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cs.PF2025
GreenLLM: SLO-Aware Dynamic Frequency Scaling for Energy-Efficient LLM Serving
Qunyou Liu, Darong Huang, Marina Zapater +1
Large Language Models (LLMs) are becoming the backbone of modern cloud services, yet their inference costs are dominated by GPU energy. Unlike traditional GPU workloads, LLM infere…
cs.PF2024★ 2 cited
Saving GPU Hours in LLM Inference System Development and Online Workloads with Simulation and DBMS-Inspired Cache Replacement Policies
Kyoungmin Kim, Jiacheng Li, Kijae Hong +3
LLMs are increasingly used world-wide from daily tasks to agentic systems and data analytics, requiring significant GPU resources. While LLM inference systems are capable of servin…