Tausch:一个halo交换库,用于使用MPI、OpenCL和CUDA的大型异构计算系统

IF 2 4区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS Parallel Computing Pub Date : 2022-12-01 DOI:10.1016/j.parco.2022.102973
Lukas Spies , Amanda Bienz , David Moulton , Luke Olson , Andrew Reisner
{"title":"Tausch:一个halo交换库,用于使用MPI、OpenCL和CUDA的大型异构计算系统","authors":"Lukas Spies ,&nbsp;Amanda Bienz ,&nbsp;David Moulton ,&nbsp;Luke Olson ,&nbsp;Andrew Reisner","doi":"10.1016/j.parco.2022.102973","DOIUrl":null,"url":null,"abstract":"<div><p><span>Exchanging halo data is a common task in modern scientific computing<span><span> applications and efficient handling of this operation is critical for the performance of the overall simulation. Tausch is a novel header-only library that provides a simple API for efficiently handling these types of data movements. Tausch supports both simple CPU-only systems, but also more complex heterogeneous systems with both CPUs and </span>GPUs. It currently supports both </span></span>OpenCL<span> and CUDA for communicating with GPGPU devices, and allows for communication between GPGPUs and CPUs. The API allows for drop-in replacement in existing codes and can be used for the communication layer in new codes. This paper provides an overview of the approach taken in Tausch, and a performance analysis that demonstrates expected and achieved performance. We highlight the ease of use and performance with three applications: First Tausch is compared to the halo exchange framework from two Mantevo applications, HPCCG and miniFE, and then it is used to replace a legacy halo exchange library in the flexible multigrid solver framework Cedar.</span></p></div>","PeriodicalId":54642,"journal":{"name":"Parallel Computing","volume":"114 ","pages":"Article 102973"},"PeriodicalIF":2.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Tausch: A halo exchange library for large heterogeneous computing systems using MPI, OpenCL, and CUDA\",\"authors\":\"Lukas Spies ,&nbsp;Amanda Bienz ,&nbsp;David Moulton ,&nbsp;Luke Olson ,&nbsp;Andrew Reisner\",\"doi\":\"10.1016/j.parco.2022.102973\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span>Exchanging halo data is a common task in modern scientific computing<span><span> applications and efficient handling of this operation is critical for the performance of the overall simulation. Tausch is a novel header-only library that provides a simple API for efficiently handling these types of data movements. Tausch supports both simple CPU-only systems, but also more complex heterogeneous systems with both CPUs and </span>GPUs. It currently supports both </span></span>OpenCL<span> and CUDA for communicating with GPGPU devices, and allows for communication between GPGPUs and CPUs. The API allows for drop-in replacement in existing codes and can be used for the communication layer in new codes. This paper provides an overview of the approach taken in Tausch, and a performance analysis that demonstrates expected and achieved performance. We highlight the ease of use and performance with three applications: First Tausch is compared to the halo exchange framework from two Mantevo applications, HPCCG and miniFE, and then it is used to replace a legacy halo exchange library in the flexible multigrid solver framework Cedar.</span></p></div>\",\"PeriodicalId\":54642,\"journal\":{\"name\":\"Parallel Computing\",\"volume\":\"114 \",\"pages\":\"Article 102973\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Parallel Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167819122000631\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Parallel Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167819122000631","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 1

摘要

在现代科学计算应用中,交换光晕数据是一项常见的任务,有效地处理这一操作对整个模拟的性能至关重要。Tausch是一个新颖的头文件库,它提供了一个简单的API来有效地处理这些类型的数据移动。Tausch既支持简单的只有cpu的系统,也支持更复杂的具有cpu和gpu的异构系统。它目前支持OpenCL和CUDA与GPGPU设备的通信,并允许GPGPU和cpu之间的通信。该API允许在现有代码中插入替换,并可用于新代码中的通信层。本文概述了Tausch采用的方法,并进行了性能分析,展示了预期的性能和已实现的性能。我们强调了三个应用程序的易用性和性能:首先将Tausch与Mantevo的两个应用程序HPCCG和miniFE的halo交换框架进行比较,然后使用Tausch取代灵活的多网格求解器框架Cedar中的遗留halo交换库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Tausch: A halo exchange library for large heterogeneous computing systems using MPI, OpenCL, and CUDA

Exchanging halo data is a common task in modern scientific computing applications and efficient handling of this operation is critical for the performance of the overall simulation. Tausch is a novel header-only library that provides a simple API for efficiently handling these types of data movements. Tausch supports both simple CPU-only systems, but also more complex heterogeneous systems with both CPUs and GPUs. It currently supports both OpenCL and CUDA for communicating with GPGPU devices, and allows for communication between GPGPUs and CPUs. The API allows for drop-in replacement in existing codes and can be used for the communication layer in new codes. This paper provides an overview of the approach taken in Tausch, and a performance analysis that demonstrates expected and achieved performance. We highlight the ease of use and performance with three applications: First Tausch is compared to the halo exchange framework from two Mantevo applications, HPCCG and miniFE, and then it is used to replace a legacy halo exchange library in the flexible multigrid solver framework Cedar.

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
Parallel Computing
Parallel Computing 工程技术-计算机:理论方法
CiteScore
3.50
自引率
7.10%
发文量
49
审稿时长
4.5 months
期刊介绍: Parallel Computing is an international journal presenting the practical use of parallel computer systems, including high performance architecture, system software, programming systems and tools, and applications. Within this context the journal covers all aspects of high-end parallel computing from single homogeneous or heterogenous computing nodes to large-scale multi-node systems. Parallel Computing features original research work and review articles as well as novel or illustrative accounts of application experience with (and techniques for) the use of parallel computers. We also welcome studies reproducing prior publications that either confirm or disprove prior published results. Particular technical areas of interest include, but are not limited to: -System software for parallel computer systems including programming languages (new languages as well as compilation techniques), operating systems (including middleware), and resource management (scheduling and load-balancing). -Enabling software including debuggers, performance tools, and system and numeric libraries. -General hardware (architecture) concepts, new technologies enabling the realization of such new concepts, and details of commercially available systems -Software engineering and productivity as it relates to parallel computing -Applications (including scientific computing, deep learning, machine learning) or tool case studies demonstrating novel ways to achieve parallelism -Performance measurement results on state-of-the-art systems -Approaches to effectively utilize large-scale parallel computing including new algorithms or algorithm analysis with demonstrated relevance to real applications using existing or next generation parallel computer architectures. -Parallel I/O systems both hardware and software -Networking technology for support of high-speed computing demonstrating the impact of high-speed computation on parallel applications
期刊最新文献
Towards resilient and energy efficient scalable Krylov solvers Seesaw: A 4096-bit vector processor for accelerating Kyber based on RISC-V ISA extensions Editorial Board FastPTM: Fast weights loading of pre-trained models for parallel inference service provisioning Distributed consensus-based estimation of the leading eigenvalue of a non-negative irreducible matrix
×
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