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.
10b6eb66-e3c5-4c9f-9bcf-3df48d76e9b0
Frey, J.G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Essex, J.W.
1f409cfe-6ba4-42e2-a0ab-a931826314b5
2004
Woods, C.J.
10b6eb66-e3c5-4c9f-9bcf-3df48d76e9b0
Frey, J.G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Essex, J.W.
1f409cfe-6ba4-42e2-a0ab-a931826314b5
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.
.
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.
More information
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
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Date deposited: 07 Jun 2005
Last modified: 16 Mar 2024 02:45
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Contributors
Author:
C.J. Woods
Editor:
S. Cox
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