Towards High-Performance Graph Processing: From a Hardware/Software Co-Design Perspective
作者机构：National Engineering Research Center for Big Data Technology and SystemSchool of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Services Computing Technology and System LaboratorySchool of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Cluster and Grid Computing LaboratorySchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Zhejiang LabHangzhou 311121China
出 版 物：《Journal of Computer Science & Technology》 (计算机科学技术学报（英文版）)
年 卷 期：2024年第39卷第2期
页 面：245-266页
核心收录：
学科分类：07[理学] 0835[工学-软件工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 070101[理学-基础数学]
主 题：graph processing hardware accelerator software system high performance ecosystem
摘 要：Graph processing has been widely used in many scenarios,from scientific computing to artificial *** processing exhibits irregular computational parallelism and random memory accesses,unlike traditional ***,running graph processing workloads on conventional architectures(e.g.,CPUs and GPUs)often shows a significantly low compute-memory ratio with few performance benefits,which can be,in many cases,even slower than a specialized single-thread graph *** domain-specific hardware designs are essential for graph processing,it is still challenging to transform the hardware capability to performance boost without coupled software *** article presents a graph processing ecosystem from hardware to *** start by introducing a series of hardware accelerators as the foundation of this ***,the codesigned parallel graph systems and their distributed techniques are presented to support graph ***,we introduce our efforts on novel graph applications and hardware *** results show that various graph applications can be efficiently accelerated in this graph processing ecosystem.
维普期刊数据库