DocumentCode :
3306992
Title :
Last level cache (LLC) performance of data mining workloads on a CMP - a case study of parallel bioinformatics workloads
Author :
Jaleel, Aamer ; Mattina, Matthew ; Jacob, Bruce
Author_Institution :
VSSAD, Intel Corp., USA
fYear :
2006
fDate :
11-15 Feb. 2006
Firstpage :
88
Lastpage :
98
Abstract :
With 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 32 MB last-level cache is able to capture a tremendous amount of data-sharing and outperform a 32 MB 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.
Keywords :
biology computing; cache storage; data mining; microprocessor chips; multi-threading; multiprocessing systems; scientific information systems; CMP; chip-multiprocessor cache; data-sharing analysis; genetic data; last level cache performance; last-level cache silicon area; multiple private caches; multithreaded data-mining bioinformatics workloads; parallel bioinformatics workloads; single cache; three-level cache hierarchy; Bioinformatics; Biology computing; Computer aided software engineering; Concurrent computing; Data engineering; Data mining; Databases; Educational institutions; Jacobian matrices; Yarn;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
High-Performance Computer Architecture, 2006. The Twelfth International Symposium on
ISSN :
1530-0897
Print_ISBN :
0-7803-9368-6
Type :
conf
DOI :
10.1109/HPCA.2006.1598115
Filename :
1598115
Link To Document :
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