首页|Towards High-Performance Graph Processing:From a Hardware/Software Co-Design Perspective
Towards High-Performance Graph Processing:From a Hardware/Software Co-Design Perspective
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Graph processing has been widely used in many scenarios,from scientific computing to artificial intelligence.Graph processing exhibits irregular computational parallelism and random memory accesses,unlike traditional workloads.Therefore,running graph processing workloads on conventional architectures(e.g.,CPUs and GPUs)often shows a signifi-cantly low compute-memory ratio with few performance benefits,which can be,in many cases,even slower than a special-ized single-thread graph algorithm.While domain-specific hardware designs are essential for graph processing,it is still challenging to transform the hardware capability to performance boost without coupled software codesigns.This article presents a graph processing ecosystem from hardware to software.We start by introducing a series of hardware accelera-tors as the foundation of this ecosystem.Subsequently,the codesigned parallel graph systems and their distributed tech-niques are presented to support graph applications.Finally,we introduce our efforts on novel graph applications and hard-ware architectures.Extensive results show that various graph applications can be efficiently accelerated in this graph pro-cessing ecosystem.
National Engineering Research Center for Big Data Technology and System,School of Computer Science and Technology Huazhong University of Science and Technology,Wuhan 430074,China
Services Computing Technology and System Laboratory,School of Computer Science and Technology Huazhong University of Science and Technology,Wuhan 430074,China
Cluster and Grid Computing Laboratory,School of Computer Science and Technology,Huazhong University of Science and Technology,Wuhan 430074,China
Zhejiang Lab,Hangzhou 311121
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National Key Research and Development Program of China
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