现代gpgpu上模板代码的性能极限研究

Ilya S. Pershin, V. Levchenko, A. Perepelkina
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引用次数: 6

摘要

我们研究了不同算法方法在求解一个具有交叉模板格式的波动方程解样题中的性能限制。因此,我们的目标是找到可实现的模板计算性能效率的最高极限。为了估计极限,我们使用定量的rooline模型对性能瓶颈进行彻底分析,并进一步开发模型以考虑不同级别GPU内存的延迟。这些估计提供了使用空间和时间阻塞算法的动机。因此,我们依次研究逐步分解、区域分解和晕轮算法的区域分解。对极限的了解激发了优化实现的动机。这导致了对CUDA中的块同步方法的分析,这也在文本中提供。在所有优化之后,我们已经达到了90%的峰值性能,这相当于在一个消费级GPU设备上每秒更新超过1万亿个单元。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Limits Study of Stencil Codes on Modern GPGPUs
We study the performance limits of different algorithmic approaches to the implementation of a sample problem of wave equation solution with a cross stencil scheme. With this, we aim to find the highest limit of the achievable performance efficiency for stencil computing. To estimate the limits, we use a quantitative Roofline model to make a thorough analysis of the performance bottlenecks and develop the model further to account for the latency of different levels of GPU memory.  These estimates provide an incentive to use spatial and temporal blocking algorithms. Thus, we study stepwise, domain decomposition, and domain decomposition with halo algorithms in that order. The knowledge of the limit incites the motivation to optimize the implementation. This led to the analysis of the block synchronization methods in CUDA, which is also provided in the text.  After all optimizations, we have achieved 90% of the peak performance, which amounts to more than 1 trillion cell updates per second on one consumer level GPU device.
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