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Last Level Cache (LLC) Performance of Data Mining Workloads On a CMP — Case Study of Parallel Bioinformatics Workloads

dc.contributor.authorJaleel, Aamer
dc.contributor.authorMattina, Matthew
dc.contributor.authorJacob, Bruce
dc.identifier.citation"Last-level cache (LLC) performance of data-mining workloads on a CMP--A case study of parallel bioinformatics workloads." Aamer Jaleel, Matthew Mattina, and Bruce Jacob. Proc. 12th International Symposium on High Performance Computer Architecture (HPCA 2006), Austin TX, February 2006.en
dc.description.abstractWith the continuing growth in the amount of genetic data, members of the bioinformatics community are developing a variety of data-mining applications to understand the data and discover meaningful information. These applications are important in defining the design and performance decisions of future high performance microprocessors. This paper presents a detailed data-sharing analysis and chip-multiprocessor (CMP) cache study of several multithreaded data-mining bioinformatics workloads. For a CMP with a three-level cache hierarchy, we model the last-level of the cache hierarchy as either multiple private caches or a single cache shared amongst different cores of the CMP. Our experiments show that the bioinformatics workloads exhibit significant data-sharing—50–95% of the data cache is shared by the different threads of the workload. Furthermore, regardless of the amount of data cache shared, for some workloads, as many as 98% of the accesses to the last-level cache are to shared data cache lines. Additionally, the amount of data-sharing exhibited by the workloads is a function of the total cache size available—the larger the data cache the better the sharing behavior. Thus, partitioning the available last-level cache silicon area into multiple private caches can cause applications to lose their inherent data-sharing behavior. For the workloads in this study, a shared 32MB last-level cache is able to capture a tremendous amount of data-sharing and outperform a 32MB private cache configuration by several orders of magnitude. Specifically, with shared last-level caches, the bandwidth demands beyond the last-level cache can be reduced by factors of 3–625 when compared to private last-level caches.en
dc.format.extent377065 bytes
dc.subjectchip-multiprocessor (CMP)en
dc.subjectcache hierarchyen
dc.titleLast Level Cache (LLC) Performance of Data Mining Workloads On a CMP — Case Study of Parallel Bioinformatics Workloadsen
dc.relation.isAvailableAtA. James Clark School of Engineeringen_us
dc.relation.isAvailableAtElectrical & Computer Engineeringen_us
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us

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