18 citations · 18 across the 1 of their papers we have counts for
2 papers
cs.DC2018
Efficient Embedding of MPI Collectives in MXNET DAGs for scaling Deep Learning
Amith R Mamidala
Availability of high performance computing infrastructures such as clusters of GPUs and CPUs have fueled the growth of distributed learning systems. Deep Learning frameworks expres…
cs.DC2018★ 18 cited
MXNET-MPI: Embedding MPI parallelism in Parameter Server Task Model for scaling Deep Learning
Amith R Mamidala, Georgios Kollias, Chris Ward +1
Existing Deep Learning frameworks exclusively use either Parameter Server(PS) approach or MPI parallelism. In this paper, we discuss the drawbacks of such approaches and propose a…