Yifeng Cui, E. Poyraz, K. Olsen, Jun Zhou, K. Withers, S. Callaghan, J. Larkin, C. Guest, D. J. Choi, A. Chourasia, Zheqiang Shi, S. Day, P. Maechling, T. Jordan
{"title":"基于物理的千万亿次异构超级计算机地震危险性分析","authors":"Yifeng Cui, E. Poyraz, K. Olsen, Jun Zhou, K. Withers, S. Callaghan, J. Larkin, C. Guest, D. J. Choi, A. Chourasia, Zheqiang Shi, S. Day, P. Maechling, T. Jordan","doi":"10.1145/2503210.2503300","DOIUrl":null,"url":null,"abstract":"We have developed a highly scalable and efficient GPU-based finite-difference code (AWP) for earthquake simulation that implements high throughput, memory locality, communication reduction and communication / computation overlap and achieves linear scalability on Cray XK7 Titan at ORNL and NCSA's Blue Waters system. We simulate realistic 0-10 Hz earthquake ground motions relevant to building engineering design using high-performance AWP. Moreover, we show that AWP provides a speedup by a factor of 110 in key strain tensor calculations critical to probabilistic seismic hazard analysis (PSHA). These performance improvements to critical scientific application software, coupled with improved co-scheduling capabilities of our workflow-managed systems, make a statewide hazard model a goal reachable with existing supercomputers. The performance improvements of GPU-based AWP are expected to save millions of core-hours over the next few years as physics-based seismic hazard analysis is developed using heterogeneous petascale supercomputers.","PeriodicalId":371074,"journal":{"name":"2013 SC - International Conference for High Performance Computing, Networking, Storage and Analysis (SC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"65","resultStr":"{\"title\":\"Physics-based seismic hazard analysis on petascale heterogeneous supercomputers\",\"authors\":\"Yifeng Cui, E. Poyraz, K. Olsen, Jun Zhou, K. Withers, S. Callaghan, J. Larkin, C. Guest, D. J. Choi, A. Chourasia, Zheqiang Shi, S. Day, P. Maechling, T. Jordan\",\"doi\":\"10.1145/2503210.2503300\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have developed a highly scalable and efficient GPU-based finite-difference code (AWP) for earthquake simulation that implements high throughput, memory locality, communication reduction and communication / computation overlap and achieves linear scalability on Cray XK7 Titan at ORNL and NCSA's Blue Waters system. We simulate realistic 0-10 Hz earthquake ground motions relevant to building engineering design using high-performance AWP. Moreover, we show that AWP provides a speedup by a factor of 110 in key strain tensor calculations critical to probabilistic seismic hazard analysis (PSHA). These performance improvements to critical scientific application software, coupled with improved co-scheduling capabilities of our workflow-managed systems, make a statewide hazard model a goal reachable with existing supercomputers. The performance improvements of GPU-based AWP are expected to save millions of core-hours over the next few years as physics-based seismic hazard analysis is developed using heterogeneous petascale supercomputers.\",\"PeriodicalId\":371074,\"journal\":{\"name\":\"2013 SC - International Conference for High Performance Computing, Networking, Storage and Analysis (SC)\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"65\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 SC - International Conference for High Performance Computing, Networking, Storage and Analysis (SC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2503210.2503300\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 SC - International Conference for High Performance Computing, Networking, Storage and Analysis (SC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2503210.2503300","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Physics-based seismic hazard analysis on petascale heterogeneous supercomputers
We have developed a highly scalable and efficient GPU-based finite-difference code (AWP) for earthquake simulation that implements high throughput, memory locality, communication reduction and communication / computation overlap and achieves linear scalability on Cray XK7 Titan at ORNL and NCSA's Blue Waters system. We simulate realistic 0-10 Hz earthquake ground motions relevant to building engineering design using high-performance AWP. Moreover, we show that AWP provides a speedup by a factor of 110 in key strain tensor calculations critical to probabilistic seismic hazard analysis (PSHA). These performance improvements to critical scientific application software, coupled with improved co-scheduling capabilities of our workflow-managed systems, make a statewide hazard model a goal reachable with existing supercomputers. The performance improvements of GPU-based AWP are expected to save millions of core-hours over the next few years as physics-based seismic hazard analysis is developed using heterogeneous petascale supercomputers.