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MapReduce in MPI for Large-scale graph algorithms
2011
Parallel Computing
We describe a parallel library written with message-passing (MPI) calls that allows algorithms to be expressed in the MapReduce paradigm. This means the calling program does not need to include explicit parallel code, but instead provides "map" and "reduce" functions that operate independently on elements of a data set distributed across processors. The library performs needed data movement between processors. We describe how typical MapReduce functionality can be implemented in an MPI context,
doi:10.1016/j.parco.2011.02.004
fatcat:icat6ghmqvaetevtbhkwslzqbq