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

DK Panda from Ohio State University gave this talk at the Swiss 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 about the challenges in designing runtime environments for MPI+X (PGAS - OpenSHMEM/UPC/CAF/UPC++, OpenMP, and CUDA) programming models. For the Deep Learning domain, we will focus on popular Deep Learning frameworks (Caffe, CNTK, and TensorFlow) to extract performance and scalability with MVAPICH2-GDR MPI library."

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