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High-Performance Matrix Multiply on a Massively Multithreaded Fiteng1000 Processor

机译:大规模多线程Fiteng1000处理器上的高性能矩阵乘法

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Matrix multiplication is an essential building block of many linear algebra operations and applications. This paper presents parallel algorithms with shared A or B matrix in the memory for the special massively multithreaded Fiteng1000 processor. We discuss the implementations of parallel matrix multiplication algorithms on the multi-core processor with many threads. To gain better performance, it is important to choose the 2D thread spatial topography, the memory layer for the placement and the sizes of the matrices. Parallel codes using C and assembly language under OpenMP parallel programming environment are designed. Performance results on Fiteng1000 processor show that the algorithms have well good parallel performance and achieve near-peak performance.
机译:矩阵乘法是许多线性代数运算和应用的重要组成部分。本文针对特殊的大规模多线程Fiteng1000处理器,提出了在内存中具有共享A或B矩阵的并行算法。我们讨论了多线程多核处理器上并行矩阵乘法算法的实现。为了获得更好的性能,重要的是选择2D线程空间拓扑,用于矩阵放置和大小的存储层。设计了在OpenMP并行编程环境下使用C和汇编语言的并行代码。在Fiteng1000处理器上的性能结果表明,这些算法具有良好的并行性能,并实现了近峰值性能。

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