优化矩阵乘法的缓存友好策略

2017 IEEE 7th International Advance Computing Conference (IACC) Pub Date : 1900-01-01 DOI:10.1109/IACC.2017.0020

M. Ananth, S. Vishwas, M. R. Anala

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引用次数: 3

摘要

矩阵乘法是许多算法中使用的一种操作，其应用范围从图像处理、信号处理到人工神经网络和线性代数。这项工作旨在展示开发矩阵乘法策略的效果，通过有效地处理内存访问来减少时间和处理器密集型。本文还谈到了使用OpenMP的优点，OpenMP是一个多处理工具包，用于显示并行化矩阵乘法的效果。

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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Cache Friendly Strategies to Optimize Matrix Multiplication

Matrix multiplication is an operation used in many algorithms with a plethora of applications ranging from Image Processing, Signal Processing, to Artificial Neural Networks and Linear algebra. This work aims to showcase the effect of developing matrix multiplication strategies that are less time and processor intensive by effectively handling memory accesses. The paper also touches upon on the advantages of using OpenMP, a multiprocessing toolkit to show the effect of parallelizing matrix multiplication.

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2017 IEEE 7th International Advance Computing Conference (IACC)

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