3 papers
cs.DC2026
Lit Silicon: A Case Where Thermal Imbalance Couples Concurrent Execution in Multiple GPUs
Marco Kurzynski, Shaizeen Aga, Di Wu
GPU systems are increasingly powering modern datacenters at scale. Despite being highly performant, GPU systems can exhibit performance variation at the node and cluster levels. Su…
cs.DC2025
Chopper: A Multi-Level GPU Characterization Tool & Derived Insights Into LLM Training Inefficiency
Marco Kurzynski, Shaizeen Aga, Di Wu
Training large language models (LLMs) efficiently requires a deep understanding of how modern GPU systems behave under real-world distributed training workloads. While prior work h…
cs.AR2025
Adding MFMA Support to gem5
Marco Kurzynski, Matthew D. Sinclair
In this work we have enhanced gem5's GPU model support to add Matrix Core Engines (MCEs). Specifically, on the AMD MI200 and MI300 GPUs that gem5 supports, these MCEs perform Matri…