An Evaluation of Low Overhead Time Series Preprocessing Techniques for Downstream Machine Learning

no code implementations • 12 Sep 2022 • Matthew L. Weiss, Joseph McDonald, David Bestor, Charles Yee, Daniel Edelman, Michael Jones, Andrew Prout, Andrew Bowne, Lindsey McEvoy, Vijay Gadepally, Siddharth Samsi

Our best performing models achieve a classification accuracy greater than 95%, outperforming previous approaches to multi-channel time series classification with the MIT SuperCloud Dataset by 5%.

Classification Time Series +2

The MIT Supercloud Workload Classification Challenge

no code implementations • 12 Apr 2022 • Benny J. Tang, Qiqi Chen, Matthew L. Weiss, Nathan Frey, Joseph McDonald, David Bestor, Charles Yee, William Arcand, Chansup Byun, Daniel Edelman, Matthew Hubbell, Michael Jones, Jeremy Kepner, Anna Klein, Adam Michaleas, Peter Michaleas, Lauren Milechin, Julia Mullen, Andrew Prout, Albert Reuther, Antonio Rosa, Andrew Bowne, Lindsey McEvoy, Baolin Li, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi

We introduce a labelled dataset that can be used to develop new approaches to workload classification and present initial results based on existing approaches.

Classification

The MIT Supercloud Dataset

no code implementations • 4 Aug 2021 • Siddharth Samsi, Matthew L Weiss, David Bestor, Baolin Li, Michael Jones, Albert Reuther, Daniel Edelman, William Arcand, Chansup Byun, John Holodnack, Matthew Hubbell, Jeremy Kepner, Anna Klein, Joseph McDonald, Adam Michaleas, Peter Michaleas, Lauren Milechin, Julia Mullen, Charles Yee, Benjamin Price, Andrew Prout, Antonio Rosa, Allan Vanterpool, Lindsey McEvoy, Anson Cheng, Devesh Tiwari, Vijay Gadepally

In this paper we introduce the MIT Supercloud Dataset which aims to foster innovative AI/ML approaches to the analysis of large scale HPC and datacenter/cloud operations.

Scheduling