Efficient Parallel Implementations of Multiple Sequence Alignment using BSP/CGM Model

Vasconcellos, Jucele F. A.; Nishibe, Christiane; Almeida, Nalvo F.; Cáceres, Edson Norberto

doi:10.1145/2578948.2560698

Cited by 3 publications

(3 citation statements)

References 26 publications

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“…26 used other application for MSA called the center star method proposed by Gus¯eld. 27 They also evaluate the performance with two di®erent implementations (i.e., MPI and CUDA) on Clusters and GPGPUs.…”

Section: Related Workmentioning

confidence: 99%

Parallel PPI Prediction Performance Study on HPC Platforms

El-Moursy

Afifi

Sibai

et al. 2015

J CIRCUIT SYST COMP

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STRIKE is an algorithm which predicts protein-protein interactions (PPIs) and determines that proteins interact if they contain similar substrings of amino acids. Unlike other methods for PPI prediction, STRIKE is able to achieve reasonable improvement over the existing PPI prediction methods. Although its high accuracy as a PPI prediction method, STRIKE consumes a large execution time and hence it is considered to be a compute-intensive application. In this paper, we develop and implement a parallel STRIKE algorithm for high-performance computing (HPC) systems. Using a large-scale cluster, the execution time of the parallel implementation of this bioinformatics algorithm was reduced from about a week on a serial uniprocessor machine to about 16.5 h on 16 computing nodes, down to about 2 h on 128 parallel nodes. Communication overheads between nodes are thoroughly studied.

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Section: Related Workmentioning

confidence: 99%

Parallel PPI Prediction Performance Study on HPC Platforms

El-Moursy

Afifi

Sibai

et al. 2015

J CIRCUIT SYST COMP

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“…Hence, it's necessary to implement parallel solutions in MSA. Jucele F. A. et al [44] present two parallel solutions using the BSP/CGM model, with MPI and CUDA implementations. And the results of this method show that the use of parallel processing allows the manipulation of more and larger sequences.…”

Section: Conclusion and Future Developmentmentioning

confidence: 99%

A Survey of Multiple Sequence Alignment Techniques

Wang

Liu

et al. 2015

Intelligent Computing Theories and Methodologies

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Abstract. Multiple sequence alignment (MSA) is a basic step in many bioinformatics analyses, and also a NP-hard problem. In order to improve the speed, accuracy and cater to the requirement of large-scale sequences alignment, a wide variety of MSA methods and softwares have been subsequently developed. In this article, we will systematically review the wildly used methods and introduce their practical results on the benchmark Balibase 3.0 references. We come to the conclusion that computational complexity still is the bottleneck of MSA. We also consider future development of MSA methods with respect to applying of more different technologies and the prospect of parallelization of MSA.

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“…Em um deles (VASCONCELLOS et al, 2014), é apresentada uma proposta de algoritmo paralelo utilizando o modelo de programação BSP, com implementações em MPI e Compute Unified Device Architecture (CUDA), possibilitando a manipulação de um número maior de sequências, além disso, sequências com tamanhos maiores.…”

Section: Alinhamento Múltiplo De Sequênciasunclassified

Metodologia para execução de aplicações paralelas baseadas no modelo BSP com tarefas heterogêneas.

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Efficient Parallel Implementations of Multiple Sequence Alignment using BSP/CGM Model

Cited by 3 publications

References 26 publications

Parallel PPI Prediction Performance Study on HPC Platforms

Parallel PPI Prediction Performance Study on HPC Platforms

A Survey of Multiple Sequence Alignment Techniques

Metodologia para execução de aplicações paralelas baseadas no modelo BSP com tarefas heterogêneas.

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