SAOU

Hadi Zamani, Devashree Tripathy, L. Bhuyan, Zizhong Chen
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引用次数: 12

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SAOU
The current trend of ever-increasing performance in scientific applications comes with tremendous growth in energy consumption. In this paper, we present a framework for GPU applications, which reduces energy consumption in GPUs through Safe Overclocking and Undervolting (SAOU) without sacrificing performance. The idea is to increase the frequency beyond the safe frequency fsa f eMax and undervolt below Vsa f eMin to get maximum energy saving. Since such overclocking and undervolting may give rise to faults, we employ an enhanced checkpoint-recovery technique to cover the possible errors. Empirically, we explore different errors and derive a fault model that can set the undervolting and overclocking level for maximum energy saving. We target cuBLAS Matrix Multiplication (cuBLAS-MM) kernel for error correction using the checkpoint and recovery (CR) technique as an example of scientific applications. In case of cuBLAS, SAOU achieves up to 22% energy reduction through undervolting and overclocking without sacrificing the performance.
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