在Intel GPU上评估整数和约简的性能

Zheming Jin, J. Vetter
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摘要

和约简是并行计算中的基本运算,而SYCL是一种很有前途的异构编程语言。在本文中,我们描述了使用原子函数、共享本地内存、向量化内存访问和参数化工作负载大小的整数和约简的SYCL实现。对约简内核的评估表明,在英特尔集成GPU上,对于足够大的整数,我们可以实现比开源实现的和约简提高1.4倍的速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating the Performance of Integer Sum Reduction on an Intel GPU
Sum reduction is a primitive operation in parallel computing while SYCL is a promising heterogeneous programming language. In this paper, we describe the SYCL implementations of integer sum reduction using atomic functions, shared local memory, vectorized memory accesses, and parameterized workload sizes. Evaluating the reduction kernels shows that we can achieve 1.4X speedup over the open-source implementations of sum reduction for a sufficiently large number of integers on an Intel integrated GPU.
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