Massively Parallel Genomic Sequence Search on the Blue Gene/P Architecture
Heshan Lin, Pavan Balaji, Ruth J. Poole, Carlos Sosa, Xiaosong Ma, Wu-chun Feng · 2009
Abstract—This paper presents our first experiences in mapping and optimizing genomic sequence search onto the massively parallel IBM Blue Gene/P (BG/P) platform. Specifically, we performed our work on mpiBLAST, a parallel sequence-search code that has been optimized on numerous supercomputing environments. In doing so, we identify several critical performance issues. Consequently, we propose and study different approaches for mapping sequence-search and parallel I/O tasks on such massively parallel architectures. We demonstrate that our optimizations can deliver nearly linear scaling (93 % efficiency) on up to 32,768 cores of BG/P. In addition, we show that such scalability enables us to complete a large-scale bioinformatics problem — sequence searching a microbial genome database against itself to support the discovery of missing genes in genomes — in only a few hours on BG/P. Previously, this problem was viewed as computationally intractable in practice. I.