DFG implementation on multi GPU cluster with computation-communication overlap

Sylvain Huet, Vincent Boulos, V. Fristot, L. Salvo
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引用次数: 4

Abstract

Nowadays, it is possible to build a multi-GPU supercomputer, well suited for implementation of digital signal processing algorithms, for a few thousand dollars. However, to achieve the highest performance with this kind of architecture, the programmer has to focus on inter-processor communications, tasks synchronization … In this paper, we propose a design flow allowing an efficient implementation of a Digital Signal Processing (DSP) application specified as a Data Flow Graph (DFG) on a multi GPU computer cluster. We focus particularly on the effective implementation of communications by automating the computation-communication overlap, which can lead to significant speedups as shown in the presented benchmark. The approach is validated on a 3D granulometry application developed for research on materials.
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计算通信重叠的多GPU集群DFG实现
如今,只要几千美元,就可以制造一台多gpu的超级计算机,非常适合实现数字信号处理算法。然而,为了实现这种架构的最高性能,程序员必须关注处理器间通信,任务同步……在本文中,我们提出了一个设计流程,允许在多GPU计算机集群上有效地实现数字信号处理(DSP)应用程序,指定为数据流图(DFG)。我们特别关注通过自动化计算-通信重叠来实现通信的有效实现,这可以带来显着的速度提升,如所提供的基准测试所示。该方法在用于材料研究的3D粒度测量应用程序中得到了验证。
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