Dyn-MPI: supporting MPI on medium-scale, non-dedicated clusters. Distributing data is a fundamental problem in implementing efficient distributed-memory parallel programs. The problem becomes more difficult in environments where the participating nodes are not dedicated to a parallel application. We are investigating the data distribution problem in non-dedicated environments in the context of explicit message-passing programs.To address this problem, we have designed and implemented an extension to MPI called dynamic MPI (Dyn-MPI). The key component of Dyn-MPI is its run-time system, which efficiently and automatically redistributes data on the fly when there are changes in the application or the underlying environment. Dyn-MPI supports efficient memory allocation, precise measurement of system load and computation time, and node removal. Performance results show that programs that use Dyn-MPI execute efficiently in non-dedicated environments, including up to almost a threefold improvement compared to programs that do not redistribute data and a 25% improvement over standard adaptive load balancing techniques.
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References in zbMATH (referenced in 2 articles )
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- Freeh, Vincent W.; Kappiah, Nandini; Lowenthal, David K.; Bletsch, Tyler K.: Just-in-time dynamic voltage scaling: exploiting inter-node slack to save energy in MPI programs (2008) ioport
- Weatherly, D.Brent; Lowenthal, David K.; Nakazawa, Mario; Lowenthal, Franklin: Dyn-MPI: supporting MPI on medium-scale, non-dedicated clusters (2006)