Title
A HMMER hardware accelerator using divergences
Abstract
As new protein sequences are discovered on an everyday basis and protein databases continue to grow exponentially with time, computational tools take more and more time to search protein databases to discover the common ancestors of them. HMMER is among the most used tools in protein search and comparison and multiple efforts have been made to accelerate its execution by using dedicated hardware prototyped on FPGAs. In this paper we introduce a novel algorithm called the Divergence Algorithm, which not only enables the FPGA accelerator to reduce execution time, but also enables further acceleration of the alignment generation algorithm of the HMMER programs by reducing the number of cells of the Dynamic Programming matrices it has to calculate. We also propose a more accurate performance measurement strategy that considers all the execution times while doing protein searches and alignments, while other works only consider hardware execution times and do not include alignment generation times. Using our proposed hardware accelerator and the Divergence Algorithm, we were able to achieve gains up to 182x when compared to the unaccelerated HMMER software running on a general purpose CPU.
Year
DOI
Venue
2010
10.1109/DATE.2010.5457169
DATE
Keywords
Field
DocType
biology computing,dynamic programming,field programmable gate arrays,matrix algebra,proteins,FPGA accelerator,HMMER hardware accelerator,HMMER programs,alignment generation time,computational tools,divergence algorithm,dynamic programming matrices,hardware execution time,performance measurement,protein databases,protein search,protein sequences,Bioinformatics,FPGA,HMMER,Hardware accelerator,Hidden Markov Models
Dynamic programming,Computer science,Parallel computing,Field-programmable gate array,Real-time computing,Software,Acceleration,Hardware acceleration,Hidden Markov model,Protein Databases,Viterbi algorithm
Conference
ISSN
Citations 
PageRank 
1530-1591
2
0.38
References 
Authors
9
4