The MIT Supercloud Workload Classification Challenge

TL;DR

This paper introduces a workload classification challenge using the MIT Supercloud Dataset to improve AI and ML workload identification for better resource management in HPC and cloud environments.

Contribution

It provides a labeled dataset and initial results to foster new algorithms for workload classification in heterogeneous datacenter environments.

Findings

Initial classification results demonstrate potential for improved accuracy.

The dataset enables development of AI-based workload identification methods.

Public availability of data and code supports further research.

Abstract

High-Performance Computing (HPC) centers and cloud providers support an increasingly diverse set of applications on heterogenous hardware. As Artificial Intelligence (AI) and Machine Learning (ML) workloads have become an increasingly larger share of the compute workloads, new approaches to optimized resource usage, allocation, and deployment of new AI frameworks are needed. By identifying compute workloads and their utilization characteristics, HPC systems may be able to better match available resources with the application demand. By leveraging datacenter instrumentation, it may be possible to develop AI-based approaches that can identify workloads and provide feedback to researchers and datacenter operators for improving operational efficiency. To enable this research, we released the MIT Supercloud Dataset, which provides detailed monitoring logs from the MIT Supercloud cluster. This dataset includes CPU and GPU usage by jobs, memory usage, and file system logs. In this paper, we present a workload classification challenge based on this dataset. We introduce a labelled dataset that can be used to develop new approaches to workload classification and present initial results based on existing approaches. The goal of this challenge is to foster algorithmic innovations in the analysis of compute workloads that can achieve higher accuracy than existing methods. Data and code will be made publicly available via the Datacenter Challenge website : https://dcc.mit.edu.