计算机科学 ›› 2013, Vol. 40 ›› Issue (3): 107-110.

• 2012多值逻辑专栏 • 上一篇    下一篇

单节点多GPU集群下HPL动态负载均衡优化

陈任之,黄立波,陈顼颢,王志英   

  1. (国防科学技术大学计算机学院 长沙410073)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Optimizing HPL Benchmark on Multi-GPU Clusters

  • Online:2018-11-16 Published:2018-11-16

摘要: 现有CPU加速的高性能Linpack基准测试程序(HPL)一般采用基于实际运算能力的动态负载均衡算法来实现。然而该算法在单节点多GPU的平台上表现不佳,其原因是单节点多GPU平台上单个GPU计算量小,并且GPU与CPU的总性能差距较大。为此,提出了经验指导的动态负载均衡算法以及多GPU自适应负载均衡算法,并且在单节点多GPU平台上进行了验证,结果显示,其比现有的基于NVIDIA费米GPU的HPI有6.3%的加速效果。

关键词: HPL,GPU,动态负载均衡算法

Abstract: The current high performance Linpack benchmark accelerated by GPU usually employs the performance-based dynamic load balancing algorism. However, this algorism does not perform well on multi-GPU cluster. The reason is that each GPU on this kind of node has a smaller calculating scale, and the gap of the total performance between GPU and CPU is larger. Therefore, this article proposed an experience-based dynamic load balancing algorism and a multi-GPU adaptive load balance algorithm. Besides, the article tested these two algorisms on multi-GPU cluster and it achieves a 6.3% acceleration compared with the latest NV)DIA's HPL accelerated by GPU.

Key words: HPL, GPU, Dynamic load balancing algorithm

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