Article
Many task computing for orthologous genes identification in protozoan genomes using Hydra
Registro en:
COUTINHO, Fábio; et al. Many task computing for orthologous genes identification in protozoan genomes using Hydra. Concurrency and Computation: Practice and Experience, v.23, n.17, p.2326-2337, Dec. 2011.
1532-0626
10.1002/cpe.1786
1532-0634
Autor
Coutinho, Fábio
Ogasawara, Eduardo
Oliveira, Daniel de
Barganholo, Vanessa
Lima, Alexandre A. B.
Dávila, Alberto M. R.
Mattoso, Marta
Resumen
One of the main advantages of using a scientific workflow management system (SWfMS) is to orchestrate
data flows among scientific activities and register provenance of the whole workflow execution. Nevertheless,
the execution control of distributed activities in high performance computing environments by SWfMS
presents challenges such as steering control and provenance gathering. Such challenges may become a
complex task to be accomplished in bioinformatics experiments, particularly in Many Task Computing scenarios.
This paper presents a data parallelism solution for a bioinformatics experiment supported by Hydra,
a middleware that bridges SWfMS and high performance computing to enable workflow parallelization with
provenance gathering. Hydra Many Task Computing parallelization strategies can be registered and reused.
Using Hydra, provenance may also be uniformly gathered. We have evaluated Hydra using an Orthologous
Gene Identification workflow. Experimental results show that a systematic approach for distributing parallel
activities is viable, sparing scientist time and diminishing operational errors, with the additional benefits of
distributed provenance support. 2030-01-01