Paper Info
Title
MASA: A Multiplatform Architecture for Sequence Aligners with Block Pruning.
Abstract
Biological sequence alignment is a very popular application in Bioinformatics, used routinely worldwide. Many implementations of biological sequence alignment algorithms have been proposed for multicores, GPUs, FPGAs and CellBEs. These implementations are platform-specific; porting them to other systems requires considerable programming effort. This article proposes and evaluates MASA, a flexible and customizable software architecture that enables the execution of biological sequence alignment applications with three variants (local, global, and semiglobal) in multiple hardware/software platforms with block pruning, which is able to reduce significantly the amount of data processed. To attain our flexibility goals, we also propose a generic version of block pruning and developed multiple parallelization strategies as building blocks, including a new asynchronous dataflow-based parallelization, which may be combined to implement efficient aligners in different platforms. We provide four MASA aligner implementations for multicores (OmpSs and OpenMP), GPU (CUDA), and Intel Phi (OpenMP), showing that MASA is very flexible. The evaluation of our generic block pruning strategy shows that it significantly outperforms the previously proposed block pruning, being able to prune up to 66.5% of the cells when using the new dataflow-based parallelization strategy.
Year
DOI
Venue
2016
10.1145/2858656
TOPC
Field
DocType
Volume
Asynchronous communication,Computer science,Parallel algorithm,CUDA,Xeon Phi,Parallel computing,Theoretical computer science,Software,Dataflow,Porting,Software architecture
Journal
2
Issue
Citations 
PageRank 
4
5
0.47
References 
Authors
29
6
Name
Order
Citations
PageRank
Edans Sandes11298.94
Guillermo Miranda250.47
Xavier Martorell31470125.40
Eduard Ayguadé42406216.00
George Teodoro515022.18
Alba Cristina Magalhaes Alves De Melo625333.90