Distributed Inference for Multi-model Generative AI Workflows in ComfyUI

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering

Final Year Thesis Oral Defense

Title: "Distributed Inference for Multi-model Generative AI Workflows in 
ComfyUI"

by

MORSI Mohamed Sobhy Mohamed Hassan

Abstract:

This thesis presents the design, implementation, and evaluation of a 
distributed inference system for ComfyUI, aimed at overcoming the 
computational constraints associated with running ComfyUI workflows on single 
machines and the privacy concerns associated with running them on cloud 
servers. Complex workflows that previously exceeded single-machine 
capabilities can now be executed efficiently through our distributed 
approach. This research contributes to the field of distributed systems for 
AI applications by providing an extensible framework that can scale with 
increasing model complexity and computational demands, making advanced AI 
workflows more accessible to users with limited individual computing 
resources.


Date            : 3 May 2025 (Satuarday)

Time            : 12:20 - 13:00

Venue           : Room 2130B (near lift 19), HKUST

Advisor         : Prof. GUO Song

2nd Reader      : Prof. WU Dekai