Abstract
Grids constitute a promising platform to execute loosely coupled applications, which arise naturally in many scientific and engineering fields like bioinformatics, computational fluid dynamics, particle physics, etc. In this paper, we describe our experiences in porting three scientific production codes to the Grid. Those codes follow typical computational models, namely: embarrassingly distributed and master-worker. In spite of their relatively simple computational structure, consisting of many “independent” tasks, their reliable and efficient execution on computational Grids involves several issues, due to both the dynamic nature of the Grid itself and the execution and programming requirements of the applications. The applications have been developed by using the DRMAA (Distributed Resource Management Application API) interface. DRMAA routines are supported by the functionality offered by the GridWay framework, that provides the runtime mechanisms needed for transparently executing jobs on a dynamic Grid environment. The experiments have been performed on Globus-based research testbeds that span heterogeneous resources in different institutions.
This research was supported by Ministerio de Ciencia y Tecnología, through the research grant TIC 2003-01321 and 2002-12422-E, and by Instituto Nacional de Técnica Aeroespacial “Esteban Terradas” (INTA) – Centro de Astrobiología.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Foster, I., Kesselman, C.: The Grid: Blueprint for a New Computing Infrastructure. Morgan-Kaufman, San Francisco (1999)
Foster, I., Kesselman, C.: Globus: A Metacomputing Infrastructure Toolkit. Intl. J. Supercomputer Applications 11, 115–128 (1997)
Schopf, J.M.: Ten Actions when Superscheduling. Technical Report WD8.5, The Global Grid Forum, Scheduling Working Group (2001)
Buyya, R., Abramson, D., Giddy, J.: A Computational Economy for Grid Computing and its Implementation in the Nimrod-G Resource Broker. In: Future Generation Computer Systems. Elsevier Science, Amsterdam (2002)
Casanova, H., Legrand, A., Zagorodnov, D., Berman, F.: Heuristics for Scheduling Parameter Sweep Applications in Grid Environments. In: Proceedings of the 9th Heterogeneous Computing workshop (HCW 2000), Cancun, Mexico (2000)
Allen, G., et al.: The Cactus Worm: Experiments with Dynamic Resource Discovery and Allocation in a Grid Environment. International Journal of High-Performance Computing Applications 15 (2001)
Huedo, E., Montero, R.S., Llorente, I.M.: A Framework for Adaptive Execution on Grids. Intl. J. Software – Practice and Experience (SPE) 34, 631–651 (2004)
Herrera, J., Huedo, E., Montero, R.S., Llorente, I.M.: Developing Grid-Aware Applications with DRMAA on Globus-based Grids. In: Danelutto, M., Vanneschi, M., Laforenza, D. (eds.) Euro-Par 2004. LNCS, vol. 3149, pp. 429–435. Springer, Heidelberg (2004)
Vadhiyar, S., Dongarra, J.: A Performance Oriented Migration Framework for the Grid. In: Proceedings of the 3rd IEEE/ACM Int’l. Symposium on Cluster Computing and the Grid, CCGrid (2003)
Giersch, A., Robert, Y., Vivien, F.: Scheduling Tasks Sharing Files on Heterogeneous Master-Slave Platforms. In: Proc. 12th Euromicro Conf. Parallel, Distributed and Network-based Processing (PDP 2004), pp. 364–371. IEEE CS, Los Alamitos (2004)
Huedo, E., Montero, R.S., Llorente, I.M.: Experiences on Adaptive Grid Scheduling of Parameter Sweep Applications. In: Proc. 12th Euromicro Conf. Parallel, Distributed and Network-based Processing (PDP 2004), pp. 28–33. IEEE CS, Los Alamitos (2004)
Medeiros, R., Cirne, W., Brasileiro, F., Sauvé, J.: Faults in Grids: Why Are They so Bad and What Can Be Done about It? In: Proc. of the 4th Intl. Workshop on Grid Computing, Grid 2003 (2003)
Huedo, E., Montero, R.S., Llorente, I.M.: Experiences on Grid Resource Selection Considering Resource Proximity. In: Fernández Rivera, F., Bubak, M., Gómez Tato, A., Doallo, R. (eds.) Across Grids 2003. LNCS, vol. 2970, pp. 1–8. Springer, Heidelberg (2004)
van Ham, R., et al.: Reductive Genome Evolution in buchnera a phidicola. Proc. Natl. Acad. Sci. USA 100, 581–586 (2003)
Ormö, J., Dohm, J.M., Ferris, J.C., Lepinette, A., Fairén, A.: Marine-Target Craters on Mars? An Assessment Study. Meteoritics & Planetary Science 39, 333–346 (2004)
Gareth, S.C., Melosh, H.J.: SALES 2: A Multi-Material Extension to SALE Hydrocode with Improved Equation of State and Constitutive Model (2002), Available at http://www.lpl.arizona.edu/~gareth/publications/sales_2
Housen, K.R., Schmidt, R.M., Holsapple, K.A.: Crater Ejecta Scaling Laws: Fundamental Forms Based on Dimensional Analysis. Journal of Geophysical Research 88, 2485–2499 (1983)
Kang, L., Chen, Y.: Parallel Evolutionary Algorithms and Applications (1999)
Imade, H., Morishita, R., Ono, I., Ono, N., Okamoto, M.: A Grid-oriented Genetic Algorithm Framework for Bioinformatics. New Generation Computing 22, 177–186 (2004)
Cantú-Paz, E.: A Survey of Parallel Genetic Algorthms (1999)
Schaffer, J., Eshelman, L.: On Crossover as an Evolutionary Viable Strategy. In: Belew, R., Booker, L. (eds.) Proceedings of the 4th International Conference on Genetic Algorithms, pp. 61–68. Morgan Kaufmann, San Francisco (1991)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Herrera, J., Huedo, E., Montero, R.S., Llorente, I.M. (2005). Embarrassingly Distributed and Master-Worker Paradigms on the Grid. In: Herrero, P., Pérez, M.S., Robles, V. (eds) Scientific Applications of Grid Computing. SAG 2004. Lecture Notes in Computer Science, vol 3458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11423287_10
Download citation
DOI: https://doi.org/10.1007/11423287_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25810-0
Online ISBN: 978-3-540-32010-4
eBook Packages: Computer ScienceComputer Science (R0)