G-MSA - A GPU-based, fast and accurate algorithm for multiple sequence alignment
Multiple sequence alignment (MSA) methods are essential in biological analysis. Several MSA algorithms have been proposed in recent years. The quality of the results produced by those methods is reasonable, but there is no single method that consistently outperforms others. Additionally, the increasing number of sequences in the biological databases is perceived as one of the upcoming challenges for alignment methods in the nearest future. The lack of performance concerns not only the alignment problems, but may be observed in many areas of biologically related research. To overcome this problem in the field of pairwise alignment, several CPU (Graphics Processing Unit) computing approaches have been proposed lately. These solutions show a great potential of CPU platform. Therefore, our main idea was to design and implement an MSA method which can take advantage of modern graphics cards. Our solution is based on T-Coffee - well known for its high accuracy MSA algorithm. Its computational time, however, is often unacceptable. Performed tests show that our method, named G-MSA, is highly efficient achieving up to 193-fold speedup on a single GPU while the quality of its results remains very good. Due to effective memory usage the method can perform alignment for huge sets of sequences that previously could only be aligned on computer clusters. Moreover, multiple GPUs support with load balancing makes the application very scalable. (C) 2012 Elsevier Inc. All rights reserved.
multiple sequence alignment the t-coffee algorithm gpu heuristics multiple gpus applications bioinformatics