Implementing Basic Computational Kernels of Linear Algebra on Multicore

Panagiotis D. Michailidis, K. Margaritis
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引用次数: 3

Abstract

This paper implements basic computational kernels of the scientific computing such as matrix - vector product, matrix product and Gaussian elimination on multi-core platforms using several parallel programming tools. Specifically, these tools are Pthreads, OpenMP, Intel Cilk++, Intel TBB, Intel ArBB, SMPSs, SWARM and Fast Flow. The aim of this paper is to present an unified quantitative and qualitative study of these tools for parallel computation of scientific computing kernels on multicore. Finally, based on this study we conclude that the Intel ArBB and SWARM parallel programming tools are the most appropriate because these give good performance and simplicity of programming.
在多核上实现线性代数基本计算核
本文利用几种并行编程工具,在多核平台上实现了科学计算的基本计算核心——矩阵向量积、矩阵乘积、高斯消去等。具体来说,这些工具是Pthreads、OpenMP、Intel cilk++、Intel TBB、Intel ArBB、smps、SWARM和Fast Flow。本文的目的是对这些科学计算内核的多核并行计算工具进行统一的定量和定性研究。最后,基于本研究,我们得出结论,英特尔ArBB和SWARM并行编程工具是最合适的,因为它们具有良好的性能和编程简单性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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