Dyn-MPI: Supporting MPI on medium-scale, non-dedicated clusters

D. Brent Weatherly, David K. Lowenthal, Mario Nakazawa, Franklin Lowenthal

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)822-838
Number of pages17
JournalJournal of Parallel and Distributed Computing
Issue number6
StatePublished - Jun 2006


  • Adaptive
  • Load balancing
  • MPI
  • Non-dedicated clusters

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence


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