From Dedicated Grid to Volunteer Grid: Large Scale Execution of a Bioinformatics Application

Large volunteer desktop platforms are now available for several kind of applications. More and more scientists consider this type of computing power as an alternative to the classical platforms such as dedicated clusters aggregated into Grids. This paper presents the work we did to run the first phase of the Help Cure Muscular Dystrophy project to run on World Community Grid. The project was launched on December 19, 2006, and took 26 weeks to complete. During this time frame, 123 GB of results were produced by volunteers who share their idle CPU time to compute a cross docking experiment over 168 proteins. We present performance evaluation of the overall execution and compare the World Community Grid volunteer Grid with a dedicated one.

[1]  Alessandra Carbone,et al.  Identification of protein interaction partners and protein-protein interaction sites. , 2008, Journal of molecular biology.

[2]  David P. Anderson,et al.  BOINC: a system for public-resource computing and storage , 2004, Fifth IEEE/ACM International Workshop on Grid Computing.

[3]  David P. Anderson,et al.  SETI@home: an experiment in public-resource computing , 2002, CACM.

[4]  Gilles Fedak,et al.  Characterizing resource availability in enterprise desktop grids , 2007, Future Gener. Comput. Syst..

[5]  Alessandra Carbone,et al.  Joint Evolutionary Trees: A Large-Scale Method To Predict Protein Interfaces Based on Sequence Sampling , 2009, PLoS Comput. Biol..

[6]  David P. Anderson,et al.  High-performance task distribution for volunteer computing , 2005, First International Conference on e-Science and Grid Computing (e-Science'05).

[7]  Zhiping Weng,et al.  A protein–protein docking benchmark , 2003, Proteins.

[8]  B. Allen,et al.  Designing a Runtime System for Volunteer Computing , 2006, ACM/IEEE SC 2006 Conference (SC'06).

[9]  Franck Cappello,et al.  Grid'5000: A Large Scale And Highly Reconfigurable Experimental Grid Testbed , 2006, Int. J. High Perform. Comput. Appl..

[10]  Charles L. Brooks,et al.  Predictor@Home: A "Protein Structure Prediction Supercomputer' Based on Global Computing , 2006, IEEE Transactions on Parallel and Distributed Systems.

[11]  Charles L. Brooks,et al.  Predictor@Home: a "protein structure prediction supercomputer" based on public-resource computing , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[12]  Z. Weng,et al.  Protein–protein docking benchmark 2.0: An update , 2005, Proteins.

[13]  Michela Taufer,et al.  Combining Task- and Data Parallelism to Speed up Protein Folding on a Desktop Grid Platform Is efficient protein folding possible with CHARMM on the United Devices MetaProcessor? , 2002 .

[14]  Martin Zacharias,et al.  Protein–protein docking with a reduced protein model accounting for side‐chain flexibility , 2003, Protein science : a publication of the Protein Society.

[15]  Thomas Stricker,et al.  Combining task- and data parallelism to speed up protein folding on a desktop grid platform , 2003, CCGrid 2003. 3rd IEEE/ACM International Symposium on Cluster Computing and the Grid, 2003. Proceedings..