An energy‐aware performance analysis of SWIMM: Smith–Waterman implementation on Intel's Multicore and Manycore architectures

Alignment is essential in many areas such as biological, chemical and criminal forensics. The well‐known Smith–Waterman (SW) algorithm is able to retrieve the optimal local alignment with quadratic time and space complexity. There are several implementations that take advantage of computing parallel...

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Detalles Bibliográficos
Autores principales: Rucci, Enzo, García Sanchez, Carlos, Botella, Juan Guillermo, De Giusti, Armando Eduardo, Naiouf, Marcelo, Prieto-Matias, Manuel
Formato: Articulo
Lenguaje:Inglés
Publicado: 2015
Materias:
Ciencias Informáticas
Bioinformatics
Smith-Waterman
HPC
Intel Xeon Phi
Heterogeneous computing
Power consumption
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/82869
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-82869
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Bioinformatics
Smith-Waterman
HPC
Intel Xeon Phi
Heterogeneous computing
Power consumption
spellingShingle Ciencias Informáticas
Bioinformatics
Smith-Waterman
HPC
Intel Xeon Phi
Heterogeneous computing
Power consumption
Rucci, Enzo
García Sanchez, Carlos
Botella, Juan Guillermo
De Giusti, Armando Eduardo
Naiouf, Marcelo
Prieto-Matias, Manuel
An energy‐aware performance analysis of SWIMM: Smith–Waterman implementation on Intel's Multicore and Manycore architectures
topic_facet Ciencias Informáticas
Bioinformatics
Smith-Waterman
HPC
Intel Xeon Phi
Heterogeneous computing
Power consumption
description Alignment is essential in many areas such as biological, chemical and criminal forensics. The well‐known Smith–Waterman (SW) algorithm is able to retrieve the optimal local alignment with quadratic time and space complexity. There are several implementations that take advantage of computing parallelization, such as manycores, FPGAs or GPUs, in order to reduce the alignment effort. In this research, we adapt, develop and tune the SW algorithm named SWIMM on a heterogeneous platform based on Intel's Xeon and Xeon Phi coprocessor. SWIMM is a free tool available in a public git repository https://github.com/enzorucci/SWIMM. We efficiently exploit data and thread‐level parallelism, reaching up to 380 GCUPS on heterogeneous architecture, 350 GCUPS for the isolated Xeon and 50 GCUPS on Xeon Phi. Despite the heterogeneous implementation obtaining the best performance, it is also the most energy‐demanding. In fact, we also present a trade‐off analysis between performance and power consumption. The greenest configuration is based on an isolated multicore system that exploits AVX2 instruction set architecture reaching 1.5 GCUPS/Watts.
format Articulo
Articulo
author Rucci, Enzo
García Sanchez, Carlos
Botella, Juan Guillermo
De Giusti, Armando Eduardo
Naiouf, Marcelo
Prieto-Matias, Manuel
author_facet Rucci, Enzo
García Sanchez, Carlos
Botella, Juan Guillermo
De Giusti, Armando Eduardo
Naiouf, Marcelo
Prieto-Matias, Manuel
author_sort Rucci, Enzo
title An energy‐aware performance analysis of SWIMM: Smith–Waterman implementation on Intel's Multicore and Manycore architectures
title_short An energy‐aware performance analysis of SWIMM: Smith–Waterman implementation on Intel's Multicore and Manycore architectures
title_full An energy‐aware performance analysis of SWIMM: Smith–Waterman implementation on Intel's Multicore and Manycore architectures
title_fullStr An energy‐aware performance analysis of SWIMM: Smith–Waterman implementation on Intel's Multicore and Manycore architectures
title_full_unstemmed An energy‐aware performance analysis of SWIMM: Smith–Waterman implementation on Intel's Multicore and Manycore architectures
title_sort energy‐aware performance analysis of swimm: smith–waterman implementation on intel's multicore and manycore architectures
publishDate 2015
url http://sedici.unlp.edu.ar/handle/10915/82869
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