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Efficient Acceleration of the Pair-HMMs Forward Algorithm for GATK HaplotypeCaller on Graphics Processing Units.
Ren, Shanshan; Bertels, Koen; Al-Ars, Zaid.
Afiliación
  • Ren S; Computer Engineering Lab, Delft University of Technology, Delft, The Netherlands.
  • Bertels K; Computer Engineering Lab, Delft University of Technology, Delft, The Netherlands.
  • Al-Ars Z; Computer Engineering Lab, Delft University of Technology, Delft, The Netherlands.
Evol Bioinform Online ; 14: 1176934318760543, 2018.
Article en En | MEDLINE | ID: mdl-29568218
ABSTRACT
GATK HaplotypeCaller (HC) is a popular variant caller, which is widely used to identify variants in complex genomes. However, due to its high variants detection accuracy, it suffers from long execution time. In GATK HC, the pair-HMMs forward algorithm accounts for a large percentage of the total execution time. This article proposes to accelerate the pair-HMMs forward algorithm on graphics processing units (GPUs) to improve the performance of GATK HC. This article presents several GPU-based implementations of the pair-HMMs forward algorithm. It also analyzes the performance bottlenecks of the implementations on an NVIDIA Tesla K40 card with various data sets. Based on these results and the characteristics of GATK HC, we are able to identify the GPU-based implementations with the highest performance for the various analyzed data sets. Experimental results show that the GPU-based implementations of the pair-HMMs forward algorithm achieve a speedup of up to 5.47× over existing GPU-based implementations.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Evol Bioinform Online Año: 2018 Tipo del documento: Article País de afiliación: Países Bajos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Evol Bioinform Online Año: 2018 Tipo del documento: Article País de afiliación: Países Bajos