Big Data Research ›› 2020, Vol. 6 ›› Issue (4): 40-55.doi: 10.11959/j.issn.2096-0271.2020032

• TOPIC:HETEROGENEOUS PARALLEL SYSTEMS FOR BIG DATA • Previous Articles     Next Articles

Research on performance optimization for large-scale sparse computation over many-core heterogenous supercomputer

Zhengding HU,Wei XUE   

  1. Department of Computer Science and Technology,Tsinghua University,Beijing 100084,China
  • Online:2020-07-15 Published:2020-07-18
  • Supported by:
    Science and Technology Project of State Grid Corporation of China(XT71-19-022)

Abstract:

With development of supercomputer technique,it is possible to solve extra-scale sparse problems in big data applications.However,irregular feature in computation and memory access of sparse problems brings challenges to implementation and optimization of applications.Many-core heterogenous architecture is popular in supercomputer design,which advances a higher requirement for application developers.How to utilize its extraordinary computing ability becomes a very difficult problem.Challenges in optimizing sparse computing problems were analyzed,and three cases of implementation and optimization based on typical many-core heterogenous computer system were introduced,which of all achieve very high performance.Experiences in those successful cases were summed up,to better solve extra-scale sparse computing problems on many-core heterogenous system of new generation.

Key words: big data application, sparse problem, high performance computation, performance optimization

CLC Number: 

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