{"title":"分布式协同缓存","authors":"E. Herrero, José González, R. Canal","doi":"10.1145/1454115.1454136","DOIUrl":null,"url":null,"abstract":"This paper presents the Distributed Cooperative Caching, a scalable and energy-efficient scheme to manage chip multiprocessor (CMP) cache resources. The proposed configuration is based in the Cooperative Caching framework [3] but it is intended for large scale CMPs. Both centralized and distributed configurations have the advantage of combining the benefits of private and shared caches. In our proposal, the Coherence Engine has been redesigned to allow its partitioning and thus, eliminate the size constraints imposed by the duplication of all tags. At the same time, a global replacement mechanism has been added to improve the usage of cache space. Our framework uses several Distributed Coherence Engines spread across all the nodes to improve scalability. The distribution permits a better balance of the network traffic over the entire chip avoiding bottlenecks and increasing performance for a 32-core CMP by 21% over a traditional shared memory configuration and by 57% over the Cooperative Caching scheme. Furthermore, we have reduced the power consumption of the entire system by using a different tag allocation method and by reducing the number of tags compared on each request. For a 32-core CMP the Distributed Cooperative Caching framework provides an average improvement of the power/performance relation (MIPS3/W) of 3.66× over a traditional shared memory configuration and 4.30× over Cooperative Caching.","PeriodicalId":186773,"journal":{"name":"2008 International Conference on Parallel Architectures and Compilation Techniques (PACT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"48","resultStr":"{\"title\":\"Distributed Cooperative Caching\",\"authors\":\"E. Herrero, José González, R. Canal\",\"doi\":\"10.1145/1454115.1454136\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the Distributed Cooperative Caching, a scalable and energy-efficient scheme to manage chip multiprocessor (CMP) cache resources. The proposed configuration is based in the Cooperative Caching framework [3] but it is intended for large scale CMPs. Both centralized and distributed configurations have the advantage of combining the benefits of private and shared caches. In our proposal, the Coherence Engine has been redesigned to allow its partitioning and thus, eliminate the size constraints imposed by the duplication of all tags. At the same time, a global replacement mechanism has been added to improve the usage of cache space. Our framework uses several Distributed Coherence Engines spread across all the nodes to improve scalability. The distribution permits a better balance of the network traffic over the entire chip avoiding bottlenecks and increasing performance for a 32-core CMP by 21% over a traditional shared memory configuration and by 57% over the Cooperative Caching scheme. Furthermore, we have reduced the power consumption of the entire system by using a different tag allocation method and by reducing the number of tags compared on each request. For a 32-core CMP the Distributed Cooperative Caching framework provides an average improvement of the power/performance relation (MIPS3/W) of 3.66× over a traditional shared memory configuration and 4.30× over Cooperative Caching.\",\"PeriodicalId\":186773,\"journal\":{\"name\":\"2008 International Conference on Parallel Architectures and Compilation Techniques (PACT)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"48\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Conference on Parallel Architectures and Compilation Techniques (PACT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1454115.1454136\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Parallel Architectures and Compilation Techniques (PACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1454115.1454136","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents the Distributed Cooperative Caching, a scalable and energy-efficient scheme to manage chip multiprocessor (CMP) cache resources. The proposed configuration is based in the Cooperative Caching framework [3] but it is intended for large scale CMPs. Both centralized and distributed configurations have the advantage of combining the benefits of private and shared caches. In our proposal, the Coherence Engine has been redesigned to allow its partitioning and thus, eliminate the size constraints imposed by the duplication of all tags. At the same time, a global replacement mechanism has been added to improve the usage of cache space. Our framework uses several Distributed Coherence Engines spread across all the nodes to improve scalability. The distribution permits a better balance of the network traffic over the entire chip avoiding bottlenecks and increasing performance for a 32-core CMP by 21% over a traditional shared memory configuration and by 57% over the Cooperative Caching scheme. Furthermore, we have reduced the power consumption of the entire system by using a different tag allocation method and by reducing the number of tags compared on each request. For a 32-core CMP the Distributed Cooperative Caching framework provides an average improvement of the power/performance relation (MIPS3/W) of 3.66× over a traditional shared memory configuration and 4.30× over Cooperative Caching.