Enabling e-science applications on the cloud with COMPSs

Authors:
Daniele Lezzi;Roger Rafanell;Abel Carrión;Ignacio Blanquer Espert;Vicente Hernández;Rosa M. Badia
Affiliations:
Barcelona Supercomputing Center, Centro Nacional de Supercomputación (BSC-CNS), Spain and Universitat Politècnica de Catalunya (UPC), Spain;Barcelona Supercomputing Center, Centro Nacional de Supercomputación (BSC-CNS), Spain;Instituto de Instrumentación para Imagen Molecular (I3M), Centro mixto CSIC, Universitat Politècnica de València, CIEMAT, Spain;Instituto de Instrumentación para Imagen Molecular (I3M), Centro mixto CSIC, Universitat Politècnica de València, CIEMAT, Spain;Instituto de Instrumentación para Imagen Molecular (I3M), Centro mixto CSIC, Universitat Politècnica de València, CIEMAT, Spain;Barcelona Supercomputing Center, Centro Nacional de Supercomputación (BSC-CNS), Spain and Spanish Council for Scientific Research (CSIC), Artificial Intelligence Research Institute (IIIA), Sp ...
Venue:
Euro-Par'11 Proceedings of the 2011 international conference on Parallel Processing
Year:
2011

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Abstract

COMP Superscalar (COMPSs) is a programming framework that provides an easy-to-use programming model and a runtime to ease the development of applications for distributed environments. Thanks to its modular architecture COMPSs can use a wide range of computational infrastructures providing a uniform interface for job submission and file transfer operations through adapters for different middlewares. In the context of the VENUS-C project the COMPSs framework has been extended through the development of a programming model enactment service that allows researcher to transparently port and execute scientific applications in the Cloud. This paper presents the implementation of a bioinformatics workflow (using BLAST as core program), the porting to the COMPSs framework and its deployment on the VENUS-C platform. The proposed approach has been evaluated on a Cloud testbed using virtual machines managed by EMOTIVE Cloud and compared to a similar approach on the Azure platform and to other implementations on HPC infrastructures.