{"title":"多模块内存的ILP最优调度","authors":"Meikang Qiu, Lei Zhang, E. Sha","doi":"10.1145/1629435.1629473","DOIUrl":null,"url":null,"abstract":"In high-end digital signal processing (DSP) system, multi-module memory provides high memory bandwidth and low power operating mode for energy savings. However, making full use of these architectural features is a challenging problem for code optimization. In this paper, we propose an integer linear programming model to optimize the performance and energy consumption of multi-module memories by solving variable assignment, instruction scheduling and operating mode setting problems simultaneously. The combined effect of performance and energy saving requirements also has been considered. We develop two optimization techniques to improve the computation efficiency of our ILP model. The experimental results show that the optimal performance and energy solution can be achieved within a reasonable amount of time.","PeriodicalId":300268,"journal":{"name":"International Conference on Hardware/Software Codesign and System Synthesis","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"ILP optimal scheduling for multi-module memory\",\"authors\":\"Meikang Qiu, Lei Zhang, E. Sha\",\"doi\":\"10.1145/1629435.1629473\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In high-end digital signal processing (DSP) system, multi-module memory provides high memory bandwidth and low power operating mode for energy savings. However, making full use of these architectural features is a challenging problem for code optimization. In this paper, we propose an integer linear programming model to optimize the performance and energy consumption of multi-module memories by solving variable assignment, instruction scheduling and operating mode setting problems simultaneously. The combined effect of performance and energy saving requirements also has been considered. We develop two optimization techniques to improve the computation efficiency of our ILP model. The experimental results show that the optimal performance and energy solution can be achieved within a reasonable amount of time.\",\"PeriodicalId\":300268,\"journal\":{\"name\":\"International Conference on Hardware/Software Codesign and System Synthesis\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Hardware/Software Codesign and System Synthesis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1629435.1629473\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Hardware/Software Codesign and System Synthesis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1629435.1629473","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In high-end digital signal processing (DSP) system, multi-module memory provides high memory bandwidth and low power operating mode for energy savings. However, making full use of these architectural features is a challenging problem for code optimization. In this paper, we propose an integer linear programming model to optimize the performance and energy consumption of multi-module memories by solving variable assignment, instruction scheduling and operating mode setting problems simultaneously. The combined effect of performance and energy saving requirements also has been considered. We develop two optimization techniques to improve the computation efficiency of our ILP model. The experimental results show that the optimal performance and energy solution can be achieved within a reasonable amount of time.