高阶和基于元组的大规模并行前缀和

Sepideh Maleki, Annie Yang, Martin Burtscher
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引用次数: 16

摘要

前缀和是一个重要的并行原语,特别是在大规模并行程序中。本文讨论了它的两个正交推广,我们称之为高阶和基于元组的前缀和。此外,它还描述并评估了SAM,这是一种gpu友好的算法,用于计算前缀和和其他直接支持高阶和元组值的扫描。它的模板化CUDA实现将所有这些计算统一到一个包含100条语句的内核中。SAM是通信高效的,因为它最小化了对主存的访问。当计算100万或更多值的前缀和时,它在Titan X和K40 GPU上的性能都优于Thrust和CUDPP。在Titan X上,SAM达到了大输入容量的内存复制速度,这是无法超越的。SAM比CUB(目前最快的传统前缀和实现)的性能要好,在八阶前缀和上最多高出2.9倍,在八元组前缀和上最多高出2.6倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Higher-order and tuple-based massively-parallel prefix sums
Prefix sums are an important parallel primitive, especially in massively-parallel programs. This paper discusses two orthogonal generalizations thereof, which we call higher-order and tuple-based prefix sums. Moreover, it describes and evaluates SAM, a GPU-friendly algorithm for computing prefix sums and other scans that directly supports higher orders and tuple values. Its templated CUDA implementation unifies all of these computations in a single 100-statement kernel. SAM is communication-efficient in the sense that it minimizes main-memory accesses. When computing prefix sums of a million or more values, it outperforms Thrust and CUDPP on both a Titan X and a K40 GPU. On the Titan X, SAM reaches memory-copy speeds for large input sizes, which cannot be surpassed. SAM outperforms CUB, the currently fastest conventional prefix sum implementation, by up to a factor of 2.9 on eighth-order prefix sums and by up to a factor of 2.6 on eight-tuple prefix sums.
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