{"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}
引用次数: 58
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.