A multi-grained distributed implementation of the parallel Block Conjugate Gradient algorithm

The Block Conjugate Gradient algorithm (Block‐CG) was developed to solve sparse linear systems of equations that have multiple right‐hand sides. We have adapted it for use in heterogeneous, geographically distributed, parallel architectures. Once the main operations of the Block‐CG (Tasks) have been...

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Veröffentlicht in:Concurrency and computation Jg. 22; H. 15; S. 2053 - 2072
Hauptverfasser: Murli, A., D'Amore, L., Laccetti, G., Gregoretti, F., Oliva, G.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Chichester, UK John Wiley & Sons, Ltd 01.10.2010
Schlagworte:
Algorithms
Block Conjugate Gradient
Blocking
Concurrency
Conjugate gradients
Linear systems
Mathematical analysis
Middleware
multi-grained parallelism
parallel and distributed algorithm
Tasks
ISSN:1532-0626, 1532-0634, 1532-0634
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Zusammenfassung:The Block Conjugate Gradient algorithm (Block‐CG) was developed to solve sparse linear systems of equations that have multiple right‐hand sides. We have adapted it for use in heterogeneous, geographically distributed, parallel architectures. Once the main operations of the Block‐CG (Tasks) have been collected into smaller groups (subjobs), each subjob is matched by the middleware MJMS (MPI Jobs Management System) with a suitable resource selected among those which are available. Moreover, within each subjob, concurrency is introduced at two different levels and with two different granularities: the coarse‐grained parallelism to perform independent tasks and the fine‐grained parallelism within the execution of a task. We refer to this algorithm as to multi‐grained distributed implementation of the parallel Block‐CG. We compare the performance of a parallel implementation with the one of the distributed implementation running on a variety of Grid computing environments. The middleware MJMS—developed by some of the authors and built on top of Globus Toolkit and Condor‐G—was used for co‐allocation, synchronization, scheduling and resource selection. Copyright © 2010 John Wiley & Sons, Ltd.
Bibliographie:ark:/67375/WNG-SSD41004-9
ArticleID:CPE1548
MIUR-PON S.Co.P.E. Italian National Project
istex:0D211C5FE92447A6770226A2DA353DB3F16A0962
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1532-0626
1532-0634
1532-0634
DOI:10.1002/cpe.1548