G-MSA - A GPU-based, fast and accurate algorithm for multiple sequence alignment
PBN-AR
Instytucja
Instytut Chemii Bioorganicznej Polskiej Akademii Nauk
Informacje podstawowe
Główny język publikacji
en
Czasopismo
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
ISSN
0743-7315
EISSN
Wydawca
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI
URL
Rok publikacji
2013
Numer zeszytu
1
Strony od-do
32-41
Numer tomu
73
Identyfikator DOI
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Autorzy
(liczba autorów: 4)
Pozostali autorzy
+ 2
Słowa kluczowe
en
Multiple sequence alignment
The T-Coffee algorithm
GPU heuristics
Multiple GPUs applications
Bioinformatics
Streszczenia
Język
en
Treść
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 GPU (Graphics Processing Unit) computing approaches have been proposed lately. These solutions show a great potential of GPU 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 GG-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.
Cechy publikacji
ORIGINAL_ARTICLE
Inne
System-identifier
556020
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