|Title||Integrating Deep Learning in Domain Science at Exascale (MagmaDNN)|
|Year of Publication||2020|
|Authors||Tomov, S., K. Wong, J. Dongarra, R. Archibald, E. Chow, E. D'Azevedo, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, and J. Yin|
|Event||DOD HPCMP seminar|
We will present some of the current challenges in the design and integration of deep learning AI with traditional HPC simulations. We evaluate existing packages for readiness to run efficiently deep learning models and applications on large scale HPC systems, identify challenges, and propose new asynchronous parallelization and optimization techniques for current large-scale heterogeneous systems and up-coming exascale systems. These developments, along with existing HPC AI software capabilities, have been integrated in MagmaDNN, an open source HPC deep learning framework.
Integrating Deep Learning in Domain Science at Exascale (MagmaDNN)
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