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 ¡ª sequence 
searching a microbial genome database against itself to 
support the discovery of missing genes in genomes ¡ª in only 
a few hours on BG/P. Previously, this problem was viewed as 
computationally intractable in practice.