MPICH-V: toward a scalable fault tolerant MPI for volatile nodes
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
CCGRID '01 Proceedings of the 1st International Symposium on Cluster Computing and the Grid
BOINC: A System for Public-Resource Computing and Storage
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
Distributed computing in practice: the Condor experience: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
SimBA: A Discrete Event Simulator for Performance Prediction of Volunteer Computing Projects
Proceedings of the 21st International Workshop on Principles of Advanced and Distributed Simulation
VolpexMPI: An MPI Library for Execution of Parallel Applications on Volatile Nodes
Proceedings of the 16th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
A Robust Communication Framework for Parallel Execution on Volunteer PC Grids
CCGRID '11 Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
Performance prediction based resource selection in grid environments
HPCC'07 Proceedings of the Third international conference on High Performance Computing and Communications
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Emerging MPI libraries, such as VolpexMPI and P2P MPI, allow message passing parallel programs to execute effectively in heterogeneous volunteer environments despite frequent failures. However, the performance of message passing codes varies widely in a volunteer environment, depending on the application characteristics and the computation and communication characteristics of the nodes and the interconnection network. This paper has the dual goal of developing and validating a tool chain to estimate performance of MPI codes in a volunteer environment and analyzing the suitability of the class of computations represented by NAS benchmarks for volunteer computing. The framework is deployed to estimate performance in a variety of possible volunteer configurations, including some based on the measured parameters of a campus volunteer pool. The results show slowdowns by factors between 2 and 10 for different NAS benchmark codes for execution on a realistic volunteer campus pool as compared to dedicated clusters.