Simulation of Pipelined MIPS Floating-Point Units using Node-RED

Author:

McClain Bryan,Fang Jinyu,Kale Prathamesh,J. Lee John

Abstract

The pipelined processor architecture is the best way to increase instruction-level parallelism, and thus, understanding its operation is one of the keys in computer architecture learning. To help with the leaning process, we have devised a series of pipeline simulation methodologies. This article presents one of them – a simulation methodology of hazard detection and forwarding in MIPS32 pipelined floating-point units. Our implementation approach is using the Node-RED programming environment, an event-driven dragand-drop system for designing data flows with business logic. In addition, to implement sophisticated operations not supported by Node-RED, we also employ WebAssembly code and the Rust language. We simulate not only the standard 5-stage pipelined MIPS ISA but also pipelined (addition, subtraction, and multiplication) and unpipelined (division) floating-point operations. Our study focuses mainly on hazard detection, which is required to ensure program correctness, as well as forwarding used to improve system performance. Lastly, we design a dashboard interface to visually represent the pipeline stages and CPU status during execution. Using the dashboard interface, MIPS32 machine code can be loaded into our simulator from hexadecimal text files. We verified that our simulator is handling hazard detection and forwarding correctly. A screenshot of the dashboard interface is included that shows all the stages of floating-point pipelines.

Publisher

Academy and Industry Research Collaboration Center (AIRCC)

Subject

General Medicine

Reference14 articles.

1. [1] "MIPS32 architecture", https://www.mips.com/products/architectures/mips32-2/, Accessed in May 2022.

2. [2] "IEEE standard for floating-point arithmetic", (2008) IEEE Std 754-2008, pp1-70.

3. [3] "Node-RED: Low-code programming for event-driven applications", https://nodered.org/, Accessed in May 2022.

4. [4] "NodeJS." https://nodejs.org/, Accessed in May 2022.

5. [5] E. Ecma, (1999) "262: Ecmascript language specification", ECMA (European Association for Standardizing Information and Communication Systems).

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