HMMer-Cell: High Performance Protein Profile Searching on the Cell/B.E. Processor

Abstract

This paper presents HMMer-Cell, an implementation of the computationally intensive bioinformatics application HMMER on the Cell/B.E. multiprocessor architecture. The core of the HMMER workload is the Plan7 Viterbi algorithm, which has a memory requirement of O(N*M) where N is the length of the HMM and M is the length of the input sequence length. The main challenge in implementing the Plan7 Viterbi algorithm on the novel Cell/B.E. multiprocessor is the limited local storage space of the Cell/B.E. SPEs (synergistic processing element). We describe our approach to modifying the Viterbi algorithm to reduce the space complexity from 0(M*N) to O(N). We then proceed to discuss design considerations such as task parallelization and code partitioning, in addition to other optimizations we used to implement HMMer-Cell. We demonstrate near-linear speedup when processing relatively larger HMM profiles; and compare our results to those obtained on commodity x86 processors.