An FPGA-based Approach to Evaluate Thermal and Resource Management Strategies of Many-core Processors

Author:

Mettler Marcel1ORCID,Rapp Martin2,Khdr Heba2,Mueller-Gritschneder Daniel1,Henkel Jörg2,Schlichtmann Ulf1

Affiliation:

1. Chair of EDA, Technical University of Munich, Munich, Germany

2. Chair for ES, Karlsruhe Institute of Technology, Karlsruhe, Germany

Abstract

The continuous technology scaling of integrated circuits results in increasingly higher power densities and operating temperatures. Hence, modern many-core processors require sophisticated thermal and resource management strategies to mitigate these undesirable side effects. A simulation-based evaluation of these strategies is limited by the accuracy of the underlying processor model and the simulation speed. Therefore, we present, for the first time, an field-programmable gate array (FPGA)-based evaluation approach to test and compare thermal and resource management strategies using the combination of benchmark generation, FPGA-based application-specific integrated circuit (ASIC) emulation, and run-time monitoring. The proposed benchmark generation method enables an evaluation of run-time management strategies for applications with various run-time characteristics. Furthermore, the ASIC emulation platform features a novel distributed temperature emulator design, whose overhead scales linearly with the number of integrated cores, and a novel dynamic voltage frequency scaling emulator design, which precisely models the timing and energy overhead of voltage and frequency transitions. In our evaluations, we demonstrate the proposed approach for a tiled many-core processor with 80 cores on four Virtex-7 FPGAs. Additionally, we present the suitability of the platform to evaluate state-of-the-art run-time management techniques with a case study.

Funder

Deutsche Forschungsgemeinschaft

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Web-based Calculator Tool for FPGA Power Consumption Estimation for Teaching Purposes;2023 International Conference on Electromechanical and Energy Systems (SIELMEN);2023-10-11

2. HDSuper: Algorithm-Hardware Co-design for Light-weight High-quality Super-Resolution Accelerator;2023 60th ACM/IEEE Design Automation Conference (DAC);2023-07-09

3. Extended Abstract: Monitoring-based Thermal Management for Mixed-Criticality Systems;2023 Design, Automation & Test in Europe Conference & Exhibition (DATE);2023-04

4. Deep Reinforcement Learning for System-on-Chip: Myths and Realities;IEEE Access;2022

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