Design and evaluation of a resource selection framework for Grid applications

While distributed, heterogeneous collections of computers ("Grids") can in principle be used as a computing platform, in practice the problems of first discovering and then organizing resources to meet application requirements are difficult. We present a general-purpose resource selection framework that addresses these problems by defining a resource selection service for locating Grid resources that match application requirements. At the heart of this framework is a simple, but powerful, declarative language based on a technique called set matching, which extends the Condor matchmaking framework to support both single-resource and multiple-resource selection. This framework also provides an open interface for loading application-specific mapping modules to personalize the resource selector. We present results obtained when this framework is applied in the context of a computational astrophysics application, Cactus. These results demonstrate the effectiveness of our technique.

[1]  Francine Berman,et al.  Modeling the effects of contention on the performance of heterogeneous applications , 1996, Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing.

[2]  Richard Wolski,et al.  Dynamically forecasting network performance using the Network Weather Service , 1998, Cluster Computing.

[3]  R. Wolski,et al.  Predicting the CPU availability of time‐shared Unix systems on the computational grid , 1999, Proceedings. The Eighth International Symposium on High Performance Distributed Computing (Cat. No.99TH8469).

[4]  Erik Seligman,et al.  Dome: parallel programming in a distributed computing environment , 1996, Proceedings of International Conference on Parallel Processing.

[5]  Francine Berman,et al.  Predicting slowdown for networked workstations , 1997, Proceedings. The Sixth IEEE International Symposium on High Performance Distributed Computing (Cat. No.97TB100183).

[6]  J. A. Robinson,et al.  A Machine-Oriented Logic Based on the Resolution Principle , 1965, JACM.

[7]  Richard Wolski,et al.  The network weather service: a distributed resource performance forecasting service for metacomputing , 1999, Future Gener. Comput. Syst..

[8]  Sathish S. Vadhiyar,et al.  Numerical Libraries and the Grid , 2001, Int. J. High Perform. Comput. Appl..

[9]  Warren Smith,et al.  A directory service for configuring high-performance distributed computations , 1997, Proceedings. The Sixth IEEE International Symposium on High Performance Distributed Computing (Cat. No.97TB100183).

[10]  Francine Berman,et al.  The AppLeS Project: A Status Report , 1997 .

[11]  Helen D. Karatza,et al.  Load sharing in heterogeneous distributed systems , 2002, Proceedings of the Winter Simulation Conference.

[12]  Warren Smith,et al.  Software infrastructure for the I-WAY high-performance distributed computing experiment , 1996, Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing.

[13]  Rajesh Raman,et al.  Matchmaking: distributed resource management for high throughput computing , 1998, Proceedings. The Seventh International Symposium on High Performance Distributed Computing (Cat. No.98TB100244).

[14]  John F. Karpovich,et al.  Resource management in Legion , 1999, Future Gener. Comput. Syst..

[15]  John F. Karpovich,et al.  The Legion Resource Management System , 1999, JSSPP.

[16]  Ian T. Foster,et al.  Grid information services for distributed resource sharing , 2001, Proceedings 10th IEEE International Symposium on High Performance Distributed Computing.

[17]  Francine Berman,et al.  Application-aware scheduling of a magnetohydrodynamics application in the Legion metasystem , 2000, Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556).

[18]  John Shalf,et al.  Cactus Tools for Grid Applications , 2001, Cluster Computing.

[19]  Ami Marowka,et al.  The GRID: Blueprint for a New Computing Infrastructure , 2000, Parallel Distributed Comput. Pract..

[20]  Sathish S. Vadhiyar,et al.  Numerical Libraries And The Grid: The GrADS Experiments With ScaLAPACK , 2001, ACM/IEEE SC 2001 Conference (SC'01).

[21]  Francine Berman,et al.  The GrADS Project: Software Support for High-Level Grid Application Development , 2001, Int. J. High Perform. Comput. Appl..

[22]  Warren Smith,et al.  A Resource Management Architecture for Metacomputing Systems , 1998, JSSPP.

[23]  Francine Berman,et al.  Master/slave computing on the Grid , 2000, Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556).

[24]  David Abramson,et al.  High performance parametric modeling with Nimrod/G: killer application for the global grid? , 2000, Proceedings 14th International Parallel and Distributed Processing Symposium. IPDPS 2000.

[25]  Miron Livny,et al.  Condor-a hunter of idle workstations , 1988, [1988] Proceedings. The 8th International Conference on Distributed.

[26]  Holly Dail,et al.  A Modular Framework for Adaptive Scheduling in Grid Application Development Environments , 2002 .

[27]  John Shalf,et al.  Solving Einstein's Equations on Supercomputers , 1999, Computer.

[28]  Alexander Reinefeld,et al.  MARS - A framework for minimizing the job execution time in a metacomputing environment , 1996, Future Gener. Comput. Syst..

[29]  Paul Messina.  Distributed supercomputing applications , 1998 .

[30]  Erik Seligman,et al.  Dome: Parallel Programming in a Heteroge-neous Multi-User Environment , 1995 .

[31]  D. Roote,et al.  Status Report , 2006, Journal of periodontology.

[32]  Dan C. Marinescu,et al.  A scheduling expert advisor for heterogeneous environments , 1997, Proceedings Sixth Heterogeneous Computing Workshop (HCW'97).

[33]  Ian T. Foster,et al.  Performance Predictions for a Numerical Relativity Package in Grid Environments , 2001, Int. J. High Perform. Comput. Appl..