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检索条件"任意字段=9th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming"

共 385 条记录，以下是111-120 订阅

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Data Transformations Enabling Loop Vectorization on Multithreaded Data parallel Architectures

Data Transformations Enabling Loop Vectorization on Multithr...

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15th acm sigplan symposium on principles and practice of parallel programming

作者： Jang, Byunghyun Mistry, Perhaad Schaa, Dana Dominguez, Rodrigo Kaeli, David Northeastern Univ Dept ECE Boston MA 02115 USA

ISBN: (纸本)9781605587080

Loop vectorization, a key feature exploited to obtain high performance on Single Instruction Multiple Data (SIMD) vector architectures, is significantly hindered by irregular memory access patterns in the data stream. this paper describes data transformations that allow us to vectorize loops targeting massively multithreaded data parallel architectures. We present a mathematical model that captures loop-based memory access patterns and computes the most appropriate data transformations in order to enable vectorization. Our experimental results show that the proposed data transformations can significantly increase the number of loops that can be vectorized and enhance the data-level parallelism of applications. Our results also show that the overhead associated with our data transformations can be easily amortized as the size of the input data set increases. For the set of high performance benchmark kernels studied, we achieve consistent and significant performance improvements (up to 11.4X) by applying vectorization using our data transformation approach.

关键词： Loop Vectorization Data Transformation GPGPU

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Incremental Flattening for Nested Data parallelism 19

Incremental Flattening for Nested Data Parallelism

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24th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Henriksen, Troels thoroe, Frederik Elsman, Martin Oancea, Cosmin Univ Copenhagen Copenhagen Denmark

ISBN: (纸本)9781450362252

Compilation techniques for nested-parallel applications that can adapt to hardware and dataset characteristics are vital for unlocking the power of modern hardware. this paper proposes such a technique, which builds on flattening and is applied in the context of a functional data-parallel language. Our solution uses the degree of utilized parallelism as the driver for generating a multitude of code versions, which together cover all possible mappings of the application's regular nested parallelism to the levels of parallelism supported by the hardware. these code versions are then combined into one program by guarding them with predicates, whose threshold values are automatically tuned to hardware and dataset characteristics. Our unsupervised method-of statically clustering datasets to code versions-is different from autotuning work that typically searches for the combination of code transformations producing a single version, best suited for a specific dataset or on average for all datasets. We demonstrate-by fully integrating our technique in the repertoire of a compiler for the Futhark programming language-significant performance gains on two GPUs for three real-world applications, from the financial domain, and for six Rodinia benchmarks.

关键词： functional language parallel compilers GPGPU

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Fine-grain parallel megabase sequence comparison with multiple heterogeneous GPUs 14

Fine-grain parallel megabase sequence comparison with multip...

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2014 19th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2014

作者： De Sandes, Edans F.O. Miranda, Guillermo Melo, Alba C.M.A. Martorell, Xavier Ayguadé, Eduard University of Brasilia Brazil Universitat Politècnica de Catalunya Barcelona Supercomputing Center Spain

ISBN: (纸本)9781450326568

this paper proposes and evaluates a parallel strategy to execute the exact Smith-Waterman (SW) algorithm for megabase DNA sequences in heterogeneous multi-GPU platforms. In our strategy, the computation of a single huge SW matrix is spread over multiple GPUs, which communicate border elements to the neighbour, using a circular buffer mechanism that hides the communication overhead. We compared 4 pairs of human-chimpanzee homologous chromosomes using 2 different GPU environments, obtaining a performance of up to 140.36 GCUPS (Billion of cells processed per second) with 3 heterogeneous GPUS.

关键词： Graphics processing unit

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Shared-memory performance profiling 97

Shared-memory performance profiling

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Proceedings of the 1997 6th acm sigplan symposium on principles and practice of parallel programming

作者： Xu, Zhichen Larus, James R. Miller, Barton P. Univ of Wisconsin Madison WI United States

ISBN: (纸本)9780897919067

this paper describes a new approach to finding performance bottlenecks in shared-memory parallel programs and its embodiment in the Paradyn parallel Performance Tools running with the Blizzard fine-grain distributed shared memory system. this approach exploits the underlying system's cache coherence protocol to detect data sharing patterns that indicate potential performance bottlenecks and presents performance measurements in a data-centric manner. As a demonstration, Paradyn helped us improve the performance of a new shared-memory application program by a factor of four.

