{"title":"Heuristic approaches to energy optimization in deep submicron bus design through QAP formulation","authors":"Konstantinos Papalamprou","doi":"10.1016/j.vlsi.2025.102404","DOIUrl":null,"url":null,"abstract":"<div><div>As modern microprocessors become increasingly interconnected, energy dissipation within digital circuits has emerged as a critical challenge, particularly in deep submicron (DSM) technologies where parasitic effects are significant. This paper addresses the energy reduction problem in DSM bus design by formulating it as a Quadratic Assignment Problem (QAP), an NP-hard combinatorial optimization problem. By leveraging this framework, optimal wire permutations that minimize energy dissipation are systematically pursued.Given the intractability of solving large-scale QAPs exactly, we evaluate heuristic algorithms for their effectiveness in approximating near-optimal solutions within a feasible timeframe. The study compares the performance of various heuristic approaches. Results demonstrate that certain methods achieve rapid convergence and significant energy reduction, proving their suitability for real-time applications. The analysis highlights the potential of heuristic methods as practical solutions for complex energy optimization problems in DSM bus systems.</div></div>","PeriodicalId":54973,"journal":{"name":"Integration-The Vlsi Journal","volume":"103 ","pages":"Article 102404"},"PeriodicalIF":2.2000,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Integration-The Vlsi Journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167926025000616","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0
Abstract
As modern microprocessors become increasingly interconnected, energy dissipation within digital circuits has emerged as a critical challenge, particularly in deep submicron (DSM) technologies where parasitic effects are significant. This paper addresses the energy reduction problem in DSM bus design by formulating it as a Quadratic Assignment Problem (QAP), an NP-hard combinatorial optimization problem. By leveraging this framework, optimal wire permutations that minimize energy dissipation are systematically pursued.Given the intractability of solving large-scale QAPs exactly, we evaluate heuristic algorithms for their effectiveness in approximating near-optimal solutions within a feasible timeframe. The study compares the performance of various heuristic approaches. Results demonstrate that certain methods achieve rapid convergence and significant energy reduction, proving their suitability for real-time applications. The analysis highlights the potential of heuristic methods as practical solutions for complex energy optimization problems in DSM bus systems.
期刊介绍:
Integration''s aim is to cover every aspect of the VLSI area, with an emphasis on cross-fertilization between various fields of science, and the design, verification, test and applications of integrated circuits and systems, as well as closely related topics in process and device technologies. Individual issues will feature peer-reviewed tutorials and articles as well as reviews of recent publications. The intended coverage of the journal can be assessed by examining the following (non-exclusive) list of topics:
Specification methods and languages; Analog/Digital Integrated Circuits and Systems; VLSI architectures; Algorithms, methods and tools for modeling, simulation, synthesis and verification of integrated circuits and systems of any complexity; Embedded systems; High-level synthesis for VLSI systems; Logic synthesis and finite automata; Testing, design-for-test and test generation algorithms; Physical design; Formal verification; Algorithms implemented in VLSI systems; Systems engineering; Heterogeneous systems.