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cs.PF2025
A Data-driven ML Approach for Maximizing Performance in LLM-Adapter Serving
Ferran Agullo, Joan Oliveras, Chen Wang +5
With the rapid adoption of Large Language Models (LLMs), LLM-adapters have become increasingly common, providing lightweight specialization of large-scale models. Serving hundreds…
cs.DC2025
Mind the Memory Gap: Unveiling GPU Bottlenecks in Large-Batch LLM Inference
Pol G. Recasens, Ferran Agullo, Yue Zhu +5
Large language models have been widely adopted across different tasks, but their auto-regressive generation nature often leads to inefficient resource utilization during inference.…