关键词： parallel processing systems

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Leveraging parallel Nesting in Transactional Memory

Leveraging Parallel Nesting in Transactional Memory

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15th acm sigplan symposium on principles and practice of parallel programming

作者： Barreto, Joao Dragojevic, Aleksandar Ferreira, Paulo Guerraoui, Rachid Kapalka, Michal Univ Tecn Lisboa INESC ID Lisbon Portugal Swiss Fed Inst Technol CH-1015 Lausanne Switzerland

ISBN: (纸本)9781605587080

Exploiting the emerging reality of affordable multi-core architectures goes through providing programmers with simple abstractions that would enable them to easily turn their sequential programs into concurrent ones that expose as much parallelism as possible. While transactional memory promises to make concurrent programming easy to a wide programmer community, current implementations either disallow nested transactions to run in parallel or do not scale to arbitrary parallel nesting depths. this is an important obstacle to the central goal of transactional memory, as programmers can only start parallel threads in restricted parts of their code. this paper addresses the intrinsic difficulty behind the support for parallel nesting in transactional memory, and proposes a novel solution that, to the best of our knowledge, is the first practical solution to meet the lowest theoretical upper bound known for the problem. Using a synthetic workload configured to test parallel transactions on a multi-core machine, a practical implementation of our algorithm yields substantial speed-ups (up to 22x with 33 threads) relatively to serial nesting, and shows that the time to start and commit transactions, as well as to detect conflicts, is independent of nesting depth.

关键词： Algorithms Nested parallel programs fork-join work-stealing transactional memory

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GPU Initiated OpenSHMEM: Correct and Eicient Intra-Kernel Networking for dGPUs 25

GPU Initiated OpenSHMEM: Correct and Eicient Intra-Kernel Ne...

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25th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Hamidouche, Khaled LeBeane, Michael Adv Micro Devices Inc Santa Clara CA 95054 USA

ISBN: (纸本)9781450368186

Current state-of-the-art in GPU networking utilizes a host-centric, kernel-boundary communication model that reduces performance and increases code complexity. To address these concerns, recent works have explored performing network operations from within a GPU kernel itself. However, these approaches typically involve the CPU in the critical path, which leads to high latency and ineicient utilization of network and/or GPU resources. In this work, we introduce GPU Initiated OpenSHMEM (GIO), a new intra-kernel PGAS programming model and runtime that enables GPUs to communicate directly with a NIC without the intervention of the CPU. We accomplish this by exploring the GPU's coarse-grained memory model and correcting semantic mismatches when GPUs wish to directly interact with the network. GIO also reduces latency by relying on a novel template-based design to minimize the overhead of initiating a network operation. We illustrate that for structured applications like a Jacobi 2D stencil, GIO can improve application performance by up to 40% compared to traditional kernel-boundary networking. Furthermore, we demonstrate that on irregular applications like Sparse Triangular Solve (SpTS), GIO provides up to 44% improvement compared to existing intra-kernel networking schemes.

关键词： GPUs Distributed programming models RDMA networks

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Work-stealing with Configurable Scheduling Strategies 13

Work-stealing with Configurable Scheduling Strategies

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18th acm sigplan symposium on principles and practice of parallel programming

作者： Wimmer, Martin Traeff, Jesper Larsson Cederman, Daniel Tsigas, Philippas Vienna Univ Technol Fac Informat Res Grp Parallel Comp A-1040 Vienna Austria Chalmers Univ Technol S-41296 Gothenburg Sweden

ISBN: (纸本)9781450319225

Work-stealing systems are typically oblivious to the nature of the tasks they are scheduling. they do not know or take into account how long a task will take to execute or how many subtasks it will spawn. Moreover, task execution order is typically determined by an underlying task storage data structure, and cannot be changed. there are thus possibilities for optimizing task parallel executions by providing information on specific tasks and their preferred execution order to the scheduling system. We investigate generalizations of work-stealing and introduce a framework enabling applications to dynamically provide hints on the nature of specific tasks using scheduling strategies. Strategies can be used to independently control both local task execution and steal order. Strategies allow optimizations on specific tasks, in contrast to more conventional scheduling policies that are typically global in scope. Strategies are composable and allow different, specific scheduling choices for different parts of an application simultaneously. We have implemented a work-stealing system based on our strategy framework. A series of benchmarks demonstrates beneficial effects that can be achieved with scheduling strategies.

