Parallel Large Scale Simulations in the PL-Grid Environment
Kurowski Krzysztof, Piontek Tomasz, Kopta Piotr, Mamoński Mariusz, Bosak Bartosz
Poznań Supercomputing and Networking Center, Poznań, Poland
e-mail: {kurowski/piontek/pkopta/mamonski/bbosak}@man.poznan.pl
Received:
Received: 25 August 2010; revised: 29 October 2010; published online: 23 November 2010
DOI: 10.12921/cmst.2010.SI.01.47-56
OAI: oai:lib.psnc.pl:685
Abstract:
The growing demand for computational power causes that Grids are becoming mission-critical components in research and industry, offering sophisticated solutions in leveraging large-scale computing and storage resources. The nature a Grid in which resources are usually shared among multiple organizations offering resources under their control based on the “best effort” approach with no guarantee concerning the quality-of-service may be inadequate to support large-scale simulations. Requirements of such simulations often exceed capabilities of a single computing center causing the need to simultaneously allocate and synchronize resources belonging to many administrative domains whose functionality is missing in leading grid middlewares preventing researchers from executing large-scale simulations in grids. The paper presents tools and services that were designed to build multilayered infrastructure
capable of dealing with computationally intensive large-scale simulations in the grid environment. The developed and deployed middleware enables computing clusters in different administrative domains to be virtually welded into a single powerful compute resource that can be treated as a quasi-opportunistic supercomputer. We describe the middleware developed in the QosCosGrid project and being enhanced under the PL-Grid national grid initiative, which provides advance reservation and resource co-allocation functionality as well as support for parallel large-scale applications based on OpenMPI (for C/C++ and Fortran) or ProActive for Java.
Key words:
References:
[1] Quasi Opportunistic Supercomputing for Complex Systems in Grid Environments. http://www.qoscosgrid.eu/
[2] Polish Infrastructure for Information Science Support in the European Research Space PL-Grid. http://www.plgrid.pl/en
[3] E. Gabriel, G.E. Fagg, G. Bosilca, T. Angskun, J.J. Dongarra, J.M. Squyres, V. Sahay, P. Kambadur, B. Barrett, Lumsdaine, R.H. Castain, D.J. Daniel, R.L. Graham, T.S. Woodal, Open MPI: Goals, Concept, and Design of a Next Generation MPI Implementation, Proceedings, 11th European PVM/MPI Users’ Group Meeting.
[4] D. Caromel, C. Delbe, A. di Costanzo, M. Leyton, Pro- Active: an Integrated Platform for Programming and Running Applications on Grids and P2P systems. Computational Methods in Science and Technology 12 (1), 69-77 (2006).
[5] Open DRMAA Service Provider. http://sourceforge.net/projects/opendsp/
[6] OGF DRMAA Working Group, http://www.drmaa.org/
[7] GFD 114-HPC Basic Profile, Version 1.0. http://www.ogf.org/documents/GFD.114.pdf
[8] OASIS Web Services Notification (WSN) Technical Committee. http://www.oasisopen. org/committees/tc_home.php?wg_abbrev=wsn
[9] K. Kurowski, J. Nabrzyski, A. Oleksiak, J. Węglarz, Grid scheduling simulations with GSSIM. In Proceedings of the International Conference on Parallel and Distributed Systems, IEEE, 2:1–8, 2007. http://www.computer.org/ portal/web/csdl/doi/10.1109/ICPADS.2007.4447835
[10] Vine Toolkit, A better way to use the Grid. http://vinetoolkit.org/
[11] X. Gonzea, B. Amadond, P.M. Anglade et al., ABINIT: First-principles approach to material and nanosystem properties. Computer Phys. Commun. 180, 2582-2615 (2009).
The growing demand for computational power causes that Grids are becoming mission-critical components in research and industry, offering sophisticated solutions in leveraging large-scale computing and storage resources. The nature a Grid in which resources are usually shared among multiple organizations offering resources under their control based on the “best effort” approach with no guarantee concerning the quality-of-service may be inadequate to support large-scale simulations. Requirements of such simulations often exceed capabilities of a single computing center causing the need to simultaneously allocate and synchronize resources belonging to many administrative domains whose functionality is missing in leading grid middlewares preventing researchers from executing large-scale simulations in grids. The paper presents tools and services that were designed to build multilayered infrastructure
capable of dealing with computationally intensive large-scale simulations in the grid environment. The developed and deployed middleware enables computing clusters in different administrative domains to be virtually welded into a single powerful compute resource that can be treated as a quasi-opportunistic supercomputer. We describe the middleware developed in the QosCosGrid project and being enhanced under the PL-Grid national grid initiative, which provides advance reservation and resource co-allocation functionality as well as support for parallel large-scale applications based on OpenMPI (for C/C++ and Fortran) or ProActive for Java.
Key words:
References:
[1] Quasi Opportunistic Supercomputing for Complex Systems in Grid Environments. http://www.qoscosgrid.eu/
[2] Polish Infrastructure for Information Science Support in the European Research Space PL-Grid. http://www.plgrid.pl/en
[3] E. Gabriel, G.E. Fagg, G. Bosilca, T. Angskun, J.J. Dongarra, J.M. Squyres, V. Sahay, P. Kambadur, B. Barrett, Lumsdaine, R.H. Castain, D.J. Daniel, R.L. Graham, T.S. Woodal, Open MPI: Goals, Concept, and Design of a Next Generation MPI Implementation, Proceedings, 11th European PVM/MPI Users’ Group Meeting.
[4] D. Caromel, C. Delbe, A. di Costanzo, M. Leyton, Pro- Active: an Integrated Platform for Programming and Running Applications on Grids and P2P systems. Computational Methods in Science and Technology 12 (1), 69-77 (2006).
[5] Open DRMAA Service Provider. http://sourceforge.net/projects/opendsp/
[6] OGF DRMAA Working Group, http://www.drmaa.org/
[7] GFD 114-HPC Basic Profile, Version 1.0. http://www.ogf.org/documents/GFD.114.pdf
[8] OASIS Web Services Notification (WSN) Technical Committee. http://www.oasisopen. org/committees/tc_home.php?wg_abbrev=wsn
[9] K. Kurowski, J. Nabrzyski, A. Oleksiak, J. Węglarz, Grid scheduling simulations with GSSIM. In Proceedings of the International Conference on Parallel and Distributed Systems, IEEE, 2:1–8, 2007. http://www.computer.org/ portal/web/csdl/doi/10.1109/ICPADS.2007.4447835
[10] Vine Toolkit, A better way to use the Grid. http://vinetoolkit.org/
[11] X. Gonzea, B. Amadond, P.M. Anglade et al., ABINIT: First-principles approach to material and nanosystem properties. Computer Phys. Commun. 180, 2582-2615 (2009).
