Enhancing parallelism of data-intensive bioinformatics applications

Zheng Xie; Liangxiu Han; Richard Baldock

doi:10.1109/EUROSIM.2013.93

Enhancing parallelism of data-intensive bioinformatics applications

Zheng Xie, Liangxiu Han, Richard Baldock

Deanery of Molecular, Genetic and Population Health Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Bioinformatics data-resources collected from heterogeneous and distributed sources can contain hundreds of Terra-Bytes and the efficient exploration on these large amounts of data is a critical task to enable scientists to gain new biological insight. In this work, an MPI-based parallel architecture has been designed for enhancing performance of biomedical data intensive applications. The experiment results show the system has achieved super-linear speedup and high scalability.

Original language	English
Title of host publication	Proceedings - 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013
Publisher	Institute of Electrical and Electronics Engineers
Pages	519-524
Number of pages	6
ISBN (Print)	9780769550732
DOIs	https://doi.org/10.1109/EUROSIM.2013.93
Publication status	Published - 8 Jan 2015
Event	8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013 - Cardiff, Wales, United Kingdom Duration: 10 Sept 2013 → 13 Sept 2013

Conference

Conference	8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013
Country/Territory	United Kingdom
City	Cardiff, Wales
Period	10/09/13 → 13/09/13

Keywords / Materials (for Non-textual outputs)

collective/point-to-point communicators
data intensive application
fine-grain parallelism
gene pattern recognition
high scalability
Message Passing Interface
super-linear speedup
task/data parallelisms

Access to Document

10.1109/EUROSIM.2013.93

Cite this

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title = "Enhancing parallelism of data-intensive bioinformatics applications",

abstract = "Bioinformatics data-resources collected from heterogeneous and distributed sources can contain hundreds of Terra-Bytes and the efficient exploration on these large amounts of data is a critical task to enable scientists to gain new biological insight. In this work, an MPI-based parallel architecture has been designed for enhancing performance of biomedical data intensive applications. The experiment results show the system has achieved super-linear speedup and high scalability.",

keywords = "collective/point-to-point communicators, data intensive application, fine-grain parallelism, gene pattern recognition, high scalability, Message Passing Interface, super-linear speedup, task/data parallelisms",

author = "Zheng Xie and Liangxiu Han and Richard Baldock",

year = "2015",

month = jan,

day = "8",

doi = "10.1109/EUROSIM.2013.93",

language = "English",

isbn = "9780769550732",

pages = "519--524",

booktitle = "Proceedings - 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013 ; Conference date: 10-09-2013 Through 13-09-2013",

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Xie, Z, Han, L & Baldock, R 2015, Enhancing parallelism of data-intensive bioinformatics applications. in Proceedings - 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013., 7004997, Institute of Electrical and Electronics Engineers, pp. 519-524, 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013, Cardiff, Wales, United Kingdom, 10/09/13. https://doi.org/10.1109/EUROSIM.2013.93

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AU - Han, Liangxiu

AU - Baldock, Richard

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N2 - Bioinformatics data-resources collected from heterogeneous and distributed sources can contain hundreds of Terra-Bytes and the efficient exploration on these large amounts of data is a critical task to enable scientists to gain new biological insight. In this work, an MPI-based parallel architecture has been designed for enhancing performance of biomedical data intensive applications. The experiment results show the system has achieved super-linear speedup and high scalability.

AB - Bioinformatics data-resources collected from heterogeneous and distributed sources can contain hundreds of Terra-Bytes and the efficient exploration on these large amounts of data is a critical task to enable scientists to gain new biological insight. In this work, an MPI-based parallel architecture has been designed for enhancing performance of biomedical data intensive applications. The experiment results show the system has achieved super-linear speedup and high scalability.

KW - collective/point-to-point communicators

KW - data intensive application

KW - fine-grain parallelism

KW - gene pattern recognition

KW - high scalability

KW - Message Passing Interface

KW - super-linear speedup

KW - task/data parallelisms

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U2 - 10.1109/EUROSIM.2013.93

DO - 10.1109/EUROSIM.2013.93

M3 - Conference contribution

AN - SCOPUS:84929590866

SN - 9780769550732

SP - 519

EP - 524

BT - Proceedings - 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013

PB - Institute of Electrical and Electronics Engineers

T2 - 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013

Y2 - 10 September 2013 through 13 September 2013

ER -

Enhancing parallelism of data-intensive bioinformatics applications

Abstract

Conference

Keywords / Materials (for Non-textual outputs)

Access to Document

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