MV-FT: Efficient Implementation for Matrix-Vector Multiplication on FT64 Stream Processor

Jing Du, F. Ao, Xuejun Yang
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引用次数: 3

Abstract

In this paper, we present a detailed case study of the optimizing implementation of a fundamental scientific kernel, matrix-vector multiplication, on FT64, which is the first 64-bit stream processor designed for scientific computing. The major novelties of our study are as follows. First, we develop four stream programs according to different stream organizations, involving dot product, row product, multi-dot product and multi-row product approaches. Second the optimal strip size for partitioning the large matrix is put forward based on a practical parameter model. Finally loop unrolling and software pipelining are used to hide the communications with the computations. The experimental results show that the optimizing implementations on FT64 achieve high speedup over the corresponding Fortran programs running on Itanium 2. It is certain that matrix-vector multiplication can efficiently exploit the tremendous potential of FT64 stream processor through programming optimizations.
MV-FT: FT64流处理器上矩阵-向量乘法的高效实现
在本文中,我们提出了一个详细的案例研究,在FT64上优化实现一个基本的科学内核,矩阵向量乘法,这是第一个为科学计算设计的64位流处理器。我们研究的主要新颖之处如下。首先,我们根据不同的流组织制定了四种流程序,包括点积、行积、多点积和多行积方法。其次,基于实用的参数模型,提出了大矩阵分区的最优条带尺寸。最后利用循环展开和软件流水线来隐藏与计算之间的通信。实验结果表明,在FT64上的优化实现比在Itanium 2上运行的相应Fortran程序获得了较高的加速。可以肯定的是,通过编程优化,矩阵向量乘法可以有效地发挥FT64流处理器的巨大潜力。
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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