Computer Science ›› 2020, Vol. 47 ›› Issue (8): 5-16.doi: 10.11896/jsjkx.200600045


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Survey of Heterogeneous Hybrid Parallel Computing

YANG Wang-dong, WANG Hao-tian, ZHANG Yu-feng, LIN Sheng-le , CAI Qin-yun   

  1. College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China
  • Online:2020-08-15 Published:2020-08-10
  • Supported by:
    This word was supported by the National Key R&D Program of China (2019YFB2103004) and National Natural Science Foundation of China (61872127).

Abstract: With the rapid increase in computing power demand of computer applications such as artificial intelligence and big data and the diversification of application scenarios, the research of heterogeneous hybrid parallel computing has become the focus of research.This paper introduces the current main heterogeneous computer architecture, including CPU/coprocessor, CPU/many-core processor, CPU/ASCI and CPU/FPGA heterogeneous architectures.The changes made by the heterogeneous hybrid parallel programming model with the development of various heterogeneous hybrid structures are briefly described, which is a transformation and re-implementation of an existing language, or an extension of an existing heterogeneous programming language, or heterogeneous programming using instructional statements, or container pattern collaborative programming.The analysis shows that the heterogeneous hybrid parallel computing architecture will further strengthen the support for AI, and will also enhance the versatility of the software.This paper reviewes the key technologies in heterogeneous hybrid parallel computing, including parallel task partitioning, task mapping, data communication, data access between heterogeneous processors, parallel synchronization of heterogeneous collaboration, and pipeline parallelism of heterogeneous resources.Based on these key technologies, this paper points out the challenges faced by heterogeneous hybrid parallel computing, such as programming difficulties, portability difficulties, large data communication overhead, complex data access, complex parallel control, and uneven resource load.The challenges faced by heterogeneous hybrid parallel computing are analyzed, and this paper concludes that the current key core technologies need to be integrated from general-purpose and AI-specific heterogeneous computing, seamless migration of heterogeneous architectures, unified programming model, integration of storage and computing, and intelligence breakthroughs in task division and allocation

Key words: Heterogeneous architecture, Heterogeneous computing, Heterogeneous hybrid programming, Heterogeneous parallel programming, Parallel computing

CLC Number: 

  • TP301
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YANG Wang-dong, doctor, professor.His main research interests include high performance computing and parallel computing.
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