Session III: To Exascale and Beyond: Some Strengths and Weaknesses of MPI

For decades, leadership computing has been heavily relying on the Message Passing Interface (MPI) for the development of science simulations. This trend was pushed with success to the point where new systems were designed specifically for the optimal execution of MPI-based applications.

However, with the growing interest in data sciences, artificial intelligence, machine learning and deep learning, new models now need to be supported by large-scale high performance computing (HPC) systems, moving away from a pure MPI-based approach. This switch is deeply impacting the way systems are designed (e.g., Summit has 6 accelerators per compute node), used (e.g., some task-based workloads require execution models that are more complex than the traditionaljob-based model; new programming languages are used) and managed (e.g., growing need for customized execution environments using containers). As a result, many in the HPC community are wondering what will be the role of MPI for the future of leadership computing. Will it be replaced by something else? Will it evolve to better match new needs?

In this presentation, I will first present the current strengths and weaknesses of MPI, as well as identified gaps when considering the Oak Ridge National Laboratory’s Summit system based the current trends within the U.S. Department of Energy, and more specifically the Exascale Computing Project (ECP). I will then present ideas and suggestions based on current trends driven by the upcoming exascale systems, as well as thoughts about the long term viability of MPI (i.e., beyond exascale).

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Location: Grand Ballroom C Date: March 27, 2019 Time: 2:45 pm - 3:10 pm David Bernholdt, ORNL