文章基本信息

标题：Performance Evaluation and Analysis for Conjugate Gradient Solver on Heterogeneous (Multi-GPUs/Multi-CPUs) platforms
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作者：Najlae Kasmi ; Mostapha Zbakh ; Sidi Ahmed Mahmoudi 等
期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2017
卷号：17
期号：8
页码：206-215
出版社：International Journal of Computer Science and Network Security
摘要：High performance computing (HPC) presents a technology that allows solving high intensive problems in a reasonable period of time, and can offer many advantages for large applications in various fields of science and industry. Current multi-core processors, especially graphic processing units (GPUs), have quickly evolved to become efficient accelerators for data parallel computing. They can maintain parallel programmability and provide high computing throughput. In this paper, the authors present an implementation and performance analysis of sparse iterative linear solver on heterogeneous multi-CPUs/multi-GPUs architectures using PARALUTION and StarPU libraries. More particularly, the authors compare the performance of parallel preconditioned conjugate gradient (PCG) solver on different platforms. Experimental results have been conducted using GPU platforms and show a significant speed up compared to central processing units CPUs implementations. In order to provide the highest performance, the system supports Multi-CPU/Multi-GPU architectures, where it scales up very high.
关键词：HPC; Multi-GPUs/Multi-CPUs architectures; Sparse linear systems; PARALUTION; StarPU