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MPI framework for parallel searching in large biological databases

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Title: MPI framework for parallel searching in large biological databases
Authors: Battré, Dominic dominic@battre.de, Angulo, David Sigfredo1 dangulo@cti.depaul.edu
Source: Journal of Parallel & Distributed Computing. Dec2006, Vol. 66 Issue 12, p1503-1511. 9p.
Subjects: Information storage & retrieval systems, Databases, Amino acid sequence, Mass spectrometry
Abstract: Abstract: In this paper, we address the problem of searching huge biological databases on the scale of at least several gigabytes by utilizing parallel processing. Biological databases storing DNA sequences, protein sequences, or mass spectra are growing exponentially. Searches through these databases consume exponentially growing computational resources as well. We demonstrate herein a general use, MPI based, framework for generically splitting databases amongst several computational nodes. The combined RAM of the nodes working in tandem is often sufficient to keep the entire database in memory, and therefore to search it efficiently without paging to disk. The framework runs as a persistent service, processing all submitted queries. This allows for query reordering and better utilization of the memory. Thereby, we achieve superlinear speedups compared to single processor implementations. We demonstrate the utility and speedup of the framework using a real biological database and an actual searching algorithm for mass spectrometry. [Copyright &y& Elsevier]
Copyright of Journal of Parallel & Distributed Computing is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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PubType: Academic Journal
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  Data: MPI framework for parallel searching in large biological databases
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  Data: <searchLink fieldCode="AR" term="%22Battré%2C+Dominic%22">Battré, Dominic</searchLink><i> dominic@battre.de</i><br /><searchLink fieldCode="AR" term="%22Angulo%2C+David+Sigfredo%22">Angulo, David Sigfredo</searchLink><relatesTo>1</relatesTo><i> dangulo@cti.depaul.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Parallel+%26+Distributed+Computing%22">Journal of Parallel & Distributed Computing</searchLink>. Dec2006, Vol. 66 Issue 12, p1503-1511. 9p.
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  Data: <searchLink fieldCode="DE" term="%22Information+storage+%26+retrieval+systems%22">Information storage & retrieval systems</searchLink><br /><searchLink fieldCode="DE" term="%22Databases%22">Databases</searchLink><br /><searchLink fieldCode="DE" term="%22Amino+acid+sequence%22">Amino acid sequence</searchLink><br /><searchLink fieldCode="DE" term="%22Mass+spectrometry%22">Mass spectrometry</searchLink>
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  Data: Abstract: In this paper, we address the problem of searching huge biological databases on the scale of at least several gigabytes by utilizing parallel processing. Biological databases storing DNA sequences, protein sequences, or mass spectra are growing exponentially. Searches through these databases consume exponentially growing computational resources as well. We demonstrate herein a general use, MPI based, framework for generically splitting databases amongst several computational nodes. The combined RAM of the nodes working in tandem is often sufficient to keep the entire database in memory, and therefore to search it efficiently without paging to disk. The framework runs as a persistent service, processing all submitted queries. This allows for query reordering and better utilization of the memory. Thereby, we achieve superlinear speedups compared to single processor implementations. We demonstrate the utility and speedup of the framework using a real biological database and an actual searching algorithm for mass spectrometry. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Journal of Parallel & Distributed Computing is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.jpdc.2006.08.003
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      – Code: eng
        Text: English
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      – SubjectFull: Information storage & retrieval systems
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      – SubjectFull: Databases
        Type: general
      – SubjectFull: Amino acid sequence
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      – SubjectFull: Mass spectrometry
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      – TitleFull: MPI framework for parallel searching in large biological databases
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            NameFull: Battré, Dominic
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            NameFull: Angulo, David Sigfredo
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              Text: Dec2006
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