92 citations · 112 across the 11 of their papers we have counts for
4 papers · 1 filter
Chameleon: Adaptive Caching and Scheduling for Many-Adapter LLM Inference Environments
Nikoleta Iliakopoulou, Jovan Stojkovic, Chloe Alverti +3
The widespread adoption of LLMs has driven an exponential rise in their deployment, imposing substantial demands on inference clusters. These clusters must handle numerous concurre…
DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency
Jovan Stojkovic, Chaojie Zhang, Íñigo Goiri +2
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 rece…
Workload Intelligence: Punching Holes Through the Cloud Abstraction
Lexiang Huang, Anjaly Parayil, Jue Zhang +13
Today, cloud workloads are essentially opaque to the cloud platform. Typically, the only information the platform receives is the virtual machine (VM) type and possibly a decoratio…
Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference
Jovan Stojkovic, Esha Choukse, Chaojie Zhang +2
With the ubiquitous use of modern large language models (LLMs) across industries, the inference serving for these models is ever expanding. Given the high compute and memory requir…