fpga的迭代改进

Jun Kyu Lee, G. D. Peterson
{"title":"fpga的迭代改进","authors":"Jun Kyu Lee, G. D. Peterson","doi":"10.1109/SAAHPC.2011.19","DOIUrl":null,"url":null,"abstract":"Achievable accuracy for mixed precision iterative refinement depends on the precisions supported by computing platforms. Even though the arithmetic unit precision can be flexible for programmable logic computing architectures (e.g. FPGAs), previous work rarely discusses the performance benefits due to enabling flexible achievable accuracy. Hence, we propose an iterative refinement approach on FPGAs which employs an arbitrary precision for the iterative refinement to obtain an arbitrary accuracy. We implement single processing elements for the refinement on the Xilinx XC5VLX110T and compare them to Xilinx XC6VSX475T for performance estimation. This paper shows that the performance is similar to the NVIDIA GTX480 when a user requires accuracies between single and double precision, but the implementation can also produce beyond double precision accuracy.","PeriodicalId":331604,"journal":{"name":"2011 Symposium on Application Accelerators in High-Performance Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Iterative Refinement on FPGAs\",\"authors\":\"Jun Kyu Lee, G. D. Peterson\",\"doi\":\"10.1109/SAAHPC.2011.19\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Achievable accuracy for mixed precision iterative refinement depends on the precisions supported by computing platforms. Even though the arithmetic unit precision can be flexible for programmable logic computing architectures (e.g. FPGAs), previous work rarely discusses the performance benefits due to enabling flexible achievable accuracy. Hence, we propose an iterative refinement approach on FPGAs which employs an arbitrary precision for the iterative refinement to obtain an arbitrary accuracy. We implement single processing elements for the refinement on the Xilinx XC5VLX110T and compare them to Xilinx XC6VSX475T for performance estimation. This paper shows that the performance is similar to the NVIDIA GTX480 when a user requires accuracies between single and double precision, but the implementation can also produce beyond double precision accuracy.\",\"PeriodicalId\":331604,\"journal\":{\"name\":\"2011 Symposium on Application Accelerators in High-Performance Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Symposium on Application Accelerators in High-Performance Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAAHPC.2011.19\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Symposium on Application Accelerators in High-Performance Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAAHPC.2011.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

混合精度迭代细化的可实现精度取决于计算平台所支持的精度。尽管算术单元精度对于可编程逻辑计算架构(例如fpga)来说是灵活的,但以前的工作很少讨论由于实现灵活的可实现精度而带来的性能优势。因此,我们提出了一种fpga的迭代细化方法,该方法采用任意精度进行迭代细化以获得任意精度。我们在Xilinx XC5VLX110T上实现了单个处理元素,并将它们与Xilinx xc6vlx475t进行了性能评估。本文表明,当用户要求精度介于单精度和双精度之间时,其性能与NVIDIA GTX480相似,但实现也可以产生超越双精度的精度。
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
Iterative Refinement on FPGAs
Achievable accuracy for mixed precision iterative refinement depends on the precisions supported by computing platforms. Even though the arithmetic unit precision can be flexible for programmable logic computing architectures (e.g. FPGAs), previous work rarely discusses the performance benefits due to enabling flexible achievable accuracy. Hence, we propose an iterative refinement approach on FPGAs which employs an arbitrary precision for the iterative refinement to obtain an arbitrary accuracy. We implement single processing elements for the refinement on the Xilinx XC5VLX110T and compare them to Xilinx XC6VSX475T for performance estimation. This paper shows that the performance is similar to the NVIDIA GTX480 when a user requires accuracies between single and double precision, but the implementation can also produce beyond double precision accuracy.
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
期刊最新文献
Experience Applying Fortran GPU Compilers to Numerical Weather Prediction Implications of Memory-Efficiency on Sparse Matrix-Vector Multiplication Application of Graphics Processing Units (GPUs) to the Study of Non-linear Dynamics of the Exciton Bose-Einstein Condensate in a Semiconductor Quantum Well A Class of Hybrid LAPACK Algorithms for Multicore and GPU Architectures Evaluation of GPU Architectures Using Spiking Neural Networks
×
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