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Enabling Fast, Noncontiguous GPU Data Movement in Hybrid MPI+GPU Environments
2012
2012 IEEE International Conference on Cluster Computing
Lack of efficient and transparent interaction with GPU data in hybrid MPI+GPU environments challenges GPU-acceleration of largescale scientific and engineering computations. A particular challenge is the efficient transfer of noncontiguous data to and from GPU memory. MPI supports such transfers through the use of datatypes, however an efficient means of utilizing datatypes for noncontiguous data in GPU memory is not currently known. To address this gap, we present the design and implementation
doi:10.1109/cluster.2012.72
dblp:conf/cluster/JenkinsDBST12
fatcat:nao2aiqflfgzrp7byepxhnrwri