用SYCL标准评价LU矩阵分解的性能

Dmytro Nasikan, V. Yaremenko
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引用次数: 0

摘要

本研究的目的是SYCL标准工具在解决LU矩阵分解问题时的性能。SYCL是用于异构系统中并行计算的一种相当新的技术,因此评估该标准在并行计算领域的特定任务上的性能是相关的。在本研究中,利用SYCL标准和标准C++实现了方矩阵的并行LU分解算法,并在具有几种类型处理器的异构系统中进行了实验测试。在测试期间,程序接收各种维度的方阵作为输入,输出是LU调度在所选处理器上的执行时间。所获得的结果以表格和图形数据的形式显示,在使用图形处理器时,SYCL标准的实现比普通C++的优势提高了2倍以上。实验表明,当在中央处理器上执行时,SYCL上的实现在速度上几乎不亚于普通C++上的实现。这样的结果是由于LU调度算法本身并行化的可能性很高,以及该标准的开发人员在其优化方面所做的大量工作造成的。所获得的结果表明,当使用具有针对数据并行性进行优化的处理器的异构系统时,利用SYCL可以加快矩阵的LU分解和类似算法的求解。研究结果可用于证明解决LU矩阵分解问题或具有类似并行化方案的问题的技术选择的合理性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance evaluation of LU matrix decomposition using the SYCL standard
The object of this study is the performance of the SYCL standard tools when solving the LU matrix decomposition problem. SYCL is a fairly new technology for parallel computing in heterogeneous systems, so the topic of evaluating the performance of the standard on specific tasks in the field of parallel computing is relevant. In the study, the algorithm of parallelized LU decomposition of a square matrix was implemented by means of the SYCL standard and standard C++, and an experiment was conducted to test the implementation in a heterogeneous system with several types of processors. During testing, the program received square matrices of various dimensions as input, and the output was the execution time of the LU schedule on the selected processor. The obtained results, presented in the form of tabular and graphic data, show the advantage of the implementation of the SYCL standard over ordinary C++ by more than 2 times when using a graphics processor. It was experimentally shown that the implementation on SYCL is almost not inferior in speed to the implementation on ordinary C++ when executed on a central processor. Such results are caused both by the high possibility of parallelizing the LU schedule algorithm itself, and by the great work of the developers of the standard on its optimization. The obtained results indicate the possibility of speeding up the solution of the LU decomposition of the matrix and similar algorithms by means of SYCL when using heterogeneous systems with processors optimized for data parallelism. The results of the study can be used in justifying the choice of technology for solving LU matrix decomposition problems or problems with a similar parallelization scheme.
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