H-BFT: A fast Breadth-First Traversal algorithm for Sparse graphs and its GPU implementation

Dinali R. Dabarera, Himesh Karunarathna, Erandika Harshani, R. Ragel
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Abstract

With Moore's law in effect, as the complexity of digital electronic circuits increases, the amount of time spent by the electronic design automation (EDA) tools to design such circuits also increases. It brings us to the point, where we need to improve the performance of EDA algorithms to fulfil the present and the future requirements of the EDA industry. Out of many algorithms used by these tools, Breadth First Traversal (BFT) is one of the most commonly used algorithms to traverse the gates of electronic circuits. In this paper, we present a new simple, fast and parallelizable BFT algorithm for sparse graphs, named H-BFT. We show that the CPU implementation of H-BFT is about 75× faster than the CPU implementation of the state of the art, the Sparse Matrix-Vector Product (SMVP) based BFT. Further, with the new features introduced by NVIDIA in their GPUs, we have accelerated both the state of the art SMVP based BFT implementation and our new H-BFT implementation. The best speedups we achieved via these accelerations are 180× and 25× for the SMVP-BFT and H-BFT respectively.
H-BFT:稀疏图的快速宽度优先遍历算法及其GPU实现
随着摩尔定律的生效,随着数字电子电路复杂性的增加,电子设计自动化(EDA)工具用于设计此类电路的时间也在增加。这让我们想到,我们需要改进EDA算法的性能,以满足EDA行业当前和未来的需求。在这些工具使用的许多算法中,宽度优先遍历(BFT)是最常用的遍历电子电路门的算法之一。本文提出了一种新的简单、快速、可并行化的稀疏图BFT算法——H-BFT。我们证明了H-BFT的CPU实现比基于稀疏矩阵向量积(SMVP)的BFT的CPU实现速度快75倍。此外,随着NVIDIA在其gpu中引入的新功能,我们加速了最先进的基于SMVP的BFT实现和我们新的H-BFT实现。SMVP-BFT和H-BFT的最佳加速分别为180倍和25倍。
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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