{"title":"用于在多核处理器上最大化吞吐量的热约束工作负载分布","authors":"Zhe Wang, S. Ranka","doi":"10.1109/GREENCOMP.2010.5598302","DOIUrl":null,"url":null,"abstract":"Power density and heat density of multi-core processor system are increasing exponentially based on Moore's Law. The reliability of a chip is severely impacted by temperature “hot spots”. In this paper, we study scheduling algorithms for multi-core processors that incorporate temperature constraints. Our goal is to optimize the workload distribution on a multicore processor to maximize throughput with a given maximum operating temperature. Our algorithms are targeted for a larger class of data parallel and task parallel applications. Experimental results show that our algorithms are computationally fast, maximize throughput and provide effective temperature management.","PeriodicalId":262148,"journal":{"name":"International Conference on Green Computing","volume":"113 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Thermal constrained workload distribution for maximizing throughput on multi-core processors\",\"authors\":\"Zhe Wang, S. Ranka\",\"doi\":\"10.1109/GREENCOMP.2010.5598302\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Power density and heat density of multi-core processor system are increasing exponentially based on Moore's Law. The reliability of a chip is severely impacted by temperature “hot spots”. In this paper, we study scheduling algorithms for multi-core processors that incorporate temperature constraints. Our goal is to optimize the workload distribution on a multicore processor to maximize throughput with a given maximum operating temperature. Our algorithms are targeted for a larger class of data parallel and task parallel applications. Experimental results show that our algorithms are computationally fast, maximize throughput and provide effective temperature management.\",\"PeriodicalId\":262148,\"journal\":{\"name\":\"International Conference on Green Computing\",\"volume\":\"113 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Green Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GREENCOMP.2010.5598302\",\"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 Green Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GREENCOMP.2010.5598302","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Thermal constrained workload distribution for maximizing throughput on multi-core processors
Power density and heat density of multi-core processor system are increasing exponentially based on Moore's Law. The reliability of a chip is severely impacted by temperature “hot spots”. In this paper, we study scheduling algorithms for multi-core processors that incorporate temperature constraints. Our goal is to optimize the workload distribution on a multicore processor to maximize throughput with a given maximum operating temperature. Our algorithms are targeted for a larger class of data parallel and task parallel applications. Experimental results show that our algorithms are computationally fast, maximize throughput and provide effective temperature management.
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