<span class="var-sub_title">AITuning: Machine Learning-Based Tuning Tool for Run-Time Communication Libraries</span> SC18 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Workshop on Exascale MPI (ExaMPI)


AITuning: Machine Learning-Based Tuning Tool for Run-Time Communication Libraries

Abstract: In this work, we address the problem of tuning communication libraries by using a deep reinforcement learning approach. Reinforcement learning is a machine learning technique incredibly effective in solving game-like situations. In fact, tuning a set of parameters in a communication library in order to get better performance in a parallel application can be expressed as a game: find the right combination/path that provides the best reward. Even though AITuning has been designed to be utilized with different run-time libraries, we focused this work on applying it to the OpenCoarrays run-time communication library, built on top of MPI-3. This work not only shows the potential of using a reinforcement learning algorithm for tuning communication libraries, but also demonstrates how the MPI Tool Information Interface, introduced by the MPI-3 standard, can be used effectively by run-time libraries to improve the performance without human intervention.

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