Run ComfyUI workflows across multiple local GPUs or networked machines, allowing users to adjust JSON parameters within ComfyUI. This tool enhances the flexibility and efficiency of AI art generation by distributing workloads across different systems.
- Enables the execution of ComfyUI processes on multiple GPUs, maximizing resource utilization.
- Facilitates remote conditioning workflows, allowing specific components to run on separate instances for improved performance.
- Supports advanced batch processing and workflow management, enabling users to easily switch between different configurations and models.
Context
This tool, ComfyUI_NetDist Plus, is an extension designed for ComfyUI that allows users to run workflows on multiple local GPUs or across networked machines. Its primary purpose is to optimize resource usage by distributing tasks, which can lead to faster processing times and more efficient use of hardware.
Key Features & Benefits
The tool provides several practical features, such as the ability to run remote conditioning workflows, which allows a primary system to focus on specific tasks while delegating others to different machines. This separation of tasks is crucial for maximizing the performance of AI models, especially when dealing with resource-intensive processes.
Advanced Functionalities
One of the advanced capabilities includes the ability to manage and execute workflows with various checkpoints and configurations, allowing users to compare different models or settings easily. Additionally, it supports the transfer of latent representations between instances, which can streamline the workflow further by reusing computed data.
Practical Benefits
By utilizing ComfyUI_NetDist Plus, users can significantly improve their workflow efficiency, enabling them to manage multiple GPUs and networked machines seamlessly. This leads to enhanced control over the AI art generation process, allowing for higher quality outputs and reduced processing times.
Credits/Acknowledgments
The development of this tool is credited to various contributors, including Comfyanonymous, City96, and EventStationAI for GPU support. Additional thanks go to all node creators whose work contributed to the project's development, and to Claude and Ogkai for their encouragement and support.