Designing an IEEE-Compliant FPU that Supports Configurable Precision for Soft Processors

Author:

Keilbart Chris1ORCID,Gao Yuhui1ORCID,Chua Martin2ORCID,Matthews Eric1ORCID,Wilton Steven J.E.2ORCID,Shannon Lesley1ORCID

Affiliation:

1. Simon Fraser University, Burnaby, Canada

2. University of British Columbia, Vancouver, Canada

Abstract

Field Programmable Gate Arrays (FPGAs) are commonly used to accelerate floating-point (FP) applications. Although researchers have extensively studied FPGA FP implementations, existing work has largely focused on standalone operators and frequency-optimized designs. These works are not suitable for FPGA soft processors which are more sensitive to latency, impose a lower frequency ceiling, and require IEEE FP standard compliance. We present an open-source floating-point unit (FPU) for FPGA RISC-V soft processors that is fully IEEE compliant with configurable levels of FP precision. Our design emphasizes runtime performance with 25% lower latency in the most common instructions compared to previous works while maintaining efficient resource utilization. Our FPU also allows users to explore various mantissa widths without having to rewrite or recompile their algorithms. We use this to investigate the scalability of our reduced-precision FPU across numerous microbenchmark functions as well as more complex case studies. Our experiments show that applications like the discrete cosine transformation and the Black-Scholes model can realize a speedup of more than 1.35x in conjunction with a 43% and 35% reduction in lookup table and flip-flop resources while experiencing less than a 0.025% average loss in numerical accuracy with a 16-bit mantissa width.

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Association for Computing Machinery (ACM)

Reference54 articles.

1. Intel. 2023. Floating-Point IP Cores User Guide. Intel. Retrieved June 7, 2023 from https://www.intel.com/content/www/us/en/docs/programmable/683750/23-1/about-floating-point-ip-cores.html

2. Frontgrade Gaisler. 2004. GRFPU High-Performance Floating-Point Unit. Frontgrade Gaisler. Retrieved January 11, 2023 from https://www.gaisler.com/index.php/products/ipcores/ieee754fpu

3. Arvind, Krste Asanović, Rimas Avižienis, Jacob Bachmeyer, Christopher F. Batten, Allen J. Baum, Alex Bradbury, Scott Beamer, Preston Briggs, Christopher Celio, Chuanhua Chang, et al. 2019. The RISC-V Instruction Set Manual, Volume I: User-Level ISA, Document Version 20191213, Andrew Waterman and Krste Asanović (Eds.). RISC-V Foundation.

4. Low-precision Logarithmic Number Systems

5. Parameterised floating-point arithmetic on FPGAs

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3