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Nimrod/K: Towards Massively Parallel Dynamic Grid Workflows (2008)
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| Venue: | Conference on High Performance Networking and Computation, Proceedings of the 2008 ACM/IEEE Conference on Supercomputing |
| Citations: | 18 - 7 self |
BibTeX
@INPROCEEDINGS{Abramson08nimrod/k:towards,
author = {David Abramson and Colin Enticott and Ilkay Altinas},
title = {Nimrod/K: Towards Massively Parallel Dynamic Grid Workflows},
booktitle = {Conference on High Performance Networking and Computation, Proceedings of the 2008 ACM/IEEE Conference on Supercomputing},
year = {2008},
pages = {1--11}
}
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Abstract
A challenge for Grid computing is the difficulty in developing software that is parallel, distributed and highly dynamic. Whilst there have been many general purpose mechanisms developed over the years, Grid programming still remains a low level, error prone task. Scientific workflow engines can double as programming environments, and allow a user to compose ‘virtual ’ Grid applications from pre-existing components. Whilst existing workflow can specify arbitrary parallel programs, (where components use message passing) they are typically not effective with large and variable parallelism. Here we discuss dynamic dataflow, originally developed for parallel tagged dataflow architectures (TDAs), and show that these can be used for implementing Grid workflows. TDAs spawn parallel threads dynamically without additional programming. We have added TDAs to Kepler, and show that the system can orchestrate workflows that have large amounts of variable parallelism. We demonstrate the system using case studies in chemistry and in cardiac modelling. 1
Keyphrases
parallel dynamic grid workflow variable parallelism additional programming dataflow architecture arbitrary parallel program prone task tdas spawn parallel thread case study pre-existing component dynamic dataflow many general purpose mechanism grid computing cardiac modelling grid workflow low level large amount programming environment virtual grid application message passing
