Article 3GGN8 Designing HPC, Deep Learning, and Cloud Middleware for Exascale Systems

Designing HPC, Deep Learning, and Cloud Middleware for Exascale Systems

by
Rich Brueckner
from High-Performance Computing News Analysis | insideHPC on (#3GGN8)
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DK Panda from Ohio State University gave this talk at the Stanford HPC Conference. "This talk will focus on challenges in designing HPC, Deep Learning, and HPC Cloud middleware for Exascale systems with millions of processors and accelerators. For the HPC domain, we will discuss the challenges in designing runtime environments for MPI+X (PGAS-OpenSHMEM/UPC/CAF/UPC++, OpenMP and Cuda) programming models by taking into account support for multi-core systems (KNL and OpenPower), high networks, GPGPUs (including GPUDirect RDMA) and energy awareness."

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