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The Application of Distributed Computing to the Investigation of Protein Conformational Change

The Application of Distributed Computing to the Investigation of Protein Conformational Change
The Application of Distributed Computing to the Investigation of Protein Conformational Change
Distributed computing is a potentially very powerful approach for accessing large amounts of computational power. Under the umbrella of the comb-e-chem project we have examined distributed computing software and applied it to the problem of investigating protein conformational change. These investigations required the development of protein simulations that were suited to distributed computing. Each simulation was split into many coupled, parallel parts. These proved challenging to schedule on the flexible and unreliable distributed computing resource. Scheduling algorithms were thus written that identified which parts of the simulation were likely to impact the overall efficiency. These parts were then rescheduled to be ‘caught-up’ via a fast and dedicated cluster.
1904425216
(6pp)
Engineering and Physical Sciences Research Council
Woods, C.J.
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Frey, J.G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Essex, J.W.
1f409cfe-6ba4-42e2-a0ab-a931826314b5
Cox, S.
Woods, C.J.
10b6eb66-e3c5-4c9f-9bcf-3df48d76e9b0
Frey, J.G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Essex, J.W.
1f409cfe-6ba4-42e2-a0ab-a931826314b5
Cox, S.

Woods, C.J., Frey, J.G. and Essex, J.W. (2004) The Application of Distributed Computing to the Investigation of Protein Conformational Change. Cox, S. (ed.) In Proceedings of the UK e-Science All Hands Meeting, Sep 2003. Engineering and Physical Sciences Research Council. (6pp) .

Record type: Conference or Workshop Item (Paper)

Abstract

Distributed computing is a potentially very powerful approach for accessing large amounts of computational power. Under the umbrella of the comb-e-chem project we have examined distributed computing software and applied it to the problem of investigating protein conformational change. These investigations required the development of protein simulations that were suited to distributed computing. Each simulation was split into many coupled, parallel parts. These proved challenging to schedule on the flexible and unreliable distributed computing resource. Scheduling algorithms were thus written that identified which parts of the simulation were likely to impact the overall efficiency. These parts were then rescheduled to be ‘caught-up’ via a fast and dedicated cluster.

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Published date: 2004
Venue - Dates: UK e-Science All Hands Meeting, Nottingham, UK, 2004-09-06 - 2004-09-06

Identifiers

Local EPrints ID: 15881
URI: http://eprints.soton.ac.uk/id/eprint/15881
ISBN: 1904425216
PURE UUID: e79b0830-fd5d-4b86-89cb-ba575ac5d05a
ORCID for J.G. Frey: ORCID iD orcid.org/0000-0003-0842-4302
ORCID for J.W. Essex: ORCID iD orcid.org/0000-0003-2639-2746

Catalogue record

Date deposited: 07 Jun 2005
Last modified: 16 Mar 2024 02:45

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Contributors

Author: C.J. Woods
Author: J.G. Frey ORCID iD
Author: J.W. Essex ORCID iD
Editor: S. Cox

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