{"title":"片上网络内存感知映射和调度的分层螺旋算法","authors":"Shuo Li, Fahimeh Jafari, A. Hemani, Shashi Kumar","doi":"10.1109/NORCHIP.2010.5669442","DOIUrl":null,"url":null,"abstract":"In this paper, Layered Spiral Algorithm (LSA) is proposed for memory-aware application mapping and scheduling onto Network-on-Chip (NoC) based Multi-Processor System-on-Chip (MPSoC). The energy consumption is optimized while keeping high task level parallelism. The experimental evaluation indicates that if memory-awareness is not considered during mapping and scheduling, memory overflows may occur. The underlying problem is also modeled as a Mixed Integer Linear Programming (MILP) problem and solved using an efficient branch-and-bound algorithm to compare optimal solutions with results achieved by LSA. Comparing to MILP solutions, the LSA results demonstrate only about 20% and 12% increase of total communication cost in case of a small and middle size synthetic problem, respectively, while it is order of magnitude faster than the MILP solutions. Therefore, the LSA can find acceptable total communication cost with a low runtime complexity, enabling quick exploration of large design spaces, which is infeasible for exhaustive search.","PeriodicalId":292342,"journal":{"name":"NORCHIP 2010","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Layered Spiral Algorithm for memory-aware mapping and scheduling on Network-on-Chip\",\"authors\":\"Shuo Li, Fahimeh Jafari, A. Hemani, Shashi Kumar\",\"doi\":\"10.1109/NORCHIP.2010.5669442\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, Layered Spiral Algorithm (LSA) is proposed for memory-aware application mapping and scheduling onto Network-on-Chip (NoC) based Multi-Processor System-on-Chip (MPSoC). The energy consumption is optimized while keeping high task level parallelism. The experimental evaluation indicates that if memory-awareness is not considered during mapping and scheduling, memory overflows may occur. The underlying problem is also modeled as a Mixed Integer Linear Programming (MILP) problem and solved using an efficient branch-and-bound algorithm to compare optimal solutions with results achieved by LSA. Comparing to MILP solutions, the LSA results demonstrate only about 20% and 12% increase of total communication cost in case of a small and middle size synthetic problem, respectively, while it is order of magnitude faster than the MILP solutions. Therefore, the LSA can find acceptable total communication cost with a low runtime complexity, enabling quick exploration of large design spaces, which is infeasible for exhaustive search.\",\"PeriodicalId\":292342,\"journal\":{\"name\":\"NORCHIP 2010\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NORCHIP 2010\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NORCHIP.2010.5669442\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NORCHIP 2010","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NORCHIP.2010.5669442","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Layered Spiral Algorithm for memory-aware mapping and scheduling on Network-on-Chip
In this paper, Layered Spiral Algorithm (LSA) is proposed for memory-aware application mapping and scheduling onto Network-on-Chip (NoC) based Multi-Processor System-on-Chip (MPSoC). The energy consumption is optimized while keeping high task level parallelism. The experimental evaluation indicates that if memory-awareness is not considered during mapping and scheduling, memory overflows may occur. The underlying problem is also modeled as a Mixed Integer Linear Programming (MILP) problem and solved using an efficient branch-and-bound algorithm to compare optimal solutions with results achieved by LSA. Comparing to MILP solutions, the LSA results demonstrate only about 20% and 12% increase of total communication cost in case of a small and middle size synthetic problem, respectively, while it is order of magnitude faster than the MILP solutions. Therefore, the LSA can find acceptable total communication cost with a low runtime complexity, enabling quick exploration of large design spaces, which is infeasible for exhaustive search.