1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.DC2025
EcoServe: Designing Carbon-Aware AI Inference Systems
Yueying Li, Zhanqiu Hu, Esha Choukse +3
The rapid increase in LLM ubiquity and scale levies unprecedented demands on computing infrastructure. These demands not only incur large compute and memory resources but also sign…
cs.AR2024★ 1 cited
Towards Understanding Systems Trade-offs in Retrieval-Augmented Generation Model Inference
Michael Shen, Muhammad Umar, Kiwan Maeng +2
The rapid increase in the number of parameters in large language models (LLMs) has significantly increased the cost involved in fine-tuning and retraining LLMs, a necessity for kee…