⌘KCtrl+K
| Symptom | Cause | Fix |
|---|---|---|
| PyTorch CUDA not available | Incorrect CUDA version or missing drivers | Verify nvcc --version matches cu129, reinstall PyTorch |
| Model download fails | Network connectivity or storage space | Check internet connection, verify 20GB+ available space |
| Web interface inaccessible | Firewall blocking port 8188 | Configure firewall to allow port 8188, check IP address |
| Out of GPU memory errors after manually flushing buffer cache | Insufficient VRAM for model | Use smaller models or enable CPU fallback mode |
NOTE
DGX Spark uses a Unified Memory Architecture (UMA), which enables dynamic memory sharing between the GPU and CPU. With many applications still updating to take advantage of UMA, you may encounter memory issues even when within the memory capacity of DGX Spark. If that happens, manually flush the buffer cache with:
sudo sh -c 'sync; echo 3 > /proc/sys/vm/drop_caches'
For latest known issues, please review the DGX Spark User Guide.