Electrical & Computer Engineering Research Works

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Author: search.filters.author.Jaleel, AamerSubject: search.filters.subject.bioinformatics

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    BioBench: A Benchmark Suite of Bioinformatics Applications
    (2005-03) Albayraktaroglu, Kursad; Jaleel, Aamer; Wu, Xue; Franklin, Manoj; Jacob, Bruce; Tseng, Chau-Wen; Yeung, Donald
    Recent advances in bioinformatics and the significant increase in computational power available to researchers have made it possible to make better use of the vast amounts of genetic data that has been collected over the last two decades. As the uses of genetic data expand to include drug discovery and development of gene-based therapies, bioinformatics is destined to take its place in the forefront of scientific computing application domains. Despite the clear importance of this field, common bioinformatics applications and their implication on microarchitectural design have received scant attention from the computer architecture community so far. The availability of a common set of bioinformatics benchmarks could be the first step to motivate further research in this crucial area. To this end, this paper presents BioBench, a benchmark suite that represents a diverse set of bioinformatics applications. The first version of BioBench includes applications from different application domains, with a particular emphasis on mature genomics applications. The applications in the benchmark are described briefly, and basic execution characteristics obtained on a real processor are presented. Compared to SPEC INT and SPEC FP benchmarks, applications in BioBench display a higher percentage of load/store instructions, almost negligible floating point operation content, and higher IPC than either SPEC INT and SPEC FP applications. Our evaluation suggests that bioinformatics applications have distinctly different characteristics from the applications in both of the mentioned SPEC suites; and our findings indicate that bioinformatics workloads can benefit from architectural improvements to memory bandwidth and techniques that exploit their high levels of ILP. The entire BioBench suite and accompanying reference data will be made freely available to researchers.
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    Last Level Cache (LLC) Performance of Data Mining Workloads On a CMP — Case Study of Parallel Bioinformatics Workloads
    (2006-02) Jaleel, Aamer; Mattina, Matthew; Jacob, Bruce
    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 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.