超智融合高性能计算技术发展探讨OA

The technological evolution of high-performance computing(HPC)has always been close-ly intertwined with the strategic demands in fields such as national defense and military affairs,funda-mental 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 intel-ligence."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 under-lying computing architectures in terms of precision coordination,data exchange,and I/O pattern adapta-tion.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 move-ment 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 archi-tecture+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 effi-ciently supporting applications under the emerging"AI for Science"computing paradigm.