• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2026, Vol. 48 ›› Issue (4): 571-579.

• 建院60周年特邀———前瞻评述 • 上一篇    下一篇

超智融合高性能计算技术发展探讨

卢锡城,杨博,刘杰,黄立波,陈新海   

  1. (1.国防科技大学计算机学院,湖南 长沙 410073;
    2.国防科技大学并行与分布计算全国重点实验室,湖南 长沙 410073)

  • 收稿日期:2026-01-22 修回日期:2026-03-23 出版日期:2026-04-25 发布日期:2026-04-29
  • 基金资助:
    国家重点研发计划(2025YFB3003100)

Discussion on the development of HPC-AI converged high performance computing technologies

LU Xicheng,YANG Bo,LIU Jie,HUANG Libo,CHEN Xinhai   

  1. (1.College of Computer Science and Technology,National University of Defense Technology,Changsha 410073;
    2.National Key Laboratory of Parallel and Distributed Computing,National University of Defense Technology,Changsha 410073,China)

  • Received:2026-01-22 Revised:2026-03-23 Online:2026-04-25 Published:2026-04-29
  • Supported by:


摘要:

高性能计算(HPC)技术演进始终与国防军事、基础科学及产业工程等领域的战略需求紧密交织,其发展历程大致可划分为专用向量机、大规模并行计算机、异构并行计算机和超智融合计算机4个关键阶段,各阶段在体系结构、软件生态和应用模式上不断演进。当前,高性能计算正经历一场由人工智能驱动的深刻范式转移,“AI for Science”成为一种新型科学研究范式,科学计算的高性能、高精度与智能计算的高性能、混合精度特征呈现出深度融合态势,对底层计算架构在精度协同、数据交换以及I/O模式适配等方面提出了严峻挑战。展望未来基于超智融合的高性能计算技术发展,竞争焦点正从单一的浮点峰值性能,转向数据搬移效率、能效比以及系统可扩展性的综合考量。计算单元间更紧密的集成、更高效的数据流动以及更统一的编程抽象,将成为下一代高性能计算系统的关键特征。CPU-SIMT融合计算架构作为一种有前景的超智融合计算体系结构,采用的“融合计算架构+层次化互连网络+融合并行存储”方案,有望突破超智融合紧耦合计算应用的“通信墙”瓶颈,为构建下一代高性能计算系统提供新的技术路径,高效支撑新型“AI for Science”计算范式应用。



关键词: 高性能计算, AI for Science, CPU-SIMT融合计算架构

Abstract: The technological evolution of high-performance computing (HPC) has always been closely intertwined with the strategic demands in fields such as national defense and military affairs,fundamental science,and industrial engineering.Its development can be broadly divided into 4 key stages: dedicated vector machine, massively parallel computer, heterogeneous parallel computer, and HPC-AI converged computer.Each stage continuously advances in system architecture,software ecosystems,and application paradigms.Currently,HPC is undergoing a profound paradigm shift driven by artificial intelligence.“AI for Science” has emerged as a new scientific research paradigm,in which the high-performance with high-precision for scientific computing and high-performance with mixed-precision  characteristics for intelligent computing are converging deeply.This convergence poses formidable challenges to underlying computing architectures in terms of precision coordination,data exchange,and I/O pattern adaptation.Looking ahead to the development of HPC-AI  converged HPC technologies,the competitive focus is shifting from single floating-point peak performance toward a comprehensive consideration of data movement efficiency,energy-performance ratio,and system scalability.Tighter integration among computing units,more efficient data flow,and more unified programming abstractions will become crucial features of next-generation HPC systems.The CPU-SIMT converged computing architecture,as a promising HPC-AI converged computing architecture, employs a solution combining “converged computing architecture+hierarchical interconnection networks+converged parallel storage”. This solution is expected to break through the “communication wall” bottleneck in tightly coupled HPC-AI converged computing applications,offering a new technological pathway for building next-generation HPC systems and efficiently supporting applications under the emerging  “AI for Science” computing paradigm.


Key words: high performance computing(HPC), AI for Science, CPU-SIMT fused computing architecture