Transparent Adaptation of e-Science Applications for Parallel and Cycle-Sharing Infrastructures
Grid computing is a concept usually associated with institution-driven networks assembled with a clear purpose, namely to address complex calculation problems or when heterogeneity and users’ geographical dispersion is a key factor. However, regular home users willing to take advantage of distributed processing cannot regard this a viable option. Even if Grid access was open to the general public, a home user would not be able to express task decomposition without clearly understanding the program internals.
In this work, distributed computation, and cycle-sharing in particular, are addressed in a different manner. Users share idle resources with other users provided that such resources (namely, CPU cycles) are mostly employed to execute already installed applications (e.g., popular commodity applications targeting video compression/transcoding, image processing, ray tracing). Users need not to modify an application they already use and trust. Instead, they require only access to an available format description of the application input/output, in order to allow transparent and automatic decomposition of a job in smaller tasks that may be distributed and executed in cycle-sharing machines.
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- 1.Thain, D., Tannenbaum, T., Livny, M.: Condor and the grid. In: Berman, F., Fox, G., Hey, T. (eds.) Grid Computing: Making the Global Infrastructure a Reality. John Wiley & Sons Inc., Chichester (December 2002)Google Scholar
- 3.De Camargo, R.Y., Kon, F.: Design and implementation of a middleware for data storage in opportunistic grids. In: CCGRID 2007: Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid, pp. 23–30. IEEE Computer Society, Washington, DC, USA (2007)Google Scholar
- 4.Egede, U., Harrison, K., Jones, R., Maier, A., Moscicki, J., Patrick, G., Soroko, A., Tan, C.: Ganga user interface for job definition and management. In: Proc. Fourth International Workshop on Frontier Science: New Frontiers in Subnuclear Physics, Italy, Laboratori Nazionali di Frascati (September 2005)Google Scholar
- 5.van der Raadt, K., Yang, Y., Casanova, H.: Practical Divisible Load Scheduling on Grid Platforms with APST-DV. In: Proceedings of 19th IEEE International Parallel and Distributed Processing Symposium, 2005, p. 29b (2005)Google Scholar
- 6.Silva, J., Veiga, L., Ferreira, P.: nuboinc: Boinc extensions for community cycle sharing. In: Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW 2008, pp. 248–253 (October 2008)Google Scholar
- 7.Zhou, D., Lo, V.: Cluster computing on the fly: Resource discovery in a cycle sharing peer-to-peer system. In: IEEE International Symposium on Cluster Computing and the Grid (2004)Google Scholar
- 8.Veiga, L., Rodrigues, R., Ferreira, P.: Gigi: An ocean of gridlets on a ”grid-for-the-masses”. In: CCGRID 2007: Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid, pp. 783–788. IEEE Computer Society, Washington, DC, USA (2007)Google Scholar
- 9.Morais, J., Silva, J., Ferreira, P., Veiga, L.: Transparent adaptation of e-science applications for parallel and cycle-sharing infrastructures, inesc-id tech. report 15/2011 (February 2011)Google Scholar