ComfyUI-Distributed

Supercharge your ComfyUI workflows with distributed GPU processing

A powerful extension for ComfyUI that enables distributed processing across multiple GPUs and machines. Speed up your image generation and upscaling workflows by leveraging all available GPU resources in your network.

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Features

• Distributed Processing - Split workloads across multiple GPUs automatically
• Distributed Upscaling - Tile-based upscaling with intelligent work distribution
• Automatic Worker Management - Launch and monitor workers from the UI
• Network Support - Use GPUs across different machines on your network
• Real-time Monitoring - Track worker status and performance from the UI
• Easy Configuration - JSON-based configuration with UI controls
• Memory Management - Built-in VRAM clearing and optimization

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Requirements

• ComfyUI installation
• PyTorch with CUDA support
• Python 3.8+

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Installation

1. Clone this repository into your ComfyUI custom nodes directory:

   cd ComfyUI/custom_nodes
   git clone https://github.com/yourusername/ComfyUI-Distributed.git
   

2. Restart ComfyUI - the extension will create a default configuration file on first load

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Quick Start

Adding Local Workers

The Distributed GPU panel can be found in the sidebar on the left.

1. Open the Distributed GPU panel.
2. Click "Add Worker" in the UI.
3. Configure your local worker:
   • Name: A descriptive name for the worker (e.g., "My Gaming PC GPU 0")
   • Port: A unique port number for this worker (e.g., 8189, 8190...).
   • CUDA Device: The GPU index from nvidia-smi (e.g., 0, 1).
   • Extra Args: Optional ComfyUI arguments for this specific worker.
4. Save and optionally launch the local worker.

Adding Remote Workers

1. On the Remote Worker Machine:
   • Launch ComfyUI with the --listen --enable-cors-header arguments. ⚠️ Required!
   • Add workers in the UI panel if the remote machine has more than one GPU.
     • Make sure that they also have --listen set in Extra Args.
     • Then launch them.
   • Open the configured worker port(s) (e.g., 8189, 8190) in the remote worker's firewall.
2. On the Main Machine:
   • Open the Distributed GPU panel (sidebar on the left).
   • Click "Add Worker."
   • Enable "Remote Worker" checkbox.
   • Configure your remote worker:
     • Name: A descriptive name for the worker (e.g., "Server Rack GPU 0")
     • Host: The remote worker's IP address.
     • Port: The port number used when launching ComfyUI on the remote worker (e.g., 8189).
   • Save the remote worker configuration.

Configuration Tips

| Setting | Description | Example | |---------|-------------|---------| | CUDA Devices | Use nvidia-smi to see GPU indices | 0, 1, 2... | | Ports | Each worker needs a unique port | 8189, 8190... | | Extra Args | Additional ComfyUI arguments | See below |

Common Extra Args:

• --lowvram - For GPUs with less memory
• --listen - Required for remote workers
• --highvram - For GPUs with 12GB+ VRAM

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Nodes

Distributed Collector

Collects and combines results from distributed processing

Usage: Place after any image generation node to enable distributed processing. Works automatically when workers are enabled.

Distributed Seed

Ensures unique seeds across distributed workers for varied generation

Usage: Connect to any seed input. Each worker automatically receives an offset seed for variety.

Ultimate SD Upscale Distributed

Distributed version of Ultimate SD Upscale that processes tiles across multiple GPUs

Usage:

1. Upscale your image with a regular upscale model (ESRGAN, etc.)
2. Feed the upscaled image into this node
3. Configure tile settings
4. Enable workers for faster processing

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UI Features

Distributed GPU Panel

The control center for your distributed setup:

| Feature | Description | |---------|-------------| | Worker Status | Real-time status indicators | | Launch/Stop | Control individual local workers | | Clear Memory | Free VRAM on all workers | | Interrupt | Stop current processing | | Worker Logs | View real-time logs |

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Workflow Examples

Basic Distributed Generation

1. Create your normal ComfyUI workflow
2. Add Distributed Seed → connect to sampler's seed
3. Add Distributed Collector → after VAE Decode
4. Enable workers in the UI
5. Run the workflow!

Distributed Upscaling

1. Load your image
2. Upscale with ESRGAN or similar
3. Connect to Ultimate SD Upscale Distributed
4. Configure tile settings
5. Enable workers for faster processing

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Troubleshooting

Common Issues

<details> <summary><b>Workers won't start</b></summary>

• Check ports are not in use: netstat -an | grep 8189
• Verify CUDA device exists: nvidia-smi
• Check ComfyUI path in worker logs

</details> <details> <summary><b>"Worker not managed by UI" message</b></summary>

• Worker was started outside the UI
• Stop the worker manually and use the UI to relaunch

</details> <details> <summary><b>Images not combining properly</b></summary>

• Ensure all workers have the same models loaded
• Check that custom nodes are installed on all workers

</details> <details> <summary><b>Network connection issues</b></summary>

• Check firewall settings for required ports
• Verify master IP is accessible: ping 192.168.1.100
• Ensure same ComfyUI version on all machines
• Ensure ComfyUI-Distributed is installed on remote workers

</details>

Debug Mode

Enable detailed logging for troubleshooting:

1. UI Method: Settings → Debug Mode → Enable
2. Check console output for detailed logs

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Development

This project is under active development. Contributions are welcome!

Planned Features

• [ ] Remote worker control via SSH
• [ ] View remote worker logs in UI
• [ ] Improve worker timeout logic