Evan Carmen
1f5aeb5248
Docker-based ComfyUI setup for NVIDIA DGX Spark ARM64 + sm_121: - CUDA 13.0.2 base (required for compute_121 support) - PyTorch 2.9.1+cu130 ARM64 wheels - SageAttention compiled with TORCH_CUDA_ARCH_LIST="12.1" - Triton/torch.compile disabled (no sm_121 support yet) - ComfyUI-Manager auto-installed at runtime - Configurable model/data paths via .env 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
145 lines
5.2 KiB
Markdown
145 lines
5.2 KiB
Markdown
# SparkyUI
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**ComfyUI + SageAttention for NVIDIA DGX Spark (Blackwell GB10)**
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A Docker-based ComfyUI setup specifically engineered for the DGX Spark's unique ARM64 + Blackwell architecture.
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## Why This Exists
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The NVIDIA DGX Spark uses the **GB10 GPU** with compute capability **12.1 (sm_121)** - Blackwell architecture. This creates challenges:
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| CUDA Version | Max Compute Capability | Can compile for GB10? |
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|--------------|------------------------|----------------------|
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| CUDA 12.8 | sm_120 | **No** |
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| CUDA 13.0+ | sm_121 | **Yes** |
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Standard ComfyUI containers and PyTorch wheels don't support sm_121. SparkyUI solves this by:
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1. Using **CUDA 13.0.2** base image (supports sm_121)
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2. Installing **PyTorch cu130** ARM64 wheels
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3. Compiling **SageAttention** with `TORCH_CUDA_ARCH_LIST="12.1"`
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4. Disabling **Triton/torch.compile** (doesn't support sm_121 yet)
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## Quick Start
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```bash
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# Clone
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git clone https://github.com/YOUR_USERNAME/SparkyUI.git
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cd SparkyUI
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# Configure paths
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cp .env.example .env
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# Edit .env with your paths
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# Build (compiles SageAttention for sm_121 - takes ~10 min)
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docker compose build
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# Start
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docker compose up -d
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# View logs
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docker compose logs -f
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```
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**Access:** http://localhost:8188 (or your DGX Spark's IP on LAN)
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## Requirements
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- **NVIDIA DGX Spark** (or other GB10-based system)
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- **Docker** with NVIDIA Container Toolkit
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- **NVIDIA Driver** 560+ (tested with 580.95)
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- **~15GB** disk for Docker image
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- **Models** from existing ComfyUI install (mounted read-only)
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## Configuration
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Copy `.env.example` to `.env` and edit:
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```bash
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# Path to your existing ComfyUI models (mounted read-only)
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COMFYUI_HOST_PATH=/path/to/your/ComfyUI
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# Path for SparkyUI data (custom_nodes, outputs, inputs)
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SPARKYUI_DATA_PATH=/path/to/SparkyUI
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# Optional: pin to specific versions
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COMFYUI_REF=master
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SAGEATTN_REF=main
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```
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## Architecture
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```
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┌─────────────────────────────────────────────────────────────┐
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│ DGX Spark Host │
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│ Ubuntu 24.04 (DGX OS 7) / Driver 580.x │
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│ │
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│ ┌─────────────────────────────────────────────────────┐ │
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│ │ Docker Container (sparkyui:cu130) │ │
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│ │ │ │
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│ │ CUDA 13.0.2 + PyTorch 2.9.1+cu130 │ │
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│ │ SageAttention 2.2.0 (compiled for sm_121) │ │
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│ │ ComfyUI 0.7.x + ComfyUI-Manager │ │
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│ │ │ │
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│ │ Key env vars: │ │
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│ │ TORCH_CUDA_ARCH_LIST="12.1" │ │
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│ │ TORCHDYNAMO_DISABLE="1" │ │
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│ └─────────────────────────────────────────────────────┘ │
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│ │ │
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│ Port 8188 (LAN) │
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└─────────────────────────────────────────────────────────────┘
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```
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## Version Compatibility
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Tested combinations:
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| Component | Version | Notes |
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|-----------|---------|-------|
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| CUDA Base | 13.0.2 | Required for sm_121 |
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| PyTorch | 2.9.1+cu130 | ARM64 wheel from PyTorch index |
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| torchvision | 0.24.1+cu130 | ARM64 wheel |
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| SageAttention | 2.2.0 | Compiled with sm_121 |
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| ComfyUI | 0.7.0 | master branch |
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| Driver | 580.95 | DGX OS 7 default |
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## Known Limitations
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1. **PyTorch Warning**: You'll see a warning about compute capability 12.1 being "outside supported range (8.0-12.0)". This is harmless - PyTorch works, and SageAttention's custom kernels are compiled natively.
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2. **torch.compile Disabled**: Triton doesn't support sm_121 yet. `torch.compile()` is disabled via environment variables. Some nodes may run slower than on supported architectures.
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3. **No GitHub Actions CI**: Can't build for ARM64 + sm_121 in GitHub's hosted runners. Must build locally on DGX Spark.
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## Troubleshooting
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### "no kernel image is available for execution on the device"
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Your SageAttention wasn't compiled for sm_121. Rebuild:
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```bash
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docker compose build --no-cache
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```
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### PyTorch can't find CUDA
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Ensure NVIDIA Container Toolkit is installed:
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```bash
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nvidia-ctk --version
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docker run --rm --gpus all nvidia/cuda:13.0.2-base-ubuntu24.04 nvidia-smi
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```
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### ComfyUI-Manager missing
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The entrypoint auto-clones it. Check logs:
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```bash
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docker compose logs | grep -i manager
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```
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## Future
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When these land, SparkyUI can be simplified:
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- [ ] PyTorch native sm_121 support → remove explicit `TORCH_CUDA_ARCH_LIST`
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- [ ] Triton sm_121 support → remove `TORCHDYNAMO_DISABLE`
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- [ ] SageAttention prebuilt ARM64 wheels → remove source build
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## License
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MIT
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