Towards dataflow based graph processing  

作　　者：Hai JIN Pengcheng YAO Xiaofei LIAO 

机构地区：[1]Service Computing Technology and System Lab, Cluster and Grid Computing Lab, Big Data Technology and System Lab School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China

出　　处：《Science China(Information Sciences)》2017年第12期270-272,共3页中国科学（信息科学）（英文版）

基　　金：supported by National High Technology Research and Development Program of China(863 Program)(Grant No.2015AA015303)

摘　　要：Modern graph processing is widely used for solving a vast variety of real-world problems,e.g.,web sites ranking[1]and community detection[2].To better adapt and express the procedure of graph iteration,a wide spectrum of research is proposed with highly concurrent programming models and smart strategies of graph partition[1,3].Modern graph processing is widely used for solving a vast variety of real-world problems,e.g.,web sites ranking[1]and community detection[2].To better adapt and express the procedure of graph iteration,a wide spectrum of research is proposed with highly concurrent programming models and smart strategies of graph partition[1,3].

关 键 词：CONCURRENT PARTITION ITERATION RANKING instructions branch ADAPT processor scheduling operations 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP393[自动化与计算机技术—计算机科学与技术]