Accelerating Image Algorithm Development using Soft Co-Processors on FPGAs

Tiantai Deng, D. Crookes, R. Woods, F. Siddiqui
{"title":"Accelerating Image Algorithm Development using Soft Co-Processors on FPGAs","authors":"Tiantai Deng, D. Crookes, R. Woods, F. Siddiqui","doi":"10.1109/ISSC.2018.8585363","DOIUrl":null,"url":null,"abstract":"FPGAs can offer high performance with low power and low hardware usage. However, with current software, FPGAs are hard to program, and lengthy re-synthesis times make them unsuitable for the algorithm experimentation which is typical of developing image processing applications. In this paper, we present a system model based on a set of Soft Co-Processors, each of which implements a basic image-level operation (or a common combination of such operations) based on the high-level operators in Image Algebra. Both ‘debug’ (generic but unoptimised) and ‘release’ (specific and optimised) versions of the Soft Co-Processors can be used. The advantage of debug mode is that no re-synthesis is required during algorithm experimentation. For release mode, a novel macro-based transformation tool enables the creation of a set of reusable HLS skeleton co-processors which require the user only to write a C function to obtain a new, special-purpose Soft Co-Processor.Initial experiments with several algorithms show that the area and speed overheads for using debug (rather than release) mode are both around 25-30%, thus enabling algorithm development to take place on the FPGA itself. For creating function-specific Co-processors using our macro-based tool, the overheads compared with an expert hardware design are around 20%.","PeriodicalId":174854,"journal":{"name":"2018 29th Irish Signals and Systems Conference (ISSC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 29th Irish Signals and Systems Conference (ISSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSC.2018.8585363","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

FPGAs can offer high performance with low power and low hardware usage. However, with current software, FPGAs are hard to program, and lengthy re-synthesis times make them unsuitable for the algorithm experimentation which is typical of developing image processing applications. In this paper, we present a system model based on a set of Soft Co-Processors, each of which implements a basic image-level operation (or a common combination of such operations) based on the high-level operators in Image Algebra. Both ‘debug’ (generic but unoptimised) and ‘release’ (specific and optimised) versions of the Soft Co-Processors can be used. The advantage of debug mode is that no re-synthesis is required during algorithm experimentation. For release mode, a novel macro-based transformation tool enables the creation of a set of reusable HLS skeleton co-processors which require the user only to write a C function to obtain a new, special-purpose Soft Co-Processor.Initial experiments with several algorithms show that the area and speed overheads for using debug (rather than release) mode are both around 25-30%, thus enabling algorithm development to take place on the FPGA itself. For creating function-specific Co-processors using our macro-based tool, the overheads compared with an expert hardware design are around 20%.
利用fpga上的软协处理器加速图像算法开发
fpga可以以低功耗和低硬件使用率提供高性能。然而,在现有的软件下,fpga很难编程,并且漫长的重新合成时间使其不适合开发图像处理应用的典型算法实验。在本文中,我们提出了一个基于一组软协处理器的系统模型,每个软协处理器基于图像代数中的高级算子实现一个基本的图像级操作(或这些操作的常见组合)。软协处理器的“调试”(通用但未优化)和“发布”(特定和优化)版本都可以使用。调试模式的优点是在算法实验期间不需要重新合成。对于发布模式,一个新颖的基于宏的转换工具可以创建一组可重用的HLS框架协处理器,用户只需编写一个C函数即可获得一个新的专用软协处理器。几种算法的初步实验表明,使用调试(而不是发布)模式的面积和速度开销都在25-30%左右,从而使算法开发能够在FPGA本身上进行。对于使用我们的基于宏的工具创建特定功能的协处理器,与专业硬件设计相比,开销约为20%。
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:604180095
Book学术官方微信