关键词： Algorithms Work-stealing scheduler hints strategies priorities

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Automatic Formal Verification of MPI-Based parallel Programs 11

Automatic Formal Verification of MPI-Based Parallel Programs

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16th acm symposium on principles and practice of parallel programming

作者： Siegel, Stephen F. Zirkel, Timothy K. Univ Delaware Verified Software Lab Dept Comp & Informat Sci Newark DE 19716 USA

ISBN: (纸本)9781450301190

the Toolkit for Accurate Scientific Software (TASS) is a suite of tools for the formal verification of MPI-based parallel programs used in computational science. TASS can verify various safety properties as well as compare two programs for functional equivalence. the TASS front end takes an integer n >= 1 and a C/MPI program, and constructs an abstract model of the program with n processes. Procedures, structs, (multi-dimensional) arrays, heap-allocated data, pointers, and pointer arithmetic are all representable in a TASS model. the model is then explored using symbolic execution and explicit state space enumeration. A number of techniques are used to reduce the time and memory consumed. A variety of realistic MPI programs have been verified with TASS, including Jacobi iteration and manager-worker type programs, and some subtle defects have been discovered. TASS is written in Java and is available from http://***/tass under the Gnu Public License.

关键词： Verification Symbolic execution MPI message-passing debugging verification

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parallelizing algorithms for symbolic computation using ||MAPLE|| 93

Parallelizing algorithms for symbolic computation using ||MA...

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4th acm sigplan symposium on principles and practice of parallel programming, PPOPP 1993

作者： Siegl, Kurt Johannes Kepler University LinzA-4040 Austria

ISBN: (纸本)0897915895

||MAPLE|| (speak: parallel Maple) is a portable system for parallel symbolic computation. the system is built as an interface between the parallel declarative programming language Strand and the sequential computer algebra system Maple, thus providing the elegance of Strand and the power of the existing sequential algorithms in Maple. the implementation of difFerent parallel programming paradigms shows that it is fairly easy to parallelize even complex algebraic algorithms using this system. Sample applications (among them algorithms solving multivariate nonlinear equation systems) are implemented on various parallel architectures. For example a straightforward parallelization of the complex and important problem of real root isolation has been parallelized using a generic Strand program of fewer than 20 Unes of code and a slight modification of 5 lines in the original sequential Maple source. Even with such a simple modification we gained a speed-up of 5 times, that is better than those reported by others in the literature.

关键词： Logic programming

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POSTER: RadiK: Scalable Radix Top-K Selection on GPUs 24

POSTER: RadiK: Scalable Radix Top-K Selection on GPUs

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29th acm sigplan Annual symposium on principles and practice of parallel programming (PPoPP)

作者： Li, Yifei Zhou, Bole Zhang, Jiejing Wei, Xuechao Li, Yinghan Chen, Yingda Alibaba Grp Hangzhou Peoples R China

ISBN: (纸本)9798400704352

By identifying the.. largest or smallest elements in a set of data, top-k selection is critical for modern high-performance databases and machine learning systems, especially with large data volumes. However, previous studies on its GPU implementation are mostly merge-based and rely heavily on the high-speed but size-limited on-chip memory, thereby resulting in a restricted upper bound on... this paper introduces RadiK, a highly optimized GPU-parallel radix top-k selection that is scalable with.., input length, and batch size. With a carefully designed optimization framework targeting high memory bandwidth and resource utilization, RadiK supports far larger.. than the prior art, achieving up to 2.5x speedup for non-batch queries and up to 4.8x speedup for batch queries. We also propose a lightweight refinement that strengthens the robustness of RadiK against skewed distributions by adaptively scaling the input elements.

关键词： Top-K Radix Select GPU-parallel Algorithm

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