Optimal simultaneous module and multivoltage assignment for low power

Author:

Chen Deming1,Cong Jason2,Xu Junjuan3

Affiliation:

1. University of Illinois, Urbana-Champaign, Urbana, IL

2. University of California, Los Angeles, Los Angeles, CA

3. Synopsys, Inc., Shanghai, China

Abstract

Reducing power consumption through high-level synthesis has attracted a growing interest from researchers due to its large potential for power reduction. In this work we study functional unit binding (or module assignment) given a scheduled data flow graph under a multi-Vdd framework. We assume that each functional unit can be driven by different Vdd levels dynamically during run time to save dynamic power. We develop a polynomial-time optimal algorithm for assigning low Vdds to as many operations as possible under the resource and latency constraints, and in the same time minimizing total switching activity through functional unit binding. Our algorithm shows consistent improvement over a design flow that separates voltage assignment from functional unit binding. We also change the initial scheduling to examine power/energy-latency tradeoff scenarios under different voltage level combinations. Experimental results show that we can achieve 28.1% and 33.4% power reductions when the latency bound is the tightest with two and three-Vdd levels respectively compared with the single-Vdd case. When latency is relaxed, multi-Vdd offers larger power reductions (up to 46.7%). We also show comparison data of energy consumption under the same experimental settings.

Publisher

Association for Computing Machinery (ACM)

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Computer Science Applications

Cited by 12 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. Compilation and Optimizations for Efficient Machine Learning on Embedded Systems;Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing;2023-10-10

2. AccShield: a New Trusted Execution Environment with Machine-Learning Accelerators;2023 60th ACM/IEEE Design Automation Conference (DAC);2023-07-09

3. ReAAP: A Reconfigurable and Algorithm-Oriented Array Processor with Compiler-Architecture Co-Design;IEEE Transactions on Computers;2022

4. An Integrated Approach for Fine-Grained Power and Peak Temperature Management During High-Level Synthesis;Journal of Low Power Electronics;2013-10-01

5. Floorplan Driven Architecture and High-Level Synthesis Algorithm for Dynamic Multiple Supply Voltages;IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences;2013

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