This project investigates how running multiple deep learning tasks simultaneously (collocation) affects performance on resource-constrained edge devices, specifically the NVIDIA DGX Spark. Students will deploy and benchmark various model in isolated vs. different collocated scenarios, measure metrics such as GPU utilization, memory usage, training time, and analyze the trade-offs between …
Supervisors: Pınar Tözün, Ehsan Yousefzadeh-Asl-Miandoab
Semester: Fall 2026
Tags: machine learning systems, GPU utilization, performance characterization, workload collocation