Analysis of the Performance of the Matrix Multiplication Algorithm on the Cirrus Supercomputer

Temitayo Adefemi
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Abstract

Matrix multiplication is integral to various scientific and engineering disciplines, including machine learning, image processing, and gaming. With the increasing data volumes in areas like machine learning, the demand for efficient parallel processing of large matrices has grown significantly.This study explores the performance of both serial and parallel matrix multiplication on the Cirrus supercomputer at the University of Edinburgh. The results demonstrate the scalability and efficiency of these methods, providing insights for optimizing matrixmultiplication in real-world applications.
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Cirrus 超级计算机上的矩阵乘法算法性能分析
矩阵乘法是机器学习、图像处理和游戏等各种科学和工程学科不可或缺的一部分。本研究探讨了爱丁堡大学 Cirrus 超级计算机上串行和并行矩阵乘法的性能。研究结果证明了这些方法的可扩展性和效率,为优化实际应用中的矩阵乘法提供了启示。
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