1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.DC2025★ 1 cited
Jenga: Effective Memory Management for Serving LLM with Heterogeneity
Chen Zhang, Kuntai Du, Shu Liu +10
Large language models (LLMs) are widely used but expensive to run, especially as inference workloads grow. To lower costs, maximizing the request batch size by managing GPU memory…
cs.DC2024
APEX: An Extensible and Dynamism-Aware Simulator for Automated Parallel Execution in LLM Serving
Yi-Chien Lin, Woosuk Kwon, Ronald Pineda +1
Efficiently serving Large Language Models (LLMs) requires selecting an optimal parallel execution plan, balancing computation, memory, and communication overhead. However, determin…