Gunrock: A High-Performance Graph Processing Library on the GPU

For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and the complexity of programming GPUs have been two significant challenges for developing a programmable high-performance graph library. "Gunrock", our graph-processing system designed specifical...

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Bibliographic Details
Published in:arXiv.org 2016-02
Main Authors: Wang, Yangzihao, Davidson, Andrew, Pan, Yuechao, Wu, Yuduo, Riffel, Andy, Owens, John D
Format: Article
Language:English
Subjects:
Access control
Graphics processing units
Level (quantity)
Libraries
Optimization
Programming
Online Access:Get full text
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Summary:For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and the complexity of programming GPUs have been two significant challenges for developing a programmable high-performance graph library. "Gunrock", our graph-processing system designed specifically for the GPU, uses a high-level, bulk-synchronous, data-centric abstraction focused on operations on a vertex or edge frontier. Gunrock achieves a balance between performance and expressiveness by coupling high performance GPU computing primitives and optimization strategies with a high-level programming model that allows programmers to quickly develop new graph primitives with small code size and minimal GPU programming knowledge. We evaluate Gunrock on five key graph primitives and show that Gunrock has on average at least an order of magnitude speedup over Boost and PowerGraph, comparable performance to the fastest GPU hardwired primitives, and better performance than any other GPU high-level graph library.
ISSN:2331-8422
DOI:10.48550/arxiv.1501.05387