摘要
随着异构融合体系结构在高性能计算领域的普及,挖掘其潜能并探索新的应用构建策略变得至关重要.传统的静态编译方法已无法满足复杂计算需求,动态编程语言因其灵活性和高效性而备受瞩目.Julia是一种现代的高性能动态编程语言,其基于即时编译机制,在科学计算等领域表现出色.结合申威异构众核架构特点,构建ORCJIT编译引擎并提出了动态模式下的片上存储管理方法,并以此为基础实现针对新一代神威超级计算机的Julia动态语言编译器swJulia.其不仅继承了Julia编译器的灵活性,同时还有效支持了SACA众核编程模型及运行时封装.利用swJulia编译系统,成功在新一代神威超级计算机上部署了NNQS-Transformer量子化学模拟器,并在多个维度验证了swJulia的好用性和高效性.实验结果显示,swJulia在单线程基准测试和众核加速上性能卓越,并能够有效支撑NNQS-Transformer量子化学模拟器的超大规模可扩展并行模拟.
With the increasing adoption of heterogeneous integrated architectures in high-performance computing,it has become essential to harness their potential and explore new strategies for application development.Traditional static compilation methodologies are no longer sufficient to meet the complex computational demands.Therefore,dynamic programming languages,known for their flexibility and efficiency,are gaining prominence.Julia,a modern high-performance language characterized by its JIT compilation mechanism,has demonstrated significant performance in fields such as scientific computing.Targeting the unique features of the Sunway heterogeneous many-core architecture,the ORCJIT engine is introduced,along with an on-chip storage management approach specifically designed for dynamic modes.Based on these advancements,swJulia is developed as a Julia dynamic language compiler tailored for the new generation of the Sunway supercomputer.This compiler not only inherits the flexibility of the Julia compiler but also provides robust support for the SACA many-core programming model and runtime encapsulation.By utilizing the swJulia compilation system,the deployment of the NNQS-Transformer quantum chemistry simulator on the new generation of the Sunway supercomputer is successfully achieved.Comprehensive validation across multiple dimensions demonstrates the efficacy and efficiency of swJulia.Experimental results show exceptional performance in single-threaded benchmark tests and many-core acceleration,significantly improving ultra-large-scale parallel simulations for the NNQS-Transformer quantum chemistry simulator.
作者
沈莉
周文浩
王飞
李斌
谭坚
商红慧
安虹
漆锋滨
SHEN Li;ZHOU Wen-Hao;WANG Fei;LI Bin;TAN Jian;SHANG Hong-Hui;AN Hong;QI Feng-Bin(University of Science and Technology of China,Hefei 230026,China;Jiangnan Institute of Computing Technology,Wuxi 214083,China;Tsinghua University,Beijing 100084,China)
出处
《软件学报》
北大核心
2025年第12期5402-5422,共21页
Journal of Software
基金
国家重点研发计划(2023YFB3001500)。
