CUDASW++ 3.0 : accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Publikationstyp:
Zeitschriftenaufsatz
Metadaten:
Autoren
Sammlungen
  • metadata
ISSN
1471-2105
Zeitschrift
BMC bioinformatics
Schlüsselwörter
  • 004 Informatik
  • 004 Data processing
Sprache
eng
Paginierung
Art. 117
Datum der Veröffentlichung
2013
Herausgeber
BioMed Central
Herausgeber URL
http://dx.doi.org/10.1186/1471-2105-14-117
Datum der Datenerfassung
2020
Datum, an dem der Datensatz öffentlich gemacht wurde
2020
Zugang
Public
Titel
CUDASW++ 3.0 : accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions
Ausgabe der Zeitschrift
14

Datenquelle: METADATA.UB

Andere Metadatenquellen:
Autoren
Autoren-URL
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000318489400001&DestLinkType=FullRecord&DestApp=WOS_CPL
DOI
10.1186/1471-2105-14-117
Externe Identifier
  • Clarivate Analytics Document Solution ID: 138DS
  • PubMed Identifier: 23557111
ISSN
1471-2105
Zeitschrift
BMC BIOINFORMATICS
Schlüsselwörter
  • Smith-Waterman
  • CUDA
  • GPU
  • PTX SIMD instructions
  • Concurrent execution
Artikelnummer
ARTN 117
Datum der Veröffentlichung
2013
Status
Published
Titel
CUDASW++3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions
Sub types
  • Article
Ausgabe der Zeitschrift
14

Datenquelle: Web of Science (Lite)

Autoren
DOI
10.1186/1471-2105-14-117
eISSN
1471-2105
Ausgabe der Veröffentlichung
1
Zeitschrift
BMC Bioinformatics
Sprache
en
Artikelnummer
117
Online publication date
2013
Datum der Veröffentlichung
2013
Status
Published
Herausgeber
Springer Science and Business Media LLC
Herausgeber URL
http://dx.doi.org/10.1186/1471-2105-14-117
Datum der Datenerfassung
2019
Titel
CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions
Ausgabe der Zeitschrift
14

Datenquelle: Crossref

Abstract
<h4>Background</h4>The maximal sensitivity for local alignments makes the Smith-Waterman algorithm a popular choice for protein sequence database search based on pairwise alignment. However, the algorithm is compute-intensive due to a quadratic time complexity. Corresponding runtimes are further compounded by the rapid growth of sequence databases.<h4>Results</h4>We present CUDASW++ 3.0, a fast Smith-Waterman protein database search algorithm, which couples CPU and GPU SIMD instructions and carries out concurrent CPU and GPU computations. For the CPU computation, this algorithm employs SSE-based vector execution units as accelerators. For the GPU computation, we have investigated for the first time a GPU SIMD parallelization, which employs CUDA PTX SIMD video instructions to gain more data parallelism beyond the SIMT execution model. Moreover, sequence alignment workloads are automatically distributed over CPUs and GPUs based on their respective compute capabilities. Evaluation on the Swiss-Prot database shows that CUDASW++ 3.0 gains a performance improvement over CUDASW++ 2.0 up to 2.9 and 3.2, with a maximum performance of 119.0 and 185.6 GCUPS, on a single-GPU GeForce GTX 680 and a dual-GPU GeForce GTX 690 graphics card, respectively. In addition, our algorithm has demonstrated significant speedups over other top-performing tools: SWIPE and BLAST+.<h4>Conclusions</h4>CUDASW++ 3.0 is written in CUDA C++ and PTX assembly languages, targeting GPUs based on the Kepler architecture. This algorithm obtains significant speedups over its predecessor: CUDASW++ 2.0, by benefiting from the use of CPU and GPU SIMD instructions as well as the concurrent execution on CPUs and GPUs. The source code and the simulated data are available at http://cudasw.sourceforge.net.
Addresses
  • Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz, Germany. liuy@uni-mainz.de
Autoren
DOI
10.1186/1471-2105-14-117
eISSN
1471-2105
Externe Identifier
  • PubMed Identifier: 23557111
  • PubMed Central ID: PMC3637623
Open access
true
ISSN
1471-2105
Zeitschrift
BMC bioinformatics
Schlüsselwörter
  • Sequence Alignment
  • Sequence Analysis, Protein
  • Algorithms
  • Software
  • Databases, Protein
Sprache
eng
Medium
Electronic
Online publication date
2013
Open access status
Open Access
Paginierung
117
Datum der Veröffentlichung
2013
Status
Published
Publisher licence
CC BY
Datum der Datenerfassung
2013
Titel
CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions.
Sub types
  • research-article
  • Evaluation Study
  • Journal Article
Ausgabe der Zeitschrift
14

