Parameterized Characterization of Bioinfomatics Workload on SIMD Architecture

Bioinformatics applications expression profile is a critical performance metric in high end genomic data processing. These profiles are compute intensive and offers a wide range of computation pattern ranging from data base searching applications to highly irregular phylogenetic trees. Such debilating factors lead to poor architecture-application correlation. A prior knowledge of software application would be very useful for an efficient bioinformatics embedded system design. This paper presents an integrated approach for parameterized workload characterization and trace driven simulation at a high end multimedia processor in bioinformatics applications. A set of sixteen widely used bioinformatics applications is selected as benchmark. Software monitoring techniques are used to collect execution traces. Based on the measured results, we investigate both the computation and communication behavior of these applications, including execution time, functional unit utilization, scheduling factors and cache misses. The temporal and spatial localities in gnomic data are also discussed. Experimental results are measured at a high end SIMD (single instruction stream over multiple data stream) processor.