Speculative Execution on GPU: An Exploratory Study

Shaoshan Liu, C. Eisenbeis, J. Gaudiot
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引用次数: 25

Abstract

We explore the possibility of using GPUs for speculative execution: we implement software value prediction techniques to accelerate programs with limited parallelism, and software speculation techniques to accelerate programs that contain runtime parallelism, which are hard to parallelize statically. Our experiment results show that due to the relatively high overhead, mapping software value prediction techniques on existing GPUs may not bring any immediate performance gain. On the other hand, although software speculation techniques introduce some overhead as well, mapping these techniques to existing GPUs can already bring some performance gain over CPU.
GPU的投机执行:探索性研究
我们探索了使用gpu进行推测执行的可能性:我们实现了软件值预测技术来加速具有有限并行性的程序,以及软件推测技术来加速包含运行时并行性的程序,这些程序很难静态并行化。我们的实验结果表明,由于相对较高的开销,在现有gpu上映射软件值预测技术可能不会带来任何直接的性能提升。另一方面,尽管软件推测技术也引入了一些开销,但将这些技术映射到现有的gpu上已经可以带来一些优于CPU的性能增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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