Zeus: interpretable ML-based job scheduling in GPU datacentres

• Main Author: Amrita, Ravishankar
• Other Authors: Zhang Tianwei
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling
• Online Access: https://hdl.handle.net/10356/156566
• Institution: Nanyang Technological University

Hardware accelerators such as GPUs are essential for the development of Deep Learning (DL) models - as their training process is compute-intensive. A growing number of organisations have employed expensive multi-tenant GPU clusters to run distributed DL training jobs. Efficient job schedulers are re...