Files
celery/scripts/setup-gpu-droplet.sh
giles 86830019ad Add IPFS HLS streaming and GPU optimizations
- Add IPFSHLSOutput class that uploads segments to IPFS as they're created
- Update streaming task to use IPFS HLS output for distributed streaming
- Add /ipfs-stream endpoint to get IPFS playlist URL
- Update /stream endpoint to redirect to IPFS when available
- Add GPU persistence mode (STREAMING_GPU_PERSIST=1) to keep frames on GPU
- Add hardware video decoding (NVDEC) support for faster video processing
- Add GPU-accelerated primitive libraries: blending_gpu, color_ops_gpu, geometry_gpu
- Add streaming_gpu module with GPUFrame class for tracking CPU/GPU data location
- Add Dockerfile.gpu for building GPU-enabled worker image

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 20:23:16 +00:00

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#!/bin/bash
# Setup script for GPU droplet with NVENC support
# Run as root on a fresh Ubuntu droplet with NVIDIA GPU
set -e
echo "=== ArtDAG GPU Droplet Setup ==="
# 1. System updates
echo "[1/7] Updating system..."
apt-get update
apt-get upgrade -y
# 2. Install NVIDIA drivers (if not already installed)
echo "[2/7] Checking NVIDIA drivers..."
if ! command -v nvidia-smi &> /dev/null; then
echo "Installing NVIDIA drivers..."
apt-get install -y nvidia-driver-535 nvidia-utils-535
echo "NVIDIA drivers installed. Reboot required."
echo "After reboot, run this script again."
exit 0
fi
nvidia-smi
echo "NVIDIA drivers OK"
# 3. Install FFmpeg with NVENC support
echo "[3/7] Installing FFmpeg with NVENC..."
apt-get install -y ffmpeg
# Verify NVENC
if ffmpeg -encoders 2>/dev/null | grep -q nvenc; then
echo "NVENC available:"
ffmpeg -encoders 2>/dev/null | grep nvenc
else
echo "WARNING: NVENC not available. GPU may not support hardware encoding."
fi
# 4. Install Python and create venv
echo "[4/7] Setting up Python environment..."
apt-get install -y python3 python3-venv python3-pip git
VENV_DIR="/opt/artdag-gpu"
python3 -m venv "$VENV_DIR"
source "$VENV_DIR/bin/activate"
# 5. Install Python dependencies
echo "[5/7] Installing Python packages..."
pip install --upgrade pip
pip install \
numpy \
opencv-python-headless \
wgpu \
httpx \
pyyaml \
celery[redis] \
fastapi \
uvicorn
# 6. Clone/update art-dag code
echo "[6/7] Setting up art-dag code..."
ARTDAG_DIR="$VENV_DIR/celery"
if [ -d "$ARTDAG_DIR" ]; then
echo "Updating existing code..."
cd "$ARTDAG_DIR"
git pull || true
else
echo "Cloning art-dag..."
git clone https://git.rose-ash.com/art-dag/celery.git "$ARTDAG_DIR" || {
echo "Git clone failed. You may need to copy code manually."
}
fi
# 7. Test GPU compute
echo "[7/7] Testing GPU compute..."
"$VENV_DIR/bin/python3" << 'PYTEST'
import sys
try:
import wgpu
adapter = wgpu.gpu.request_adapter_sync(power_preference="high-performance")
print(f"GPU Adapter: {adapter.info.get('device', 'unknown')}")
device = adapter.request_device_sync()
print("wgpu device created successfully")
# Check for NVENC via FFmpeg
import subprocess
result = subprocess.run(['ffmpeg', '-encoders'], capture_output=True, text=True)
if 'h264_nvenc' in result.stdout:
print("NVENC H.264 encoder: AVAILABLE")
else:
print("NVENC H.264 encoder: NOT AVAILABLE")
if 'hevc_nvenc' in result.stdout:
print("NVENC HEVC encoder: AVAILABLE")
else:
print("NVENC HEVC encoder: NOT AVAILABLE")
except Exception as e:
print(f"Error: {e}")
sys.exit(1)
PYTEST
echo ""
echo "=== Setup Complete ==="
echo "Venv: $VENV_DIR"
echo "Code: $ARTDAG_DIR"
echo ""
echo "To activate: source $VENV_DIR/bin/activate"
echo "To test: cd $ARTDAG_DIR && python -c 'from streaming.backends import get_backend; print(get_backend(\"wgpu\"))'"