{"title":"An energy-aware mapping algorithm for mesh-based network-on-chip architectures","authors":"Jin Sun, Yi Zhang","doi":"10.1109/PIC.2017.8359572","DOIUrl":null,"url":null,"abstract":"Network-on-chip (NoC) mapping algorithms significantly affect NoC system performance in terms of communication cost and energy consumption. For a specific application represented by a task graph, this paper proposes an energy-aware mapping algorithm that searches for the mapping solution with best communication locality and therefore lowest energy consumption. During the search procedure, we employ a simulation-free, communication locality-based energy model to evaluate the quality of each candidate mapping. By iteratively updating the best candidate mapping using a greedy search heuristic, the search procedure converges to an mapping decision with optimal energy efficiency in the search space. Compared with the round-robin mapping strategy, the proposed method is capable of exploring energy-efficient mapping decision for various applications as well as network sizes.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Progress in Informatics and Computing (PIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIC.2017.8359572","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Network-on-chip (NoC) mapping algorithms significantly affect NoC system performance in terms of communication cost and energy consumption. For a specific application represented by a task graph, this paper proposes an energy-aware mapping algorithm that searches for the mapping solution with best communication locality and therefore lowest energy consumption. During the search procedure, we employ a simulation-free, communication locality-based energy model to evaluate the quality of each candidate mapping. By iteratively updating the best candidate mapping using a greedy search heuristic, the search procedure converges to an mapping decision with optimal energy efficiency in the search space. Compared with the round-robin mapping strategy, the proposed method is capable of exploring energy-efficient mapping decision for various applications as well as network sizes.