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Project: Queue Prediction for Supercomputers

Mentor/Lab: Ryan Chard/Globus Labs

Research Area Keywords: Machine Learning // Systems & Architecture

Research in many scientific domains require significant computational power resulting in limitations such as the expense to grab new resources and jobs being initiated only after a certain number of nodes become available. Therefore it is essential to incorporate intelligence in computing resource management. One of the key components of this intelligence is being able to predict queue wait times for jobs running through supercomputers using AWS and Parsl. In my project, I leveraged Amazon SageMaker, a cloud Machine Learning (ML) platform to create, train, and deploy a machine learning model to predict queue wait times.

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