Generative large language model (LLM) applications are growing rapidly, leading to large-
scale deployments of expensive and power-hungry GPUs. Our characterization of LLM …

This survey offers a comprehensive overview of recent advancements in Large Language
Model (LLM) serving systems, focusing on research since the year 2023. We specifically …

The rapid evolution and widespread adoption of generative large language models (LLMs)
have made them a pivotal workload in various applications. Today, LLM inference clusters …

The rapid adoption of large language models (LLMs) has led to significant advances in
natural language processing and text generation. However, the energy consumed through …

The recent proliferation of large language models (LLMs) has led to divergent narratives
about their environmental impacts. Some studies highlight the substantial carbon footprint of …

With the rapid growth in the number of large language model (LLM) users, it is difficult for
bandwidth-constrained cloud servers to simultaneously process massive LLM services in …

The rising demand for generative large language models (LLMs) poses challenges for
thermal and power management in cloud datacenters. Traditional techniques often are …

Small Language Models (SLMs) have become increasingly important due to their efficiency
and performance to perform various language tasks with minimal computational resources …

Recent breakthroughs of large language models (LLMs) have exhibited superior capability
across major industries and stimulated multi-hundred-billion-dollar investment in AI-centric …

This article overviews some of the key past developments in cloud data center power and
energy management, where we are today, and what the future could be. This topic is gaining …