Files

https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/1471-2105-14-117 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23557111/pdf/?tool=EBI https://europepmc.org/articles/PMC3637623?pdf=render

Datenquelle: Europe PubMed Central

Abstract
BACKGROUND: The maximal sensitivity for local alignments makes the Smith-Waterman algorithm a popular choice for protein sequence database search based on pairwise alignment. However, the algorithm is compute-intensive due to a quadratic time complexity. Corresponding runtimes are further compounded by the rapid growth of sequence databases. RESULTS: We present CUDASW++ 3.0, a fast Smith-Waterman protein database search algorithm, which couples CPU and GPU SIMD instructions and carries out concurrent CPU and GPU computations. For the CPU computation, this algorithm employs SSE-based vector execution units as accelerators. For the GPU computation, we have investigated for the first time a GPU SIMD parallelization, which employs CUDA PTX SIMD video instructions to gain more data parallelism beyond the SIMT execution model. Moreover, sequence alignment workloads are automatically distributed over CPUs and GPUs based on their respective compute capabilities. Evaluation on the Swiss-Prot database shows that CUDASW++ 3.0 gains a performance improvement over CUDASW++ 2.0 up to 2.9 and 3.2, with a maximum performance of 119.0 and 185.6 GCUPS, on a single-GPU GeForce GTX 680 and a dual-GPU GeForce GTX 690 graphics card, respectively. In addition, our algorithm has demonstrated significant speedups over other top-performing tools: SWIPE and BLAST+. CONCLUSIONS: CUDASW++ 3.0 is written in CUDA C++ and PTX assembly languages, targeting GPUs based on the Kepler architecture. This algorithm obtains significant speedups over its predecessor: CUDASW++ 2.0, by benefiting from the use of CPU and GPU SIMD instructions as well as the concurrent execution on CPUs and GPUs. The source code and the simulated data are available at http://cudasw.sourceforge.net.
Date of acceptance
2013
Autoren
Autoren-URL
https://www.ncbi.nlm.nih.gov/pubmed/23557111
DOI
10.1186/1471-2105-14-117
eISSN
1471-2105
Externe Identifier
  • PubMed Central ID: PMC3637623
Zeitschrift
BMC Bioinformatics
Schlüsselwörter
  • Algorithms
  • Databases, Protein
  • Sequence Alignment
  • Sequence Analysis, Protein
  • Software
Sprache
eng
Country
England
Paginierung
117
PII
1471-2105-14-117
Datum der Veröffentlichung
2013
Status
Published online
Datum, an dem der Datensatz öffentlich gemacht wurde
2013
Titel
CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions.
Sub types
  • Evaluation Study
  • Journal Article
Ausgabe der Zeitschrift
14

Datenquelle: PubMed

Autoren
Zeitschrift
BMC Bioinform.
Paginierung
117 - 117
Datum der Veröffentlichung
2013
Titel
CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions.
Ausgabe der Zeitschrift
14

Datenquelle: DBLP

Author's licence
CC-BY
Autoren
Hosting institution
Universitätsbibliothek Mainz
Sammlungen
  • DFG-OA-Publizieren (2012 - 2017)
Resource version
Published version
DOI
10.1186/1471-2105-14-117
Funding acknowledgements
  • DFG, Open Access-Publizieren Universität Mainz / Universitätsmedizin
File(s) embargoed
false
Open access
true
ISSN
1471-2105
Zeitschrift
BMC bioinformatics
Schlüsselwörter
  • 004 Informatik
  • 004 Data processing
Sprache
eng
Open access status
Open Access
Paginierung
Art. 117
Datum der Veröffentlichung
2013
Public URL
https://openscience.ub.uni-mainz.de/handle/20.500.12030/7189
Herausgeber
BioMed Central
Herausgeber URL
http://dx.doi.org/10.1186/1471-2105-14-117
Datum der Datenerfassung
2022
Datum, an dem der Datensatz öffentlich gemacht wurde
2022
Zugang
Public
Titel
CUDASW++ 3.0 : accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions
Ausgabe der Zeitschrift
14

Files

cudasw_30___accelerating_smit-20220616161227871.pdf

Datenquelle: OPENSCIENCE.UB

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