Hardware/software co-design for energy-efficient seismic modeling

J. Krueger, D. Donofrio, J. Shalf, M. Mohiyuddin, Samuel Williams, L. Oliker, F. Pfreundt
{"title":"Hardware/software co-design for energy-efficient seismic modeling","authors":"J. Krueger, D. Donofrio, J. Shalf, M. Mohiyuddin, Samuel Williams, L. Oliker, F. Pfreundt","doi":"10.1145/2063384.2063482","DOIUrl":null,"url":null,"abstract":"Reverse Time Migration (RTM) has become the standard for high-quality imaging in the seismic industry. RTM relies on PDE solutions using stencils that are 8th order or larger, which require large-scale HPC clusters to meet the computational demands. However, the rising power consumption of conventional cluster technology has prompted investigation of architectural alternatives that offer higher computational efficiency. In this work, we compare the performance and energy efficiency of three architectural alternatives the Intel Nehalem X5530 multicore processor, the NVIDIA Tesla C2050 GPU, and a general-purpose manycore chip design optimized for high-order wave equations called \"Green Wave.\" We have developed an FPGA-accelerated architectural simulation platform to accurately model the power and performance of the Green Wave design. Results show that across highly-tuned high-order RTM stencils, the Green Wave implementation can offer up to 8× and 3.5× energy efficiency improvement per node respectively, compared with the Nehalem and GPU platforms. These results point to the enormous potential energy advantages of our hardware/software co-design methodology.","PeriodicalId":358797,"journal":{"name":"2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"45","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2063384.2063482","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 45

Abstract

Reverse Time Migration (RTM) has become the standard for high-quality imaging in the seismic industry. RTM relies on PDE solutions using stencils that are 8th order or larger, which require large-scale HPC clusters to meet the computational demands. However, the rising power consumption of conventional cluster technology has prompted investigation of architectural alternatives that offer higher computational efficiency. In this work, we compare the performance and energy efficiency of three architectural alternatives the Intel Nehalem X5530 multicore processor, the NVIDIA Tesla C2050 GPU, and a general-purpose manycore chip design optimized for high-order wave equations called "Green Wave." We have developed an FPGA-accelerated architectural simulation platform to accurately model the power and performance of the Green Wave design. Results show that across highly-tuned high-order RTM stencils, the Green Wave implementation can offer up to 8× and 3.5× energy efficiency improvement per node respectively, compared with the Nehalem and GPU platforms. These results point to the enormous potential energy advantages of our hardware/software co-design methodology.
节能地震建模的软硬件协同设计
逆时偏移(RTM)已成为地震行业高质量成像的标准。RTM依赖于使用8阶或更大的模板的PDE解决方案,这需要大规模的HPC集群来满足计算需求。然而,传统集群技术不断上升的功耗促使人们开始研究能够提供更高计算效率的架构替代方案。在这项工作中,我们比较了三种架构替代方案的性能和能效:英特尔Nehalem X5530多核处理器,NVIDIA Tesla C2050 GPU,以及针对高阶波动方程优化的通用多核芯片设计,称为“绿波”。我们已经开发了一个fpga加速架构仿真平台,以准确地模拟绿波设计的功率和性能。结果表明,在高度调谐的高阶RTM模板上,与Nehalem和GPU平台相比,Green Wave实现可以分别提供高达8倍和3.5倍的每个节点的能效提升。这些结果表明,我们的硬件/软件协同设计方法具有巨大的潜在能源优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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