Heterogeneous Computing for Bioinformatics Applications
Advances in bioinformatics research continue to add complexity to the analyses and interpretation of biological data. Certain genomic sequence database searches may take weeks to complete due to complicated data dependencies by dynamic programming. A reconfigurable coprocessor can remove this computational bottleneck and accelerate the operation. This study presents a heterogeneous computing platform through Message Passing Interface enabled enterprise computing infrastructure for high-throughput biological sequence analysis. The computing platform integrates heterogeneous computer architectures including conventional processors with Streaming Single Instruction Multiple Data Extensions 2 instructions, reconfigurable coprocessors, and legacy processors together into one architecture, and allows each to perform the task to which it is best suited. With appropriate computation and communication scheduling, the integrated heterogeneous computing infrastructure is designed to accommodate various types of accelerators to provide a High Performance Computing framework to support the most widely used life science applications. The heterogeneous implementation executing at a cluster with eight Dual Core AMD Opteron 175 processors and one coprocessor achieves up to 110 times faster than a traditional C implementation executing on a 1.9 GHz Pentium IV processor. Figure shows the architecture of the heterogeneous computing architecture.
Xiandong Meng Vipin Chaudhary
Supercomputing Facility, Texas A&M University, College Station, TX 77843, USA Department of Computer Science and Engineering, NYS Center of Excellence in Bioinformatics and Life
国际会议
The 7th Asia-Pacific Bioinformatics Conference(第七届亚太生物信息学大会)
北京
英文
824
2009-01-01（万方平台首次上网日期，不代表论文的发表时间）