Sapporo2:一个通用的直接n体库

Jeroen Bédorf, Evghenii Gaburov, Simon Portegies Zwart
{"title":"Sapporo2:一个通用的直接n体库","authors":"Jeroen Bédorf,&nbsp;Evghenii Gaburov,&nbsp;Simon Portegies Zwart","doi":"10.1186/s40668-015-0012-z","DOIUrl":null,"url":null,"abstract":"<p>Astrophysical direct <i>N</i>-body methods have been one of the first production algorithms to be implemented using NVIDIA’s <span>CUDA</span> architecture. Now, almost seven years later, the GPU is the most used accelerator device in astronomy for simulating stellar systems. In this paper we present the implementation of the <span>Sapporo2</span>\n\t\t\t\t <i>N</i>-body library, which allows researchers to use the GPU for <i>N</i>-body simulations with little to no effort. The first version, released five years ago, is actively used, but lacks advanced features and versatility in numerical precision and support for higher order integrators. In this updated version we have rebuilt the code from scratch and added support for <span>OpenCL</span>, multi-precision and higher order integrators. We show how to tune these codes for different GPU architectures and present how to continue utilizing the GPU optimal even when only a small number of particles (<span>\\(N &lt; 100\\)</span>) is integrated. This careful tuning allows <span>Sapporo2</span> to be faster than <span>Sapporo1</span> even with the added options and double precision data loads. The code runs on a range of NVIDIA and AMD GPUs in single and double precision accuracy. With the addition of <span>OpenCL</span> support the library is also able to run on CPUs and other accelerators that support <span>OpenCL</span>.</p>","PeriodicalId":523,"journal":{"name":"Computational Astrophysics and Cosmology","volume":"2 1","pages":""},"PeriodicalIF":16.2810,"publicationDate":"2015-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40668-015-0012-z","citationCount":"7","resultStr":"{\"title\":\"Sapporo2: a versatile direct N-body library\",\"authors\":\"Jeroen Bédorf,&nbsp;Evghenii Gaburov,&nbsp;Simon Portegies Zwart\",\"doi\":\"10.1186/s40668-015-0012-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Astrophysical direct <i>N</i>-body methods have been one of the first production algorithms to be implemented using NVIDIA’s <span>CUDA</span> architecture. Now, almost seven years later, the GPU is the most used accelerator device in astronomy for simulating stellar systems. In this paper we present the implementation of the <span>Sapporo2</span>\\n\\t\\t\\t\\t <i>N</i>-body library, which allows researchers to use the GPU for <i>N</i>-body simulations with little to no effort. The first version, released five years ago, is actively used, but lacks advanced features and versatility in numerical precision and support for higher order integrators. In this updated version we have rebuilt the code from scratch and added support for <span>OpenCL</span>, multi-precision and higher order integrators. We show how to tune these codes for different GPU architectures and present how to continue utilizing the GPU optimal even when only a small number of particles (<span>\\\\(N &lt; 100\\\\)</span>) is integrated. This careful tuning allows <span>Sapporo2</span> to be faster than <span>Sapporo1</span> even with the added options and double precision data loads. The code runs on a range of NVIDIA and AMD GPUs in single and double precision accuracy. With the addition of <span>OpenCL</span> support the library is also able to run on CPUs and other accelerators that support <span>OpenCL</span>.</p>\",\"PeriodicalId\":523,\"journal\":{\"name\":\"Computational Astrophysics and Cosmology\",\"volume\":\"2 1\",\"pages\":\"\"},\"PeriodicalIF\":16.2810,\"publicationDate\":\"2015-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1186/s40668-015-0012-z\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Astrophysics and Cosmology\",\"FirstCategoryId\":\"4\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s40668-015-0012-z\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Astrophysics and Cosmology","FirstCategoryId":"4","ListUrlMain":"https://link.springer.com/article/10.1186/s40668-015-0012-z","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

天体物理直接n体方法是使用NVIDIA CUDA架构实现的首批生产算法之一。现在,差不多七年过去了,GPU是天文学中用于模拟恒星系统的最常用的加速器设备。在本文中,我们提出了Sapporo2 N-body库的实现,它允许研究人员使用GPU进行N-body模拟,几乎不需要任何努力。5年前发布的第一个版本被积极使用,但在数值精度和支持高阶积分器方面缺乏先进的功能和多功能性。在这个更新版本中,我们从头开始重新构建了代码,并添加了对OpenCL、多精度和高阶积分器的支持。我们展示了如何为不同的GPU架构调整这些代码,并展示了如何继续利用GPU优化,即使只有少量粒子(\(N < 100\))被集成。这种精心的调优使得Sapporo2比Sapporo1更快,即使增加了选项和双倍精度的数据加载。该代码在一系列NVIDIA和AMD gpu上运行,具有单精度和双精度。随着OpenCL支持的增加,该库也能够在支持OpenCL的cpu和其他加速器上运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Sapporo2: a versatile direct N-body library

Astrophysical direct N-body methods have been one of the first production algorithms to be implemented using NVIDIA’s CUDA architecture. Now, almost seven years later, the GPU is the most used accelerator device in astronomy for simulating stellar systems. In this paper we present the implementation of the Sapporo2 N-body library, which allows researchers to use the GPU for N-body simulations with little to no effort. The first version, released five years ago, is actively used, but lacks advanced features and versatility in numerical precision and support for higher order integrators. In this updated version we have rebuilt the code from scratch and added support for OpenCL, multi-precision and higher order integrators. We show how to tune these codes for different GPU architectures and present how to continue utilizing the GPU optimal even when only a small number of particles (\(N < 100\)) is integrated. This careful tuning allows Sapporo2 to be faster than Sapporo1 even with the added options and double precision data loads. The code runs on a range of NVIDIA and AMD GPUs in single and double precision accuracy. With the addition of OpenCL support the library is also able to run on CPUs and other accelerators that support OpenCL.

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
期刊介绍: Computational Astrophysics and Cosmology (CompAC) is now closed and no longer accepting submissions. However, we would like to assure you that Springer will maintain an archive of all articles published in CompAC, ensuring their accessibility through SpringerLink's comprehensive search functionality.
期刊最新文献
Machine learning applied to simulations of collisions between rotating, differentiated planets Technologies for supporting high-order geodesic mesh frameworks for computational astrophysics and space sciences Cosmological N-body simulations: a challenge for scalable generative models A detection metric designed for O’Connell effect eclipsing binaries DESTINY: Database for the Effects of STellar encounters on dIsks and plaNetary sYstems
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1