用于在云分辨分辨率下运行的能量百亿亿次地球系统模型的性能便携式非流体静力大气Dycore。

Luca Bertagna, O. Guba, M. Taylor, J. Foucar, J. Larkin, A. Bradley, S. Rajamanickam, A. Salinger
{"title":"用于在云分辨分辨率下运行的能量百亿亿次地球系统模型的性能便携式非流体静力大气Dycore。","authors":"Luca Bertagna, O. Guba, M. Taylor, J. Foucar, J. Larkin, A. Bradley, S. Rajamanickam, A. Salinger","doi":"10.1109/SC41405.2020.00096","DOIUrl":null,"url":null,"abstract":"We present an effort to port the nonhydrostatic atmosphere dynamical core of the Energy Exascale Earth System Model (E3SM) to efficiently run on a variety of architectures, including conventional CPU, many-core CPU, and GPU. We specifically target cloud-resolving resolutions of 3 km and 1 km. To express on-node parallelism we use the C++ library Kokkos, which allows us to achieve a performance portable code in a largely architecture-independent way. Our C++ implementation is at least as fast as the original Fortran implementation on IBM Power9 and Intel Knights Landing processors, proving that the code refactor did not compromise the efficiency on CPU architectures. On the other hand, when using the GPUs, our implementation is able to achieve 0.97 Simulated Years Per Day, running on the full Summit supercomputer. To the best of our knowledge, this is the most achieved to date by any global atmosphere dynamical core running at such resolutions.","PeriodicalId":424429,"journal":{"name":"SC20: International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"A Performance-Portable Nonhydrostatic Atmospheric Dycore for the Energy Exascale Earth System Model Running at Cloud-Resolving Resolutions.\",\"authors\":\"Luca Bertagna, O. Guba, M. Taylor, J. Foucar, J. Larkin, A. Bradley, S. Rajamanickam, A. Salinger\",\"doi\":\"10.1109/SC41405.2020.00096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present an effort to port the nonhydrostatic atmosphere dynamical core of the Energy Exascale Earth System Model (E3SM) to efficiently run on a variety of architectures, including conventional CPU, many-core CPU, and GPU. We specifically target cloud-resolving resolutions of 3 km and 1 km. To express on-node parallelism we use the C++ library Kokkos, which allows us to achieve a performance portable code in a largely architecture-independent way. Our C++ implementation is at least as fast as the original Fortran implementation on IBM Power9 and Intel Knights Landing processors, proving that the code refactor did not compromise the efficiency on CPU architectures. On the other hand, when using the GPUs, our implementation is able to achieve 0.97 Simulated Years Per Day, running on the full Summit supercomputer. To the best of our knowledge, this is the most achieved to date by any global atmosphere dynamical core running at such resolutions.\",\"PeriodicalId\":424429,\"journal\":{\"name\":\"SC20: International Conference for High Performance Computing, Networking, Storage and Analysis\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SC20: International Conference for High Performance Computing, Networking, Storage and Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SC41405.2020.00096\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SC20: International Conference for High Performance Computing, Networking, Storage and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SC41405.2020.00096","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

我们提出了一项努力,将Energy Exascale地球系统模型(E3SM)的非流体静力大气动力核心移植到各种架构上,包括传统CPU,多核CPU和GPU。我们特别针对3公里和1公里的云分辨分辨率。为了表达节点上的并行性,我们使用c++库Kokkos,它允许我们以一种很大程度上与体系结构无关的方式实现性能可移植代码。我们的c++实现至少与IBM Power9和Intel Knights Landing处理器上的原始Fortran实现一样快,这证明代码重构不会影响CPU架构的效率。另一方面,当使用gpu时,我们的实现能够在完整的Summit超级计算机上运行,达到0.97模拟年/天。据我们所知,这是迄今为止以这种分辨率运行的任何全球大气动力核心所取得的最大成就。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Performance-Portable Nonhydrostatic Atmospheric Dycore for the Energy Exascale Earth System Model Running at Cloud-Resolving Resolutions.
We present an effort to port the nonhydrostatic atmosphere dynamical core of the Energy Exascale Earth System Model (E3SM) to efficiently run on a variety of architectures, including conventional CPU, many-core CPU, and GPU. We specifically target cloud-resolving resolutions of 3 km and 1 km. To express on-node parallelism we use the C++ library Kokkos, which allows us to achieve a performance portable code in a largely architecture-independent way. Our C++ implementation is at least as fast as the original Fortran implementation on IBM Power9 and Intel Knights Landing processors, proving that the code refactor did not compromise the efficiency on CPU architectures. On the other hand, when using the GPUs, our implementation is able to achieve 0.97 Simulated Years Per Day, running on the full Summit supercomputer. To the best of our knowledge, this is the most achieved to date by any global atmosphere dynamical core running at such resolutions.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信