可扩展至数十万核的全隐式时空耦合并行区域分解算法研究

项目名称： 可扩展至数十万核的全隐式时空耦合并行区域分解算法研究

项目编号： No.91330111

项目类型： 重大研究计划

立项/批准年度： 2014

项目学科： 数理科学和化学

项目作者： 蔡小川

作者单位： 中国科学院深圳先进技术研究院

项目金额： 70万元

中文摘要： 由于千万亿次级超级计算机具有庞大的系统规模和复杂的体系结构，传统的并行算法和预条件子技术难以直接移植并实现较高的可扩展性，加强面向千万亿次科学计算的基础研究，特别是可扩展算法和应用软件实现技术的研究，成为高性能计算领域急需突破的瓶颈。本项目拟针对计算流体力学中最典型也是最难的一类应用——流体控制问题，结合全隐式的时空并行算法、区域分解算法和全耦合的Newton-Krylov类方法，兼顾并行数值算法的创新和适应异构、众核环境的并行程序设计和优化技术，进行面向千万亿次超级计算机的大规模可扩展算法研究；力争在以天河、星云等为代表的国产千万亿次超级计算机上，高效实现数十万核的可扩展性以及数百亿未知数规模以上的大规模数值模拟，为面向千万亿次科学计算的可扩展算法和应用软件实现技术提供思路，努力推动国产超级计算机的应用。

中文关键词： 时空耦合算法；区域分解算法；并行算法；计算流体力学；流体控制

英文摘要： Petascale supercomputers are extremely powerful, and the architecture is so complex that traditional parallel algorithms cannot be straightforwardly implemented with such a high level of scalability. The scalability issue is becoming a bottleneck in high performance computing, and this makes the study of highly scalable algorithms and the corresponding software a very important task. In the proposed project, we plan to investigate a class of important applications, namely the control of fluid flows using some fully implicit, coupled space-time domain decomposition algorithms, as well as the nonlinear Newton-Krylov solver. The coupled space-time approach provides more much parallelism than the standard space-only domain decomposition methods, and is therefore more suitable for supercomputers with a very large number of heterogeneous processors. We will develop several critical algorithms and software for the target application problems and study their performance on machines including the current Tianhe and Xingyun with 10,000-100,000 processor-cores. The work will provide valuable experiences for the future development of scalable algorithms and software on petascale, or even exascale, computers and their applications in China.

英文关键词： space-time method；domain decomposition method；parallel algorithm；computational fluid dynamics；fluid control