{"title":"异构计算系统中编译时任务调度的近下界复杂度算法","authors":"Tarek Hagras, J. Janecek","doi":"10.1109/ISPDC.2004.3","DOIUrl":null,"url":null,"abstract":"Task scheduling is in general an NP-complete problem. For this reason a huge number of heuristics have been presented in the literature to obtain near optimal schedules. These heuristics mainly target homogeneous computing systems, while a few of them target heterogeneous systems. The heterogeneous heuristics presented so far target computing machines with different capabilities, while almost none of them handle heterogeneous communication systems. This paper presents a novel task scheduling algorithm called the heterogeneous critical tasks reverse duplicator (HCTRD), which targets both heterogeneous computation and communication systems. The algorithm is based on list-scheduling and task-duplication in a bounded number of machines, and aims to achieve high performance and near lower bound complexity.","PeriodicalId":62714,"journal":{"name":"骈文研究","volume":"33 1","pages":"106-113"},"PeriodicalIF":0.0000,"publicationDate":"2004-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"A near lower-bound complexity algorithm for compile-time task-scheduling in heterogeneous computing systems\",\"authors\":\"Tarek Hagras, J. Janecek\",\"doi\":\"10.1109/ISPDC.2004.3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Task scheduling is in general an NP-complete problem. For this reason a huge number of heuristics have been presented in the literature to obtain near optimal schedules. These heuristics mainly target homogeneous computing systems, while a few of them target heterogeneous systems. The heterogeneous heuristics presented so far target computing machines with different capabilities, while almost none of them handle heterogeneous communication systems. This paper presents a novel task scheduling algorithm called the heterogeneous critical tasks reverse duplicator (HCTRD), which targets both heterogeneous computation and communication systems. The algorithm is based on list-scheduling and task-duplication in a bounded number of machines, and aims to achieve high performance and near lower bound complexity.\",\"PeriodicalId\":62714,\"journal\":{\"name\":\"骈文研究\",\"volume\":\"33 1\",\"pages\":\"106-113\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"骈文研究\",\"FirstCategoryId\":\"1092\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPDC.2004.3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"骈文研究","FirstCategoryId":"1092","ListUrlMain":"https://doi.org/10.1109/ISPDC.2004.3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A near lower-bound complexity algorithm for compile-time task-scheduling in heterogeneous computing systems
Task scheduling is in general an NP-complete problem. For this reason a huge number of heuristics have been presented in the literature to obtain near optimal schedules. These heuristics mainly target homogeneous computing systems, while a few of them target heterogeneous systems. The heterogeneous heuristics presented so far target computing machines with different capabilities, while almost none of them handle heterogeneous communication systems. This paper presents a novel task scheduling algorithm called the heterogeneous critical tasks reverse duplicator (HCTRD), which targets both heterogeneous computation and communication systems. The algorithm is based on list-scheduling and task-duplication in a bounded number of machines, and aims to achieve high performance and near lower bound complexity.