activity
20242026
most citedDynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency

92 citations · 105 across the 14 of their papers we have counts for

collaborators
Showing cs.DCShow all

6 papers · 1 filter

cs.DC2026

StreamWise: Serving Multi-Modal Generation in Real-Time at Scale

Haoran Qiu, Gohar Irfan Chaudhry, Chaojie Zhang +4

Advances in multi-modal generative models are enabling new applications, from storytelling to automated media synthesis. Most current workloads generate simple outputs (e.g., image…

cs.DC2025★ 1 cited

TAPAS: Thermal- and Power-Aware Scheduling for LLM Inference in Cloud Platforms

Jovan Stojkovic, Chaojie Zhang, Íñigo Goiri +5

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

cs.DC2025

Towards Resource-Efficient Compound AI Systems

Gohar Irfan Chaudhry, Esha Choukse, Íñigo Goiri +3

Compound AI Systems, integrating multiple interacting components like models, retrievers, and external tools, have emerged as essential for addressing complex AI tasks. However, cu…

cs.DC2025

Cloud abstractions for AI workloads

Marco Canini, Theophilus A. Benson, Ricardo Bianchini +4

AI workloads, often hosted in multi-tenant cloud environments, require vast computational resources but suffer inefficiencies due to limited tenant-provider coordination. Tenants l…

cs.DC2024★ 3 cited

Towards Cloud Efficiency with Large-scale Workload Characterization

Anjaly Parayil, Jue Zhang, Xiaoting Qin +4

Cloud providers introduce features (e.g., Spot VMs, Harvest VMs, and Burstable VMs) and optimizations (e.g., oversubscription, auto-scaling, power harvesting, and overclocking) to…

cs.DC2024

Junctiond: Extending FaaS Runtimes with Kernel-Bypass

Enrique Saurez, Joshua Fried, Gohar Irfan Chaudhry +5

This report explores the use of kernel-bypass networking in FaaS runtimes and demonstrates how using Junction, a novel kernel-bypass system, as the backend for executing components…