{"title":"避免由于私有数据放置在多核扩展的最后一级缓存中而导致缓存抖动","authors":"Jiayuan Meng, K. Skadron","doi":"10.1109/ICCD.2009.5413143","DOIUrl":null,"url":null,"abstract":"Without high-bandwidth broadcast, large numbers of cores require a scalable point-to-point interconnect and a directory protocol. In such cases, a shared, inclusive last level cache (LLC) can improve data sharing and avoid three-way communication for shared reads. However, if inclusion encompasses thread-private data, two problems arise with the shared LLC. First, current memory allocators align stack bases on page boundaries, which emerges as a source of severe conflict misses for large numbers of threads on data-parallel applications. Second, correctness does not require the private data to reside in the shared directory or the LLC. This paper advocates stack-base randomization that eliminates the major source of conflict misses for large numbers of threads. However, when capacity becomes a limitation for the directory or last-level cache, this is not sufficient. We then propose non-inclusive, semi-coherent cache organization (NISC) that removes the requirement for inclusion of private data and reduces capacity misses. Our data-parallel benchmarks show that these limitations prevent scaling beyond 8 cores, while our techniques allow scaling to at least 32 cores for most benchmarks. At 8 cores, stack randomization provides a mean speedup of 1.2X, but stack randomization with 32 cores gives a speedup of 2.7X over the best baseline configuration. Comparing to conventional performance with a 2 MB LLC, our technique achieves similar performance with a 256 KB LLC, suggesting LLCs may be typically overprovisioned. When very limited LLC resources are available, NISC can further improve system performance by 1.8X.","PeriodicalId":256908,"journal":{"name":"2009 IEEE International Conference on Computer Design","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"58","resultStr":"{\"title\":\"Avoiding cache thrashing due to private data placement in last-level cache for manycore scaling\",\"authors\":\"Jiayuan Meng, K. Skadron\",\"doi\":\"10.1109/ICCD.2009.5413143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Without high-bandwidth broadcast, large numbers of cores require a scalable point-to-point interconnect and a directory protocol. In such cases, a shared, inclusive last level cache (LLC) can improve data sharing and avoid three-way communication for shared reads. However, if inclusion encompasses thread-private data, two problems arise with the shared LLC. First, current memory allocators align stack bases on page boundaries, which emerges as a source of severe conflict misses for large numbers of threads on data-parallel applications. Second, correctness does not require the private data to reside in the shared directory or the LLC. This paper advocates stack-base randomization that eliminates the major source of conflict misses for large numbers of threads. However, when capacity becomes a limitation for the directory or last-level cache, this is not sufficient. We then propose non-inclusive, semi-coherent cache organization (NISC) that removes the requirement for inclusion of private data and reduces capacity misses. Our data-parallel benchmarks show that these limitations prevent scaling beyond 8 cores, while our techniques allow scaling to at least 32 cores for most benchmarks. At 8 cores, stack randomization provides a mean speedup of 1.2X, but stack randomization with 32 cores gives a speedup of 2.7X over the best baseline configuration. Comparing to conventional performance with a 2 MB LLC, our technique achieves similar performance with a 256 KB LLC, suggesting LLCs may be typically overprovisioned. When very limited LLC resources are available, NISC can further improve system performance by 1.8X.\",\"PeriodicalId\":256908,\"journal\":{\"name\":\"2009 IEEE International Conference on Computer Design\",\"volume\":\"109 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"58\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Computer Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCD.2009.5413143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Computer Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCD.2009.5413143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Avoiding cache thrashing due to private data placement in last-level cache for manycore scaling
Without high-bandwidth broadcast, large numbers of cores require a scalable point-to-point interconnect and a directory protocol. In such cases, a shared, inclusive last level cache (LLC) can improve data sharing and avoid three-way communication for shared reads. However, if inclusion encompasses thread-private data, two problems arise with the shared LLC. First, current memory allocators align stack bases on page boundaries, which emerges as a source of severe conflict misses for large numbers of threads on data-parallel applications. Second, correctness does not require the private data to reside in the shared directory or the LLC. This paper advocates stack-base randomization that eliminates the major source of conflict misses for large numbers of threads. However, when capacity becomes a limitation for the directory or last-level cache, this is not sufficient. We then propose non-inclusive, semi-coherent cache organization (NISC) that removes the requirement for inclusion of private data and reduces capacity misses. Our data-parallel benchmarks show that these limitations prevent scaling beyond 8 cores, while our techniques allow scaling to at least 32 cores for most benchmarks. At 8 cores, stack randomization provides a mean speedup of 1.2X, but stack randomization with 32 cores gives a speedup of 2.7X over the best baseline configuration. Comparing to conventional performance with a 2 MB LLC, our technique achieves similar performance with a 256 KB LLC, suggesting LLCs may be typically overprovisioned. When very limited LLC resources are available, NISC can further improve system performance by 1.8X.