3 papers
cs.PF2026
Dissecting GPU Utilization for LLM Inference on Nvidia Hopper
Mohammad Siavashi, Gerald Q. Maguire, Dejan Kostic +1
A single SM utilization percentage can make an LLM inference workload look compute-saturated while hiding how much useful work is being done. The problem is not that the counter is…
cs.DC2026
Blink: CPU-Free LLM Inference by Delegating the Serving Stack to GPU and SmartNIC
Mohammad Siavashi, Mariano Scazzariello, Gerald Q. Maguire +2
Large Language Model (LLM) inference is rapidly becoming a core datacenter service, yet current serving stacks keep the host CPU on the critical path for orchestration and token-le…
cs.LG2025
KVComm: Enabling Efficient LLM Communication through Selective KV Sharing
Xiangyu Shi, Marco Chiesa, Gerald Q. Maguire +1
Large Language Models (LLMs) are increasingly deployed in multi-agent systems, where effective inter-model communication is crucial. Existing communication protocols either rely on…