92 citations · 125 across the 10 of their papers we have counts for
10 papers
Architectural Implications of Agentic AI Workflows
Jirong Yang, Peizhe Liu, Chaojie Zhang +1
Agentic AI is emerging in datacenters, but its architectural implications remain unexplored. We organize agentic workflows in a taxonomy and present its first architectural charact…
AtumAI: A Principled Framework for Agentic Generation of Datacenter Control-Plane Policies
Qiushi Lin, Chaojie Zhang, Íñigo Goiri +3
The efficiency of a datacenter rests on its control plane policies. Designing these policies is increasingly hard: the hardware-software stack grows fast, the design space is vast…
Designing Datacenter Power Delivery Hierarchies for the AI Era
Grant Wilkins, Fiodar Kazhamiaka, Alok Gautam Kumbhare +2
Demand for AI accelerators is rapidly increasing rack power density, with projections approaching 1MW per deployment by 2027. This poses a major challenge for datacenter power deli…
XWind: A Cross-site Router for Large Language Model Inference Serving at Renewable Energy Farms
Tella Rajashekhar Reddy, Atharva Deshmukh, Liangcheng Yu +7
AI power demand is growing at an unprecedented rate while power grids are often ailing and struggle to keep up. Grid expansion comes with high capital expenditure and long-distance…
AI Greenferencing: Routing AI Inferencing to Green Modular Data Centers with Heron
Tella Rajashekhar Reddy, Palak, Rohan Gandhi +8
AI power demand is growing unprecedentedly thanks to the high power density of AI compute and the emerging inferencing workload. On the supply side, abundant wind power is waiting…
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…
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…
Splitwise: Efficient generative LLM inference using phase splitting
Pratyush Patel, Esha Choukse, Chaojie Zhang +4
Recent innovations in generative large language models (LLMs) have made their applications and use-cases ubiquitous. This has led to large-scale deployments of these models, using…
POLCA: Power Oversubscription in LLM Cloud Providers
Pratyush Patel, Esha Choukse, Chaojie Zhang +4
Recent innovation in large language models (LLMs), and their myriad use-cases have rapidly driven up the compute capacity demand for datacenter GPUs. Several cloud providers and ot…
Characterizing Curtailed and Uneconomic Renewable Power in the Mid-continent Independent System Operator
Andrew A. Chien, Fan Yang, Chaojie Zhang
As power grids incorporate increased renewable generation such as wind and solar, their variability creates growing challenges for grid stability and efficiency. We study two facet…