources. Nowadays the memory system is the most critical component because of its growing inability to keep up with the processor requests. Technological trends have produced a large and growing gap between CPU speeds and DRAM speeds. Much research has focused this memory system problem, including program optimizing techniques, data locality enhancement, hardware and software prefetching, decoupled architectures, mutithreading, speculative loads and execution. These techniques have got a relative success, but they focus only one component in the hardware or software systems. We present here a new strategy for memory management in high-performance computer systems, named COMMUNION. The basic idea behind this strategy is cooperation. We introduce some interaction possibilities among system programs that are responsible to generate and execute application programs. So, we investigate two specific interactions: between the compiler and the operating system, and among the compiling system components. The experimental results show that it’s possible to get improvements of about 10 times in execution time, and about 5 times in memory demand. In the interaction between compiler and operating system, named Compiler-Aided Page Replacement (CAPR), we achieved a reduction of about 10% in space-time product, with an increase of only 0.5% in the total execution time. All these results show that it’s possible to manage main memory with a better efficiency than current systems.Eje: Procesamiento distribuido y paralelo. Tratamiento de señalesRed de Universidades con Carreras en Informática (RedUNCI

    Communion: a new strategy form memory management in high-performance computer

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    Modern computers present a big gap between peak performance and sustained performance. There are many reasons for this situation, but mainly involving an inefficient usage of computational resources. Nowadays the memory system is the most critical component because of its growing inability to keep up with the processor requests. Technological trends have produced a large and growing gap between CPU speeds and DRAM speeds. Much research has focused this memory system problem, including program optimizing techniques, data locality enhancement, hardware and software prefetching, decoupled architectures, multithreading, speculative loads and execution. These techniques have got a relative success, but they focus only one component in the hardware or software systems. We present here a new strategy for memory management in high-performance computer systems, named COMMUNION. The basic idea behind this strategy is "cooperation". We introduce some interaction possibilities among system programs that are responsible to generate and execute application programs. So, we investigate two specific interactions: between the compiler and the operating system, and among the compiling system components. The experimental results show that it's possible to get improvements of about 10 times in execution time, and about 5 times in memory demand, enhancing the interaction between the compiling system components. In the interaction between compiler and operating system, named Compiler-Aided Page Replacement (CAPR), we achieved a reduction of about 10% in space-time product, with an increase of only 0.5% in the total execution time. All these results show that it s possible to manage main memory with a better efficiency than current systems.Facultad de Informátic

    Communion: a new strategy for memory management in high-performance computer systems

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    Modern computers present a big gap between peak performance and sustained performance. There are many reasons for this situation, but mainly involving an inefficient usage of computational resources. Nowadays the memory system is the most critical component because of its growing inability to keep up with the processor requests. Technological trends have produced a large and growing gap between CPU speeds and DRAM speeds. Much research has focused this memory system problem, including program optimizing techniques, data locality enhancement, hardware and software prefetching, decoupled architectures, mutithreading, speculative loads and execution. These techniques have got a relative success, but they focus only one component in the hardware or software systems. We present here a new strategy for memory management in high-performance computer systems, named COMMUNION. The basic idea behind this strategy is cooperation. We introduce some interaction possibilities among system programs that are responsible to generate and execute application programs. So, we investigate two specific interactions: between the compiler and the operating system, and among the compiling system components. The experimental results show that it’s possible to get improvements of about 10 times in execution time, and about 5 times in memory demand. In the interaction between compiler and operating system, named Compiler-Aided Page Replacement (CAPR), we achieved a reduction of about 10% in space-time product, with an increase of only 0.5% in the total execution time. All these results show that it’s possible to manage main memory with a better efficiency than current systems.Eje: Procesamiento distribuido y paralelo. Tratamiento de señalesRed de Universidades con Carreras en Informática (RedUNCI

    Using shared-data localization to reduce the cost of inspector-execution in unified-parallel-C programs

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    Programs written in the Unified Parallel C (UPC) language can access any location of the entire local and remote address space via read/write operations. However, UPC programs that contain fine-grained shared accesses can exhibit performance degradation. One solution is to use the inspector-executor technique to coalesce fine-grained shared accesses to larger remote access operations. A straightforward implementation of the inspector executor transformation results in excessive instrumentation that hinders performance.; This paper addresses this issue and introduces various techniques that aim at reducing the generated instrumentation code: a shared-data localization transformation based on Constant-Stride Linear Memory Descriptors (CSLMADs) [S. Aarseth, Gravitational N-Body Simulations: Tools and Algorithms, Cambridge Monographs on Mathematical Physics, Cambridge University Press, 2003.], the inlining of data locality checks and the usage of an index vector to aggregate the data. Finally, the paper introduces a lightweight loop code motion transformation to privatize shared scalars that were propagated through the loop body.; A performance evaluation, using up to 2048 cores of a POWER 775, explores the impact of each optimization and characterizes the overheads of UPC programs. It also shows that the presented optimizations increase performance of UPC programs up to 1.8 x their UPC hand-optimized counterpart for applications with regular accesses and up to 6.3 x for applications with irregular accesses.Peer ReviewedPostprint (author's final draft
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