nodes/robertvoy-ComfyUI-Distributed
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Update README.md

Browse Source
This commit is contained in:
Robert Wojciechowski
2025-06-29 09:38:01 +10:00
committed by GitHub
parent 398ee5a47a
commit f247ea21ff
1 changed files with 74 additions and 40 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+74 -40
View File
@@ -16,12 +16,14 @@ ComfyUI-Distributed extends ComfyUI with the ability to distribute batch process
- **Master-Worker Architecture**: Automatic coordination between GPU instances
- **Dynamic Worker Management**: Enable/disable GPUs on-the-fly through the UI
- **Parallel Execution**: All enabled GPUs process batches simultaneously for maximum speed
- **Web UI Integration**: Seamless control panel integrated into ComfyUI's interface
- **Smart Launch**: Launcher checks for running instances and starts only those that aren't running
- **Web UI Integration**: Seamless control panel integrated into ComfyUI's sidebar
- **Smart Launcher**: Unified launcher with multiple modes and instance detection
- **VRAM Management**: Clear worker VRAM remotely through the UI
- **Flexible Configuration**: JSON-based configuration with runtime updates
## How It Works
1. Launch multiple ComfyUI instances, each assigned to a different GPU
1. Launch multiple ComfyUI instances using the unified launcher
2. One instance acts as the master (typically on CUDA device 0)
3. Add the "Multi-GPU Collector" node to your workflow
4. The extension automatically distributes batches across available GPUs
@@ -31,10 +33,10 @@ For example, with 4 GPUs and a batch size of 2, you'll generate 8 images in para
## Requirements
- ComfyUI installation (venv, portable not supported yet)
- Virtual environment with ComfyUI installed
- ComfyUI installation with ComfyUI CLI (`comfy` command)
- Multiple NVIDIA GPUs
- Python 3.8+
- Windows (for the provided launcher script) or Linux/Mac with manual setup
## Installation
@@ -50,47 +52,41 @@ For example, with 4 GPUs and a batch size of 2, you'll generate 8 images in para
### Quick Start (Windows)
1. Copy the `launch_distributed.bat` file to your ComfyUI root directory (alongside other .bat files like `run_nvidia_gpu.bat`)
1. Copy the `launch_distributed.bat` file to your ComfyUI root directory (alongside your `venv` folder)
2. Edit the `gpu_config.json` file in `ComfyUI/custom_nodes/ComfyUI-Distributed/` to match your GPU setup:
- Adjust the number of workers based on your available GPUs
- Update CUDA device numbers if needed
- Set appropriate ports (ensure they're not in use)
- Add custom launch arguments in `extra_args` for master and workers
- Add custom launch arguments in `extra_args`
3. Run the launcher script from the ComfyUI root directory:
3. Run the launcher from the ComfyUI root directory:
```bash
launch_distributed.bat
```
Or use command-line options:
```bash
launch_distributed.bat master # Launch master only
launch_distributed.bat all-fast # Launch all with 2-second delays
launch_distributed.bat all-slow # Launch all, wait for each to be ready
launch_distributed.bat venv # Open command prompt with venv activated
launch_distributed.bat update # Update ComfyUI
launch_distributed.bat update-nodes # Update all custom nodes
```
4. Open the master instance (usually http://localhost:8188)
4. Open the master instance (check the launcher output for the URL)
5. Add the "Multi-GPU Collector" node to your workflow
6. Use the GPU control panel in the sidebar to:
- View GPU status and worker information
- Monitor active instances
### Manual Setup (All Platforms)
Start each ComfyUI instance with the appropriate CUDA device:
```bash
# Master instance (GPU 0)
CUDA_VISIBLE_DEVICES=0 python main.py --port 8188
# Worker instance (GPU 1)
CUDA_VISIBLE_DEVICES=1 python main.py --port 8189 --enable-cors-header
# Worker instance (GPU 2)
CUDA_VISIBLE_DEVICES=2 python main.py --port 8190 --enable-cors-header
# Continue for additional GPUs...
```
6. Use the Multi-GPU sidebar panel to:
- Enable/disable worker GPUs
- View worker status
- Clear worker VRAM
### Configuration
The system uses a `gpu_config.json` file for configuration. Default configuration:
The system uses a `gpu_config.json` file for configuration. Example configuration:
```json
{
@@ -117,24 +113,48 @@ The system uses a `gpu_config.json` file for configuration. Default configuratio
"extra_args": "--mmap-torch-files --highvram --disable-smart-memory"
}
],
"settings": {
"retry_delay_ms": 500
}
"settings": {}
}
```
**Configuration Options:**
- `extra_args`: Custom launch arguments for each instance (e.g., memory management flags)
- `retry_delay_ms`: Delay between connection attempts during startup
- Worker `enabled` flag: Control which GPUs are active
- `master`: Master instance configuration
- `port`: Port number for the master instance
- `cuda_device`: CUDA device index
- `extra_args`: Custom launch arguments
- `workers`: Array of worker configurations
- `id`: Unique worker identifier
- `name`: Display name in UI
- `cuda_device`: CUDA device index
- `port`: Port number for the worker
- `enabled`: Whether the worker is active
- `extra_args`: Custom launch arguments
- `host` (optional): Remote host address
- `settings`: Additional settings (reserved for future use)
### Remote Workers
Remote workers are fully supported! Add a `host` field to any worker configuration:
```json
{
"id": 3,
"name": "Remote GPU",
"host": "192.168.1.100",
"port": 8190,
"enabled": true,
"extra_args": "--enable-cors-header"
}
```
Ensure remote workers are started with `--enable-cors-header` and are accessible from the master instance.
## Workflow Integration
The Multi-GPU Collector node integrates seamlessly with existing ComfyUI workflows:
1. Connect the node after your image generation pipeline
2. The node will automatically detect batch sizes and distribute work
3. All GPUs will process their assigned batches
3. All GPUs will process their assigned batches in parallel
4. Results are collected and passed to the next node as a single batch
### Important Node Requirements
@@ -142,23 +162,37 @@ The Multi-GPU Collector node integrates seamlessly with existing ComfyUI workflo
- **Batch Node**: Your workflow must include a node with the title "BATCH" or "BATCH SIZE" (case-insensitive). This is required for the Multi-GPU system to detect the batch size for distribution.
- The system will show an error if no batch node with the correct title is found.
## API Endpoints
The extension provides several REST API endpoints for integration:
- `GET /multigpu/config` - Retrieve current configuration
- `POST /multigpu/config/update_worker` - Enable/disable a worker
- `POST /multigpu/config/update_setting` - Update configuration settings
- `POST /multigpu/prepare_job` - Prepare a multi-GPU job
- `POST /multigpu/clear_memory` - Clear VRAM on workers
- `POST /multigpu/job_complete` - Worker callback for job completion
## Performance Considerations
- **Parallel Execution**: All enabled GPUs process simultaneously for maximum throughput
- **Batch Size**: Total generation = batch_size × number_of_active_GPUs
- **Batch Size**: Total generation = batch_size × (1 master + number_of_enabled_workers)
- **Smart Launching**: The launcher only starts instances that aren't already running
- **Memory Management**: Use appropriate `extra_args` in configuration for memory optimization
- **Network Overhead**: Minimal - only final images are transferred between instances
## Troubleshooting
- **Workers not connecting**: Ensure CORS headers are enabled (`--enable-cors-header`)
- **VRAM errors**: Add memory management flags in `extra_args` (e.g., `--highvram`, `--disable-smart-memory`)
- **Port conflicts**: Ensure each instance uses a unique port
- **Partial startup**: The launcher will automatically start only missing instances without affecting running ones
- **Launcher errors**: Ensure the batch file is in the ComfyUI root directory with the `venv` folder
- **Batch node not found**: Ensure your workflow has a node titled "BATCH" or "BATCH SIZE"
- **ComfyUI CLI not found**: Make sure ComfyUI CLI is installed (`pip install comfyui-cli`)
## Development
This project is under active development. Contributions are welcome!
This project is stable and ready for use. Contributions are welcome!
### Planned Features/Improvements