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

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In this video from the 2018 Swiss HPC Conference, DK Panda from Ohio State University presents: Designing Scalable HPC, Deep Learning and Cloud Middleware for Exascale Systems.

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. Finally, we will outline the challenges in moving these middleware to the Cloud environments."

Learn more:

  1. insideHPC Report
  2. hpc
  3. supercomputing
  4. HPC Advisory Council
  5. Swiss HPC Conference
  6. insideHPC
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