OCR/openspec/changes/add-gpu-acceleration-support/tasks.md

Implementation Tasks

1. Environment Setup Enhancement

• 1.1 Add GPU detection function in setup_dev_env.sh
  • Detect NVIDIA GPU using nvidia-smi or lspci
  • Detect CUDA version if GPU is available
  • Output GPU detection results to user
• 1.2 Add conditional CUDA package installation
  • Install paddlepaddle-gpu with matching CUDA version when GPU detected
  • Install paddlepaddle (CPU-only) when no GPU detected
  • Handle different CUDA versions (11.x, 12.x, 13.x)
• 1.3 Add GPU verification step after installation
  • Test PaddlePaddle GPU availability
  • Report GPU status and CUDA version to user
  • Provide fallback instructions if GPU setup fails

2. Configuration Updates

• 2.1 Add GPU configuration to .env.local
  • Add FORCE_CPU_MODE option (default: false)
  • Add GPU_DEVICE_ID for device selection
  • Add GPU_MEMORY_FRACTION for memory allocation control
• 2.2 Update backend configuration
  • Add GPU settings to backend/app/core/config.py
  • Load GPU-related environment variables
  • Add validation for GPU configuration values

3. OCR Service GPU Integration

• 3.1 Add GPU detection in OCR service initialization
  • Create GPU availability check function
  • Detect available GPU devices
  • Log GPU status (available/unavailable, device name, memory)
• 3.2 Implement automatic GPU/CPU mode selection
  • Enable GPU mode in PaddleOCR when GPU is available
  • Fall back to CPU mode when GPU is unavailable or forced
  • Use global device setting via paddle.set_device() for PaddleOCR 3.x
• 3.3 Add GPU memory management
  • Set GPU memory fraction to prevent OOM errors
  • Detect GPU memory and compute capability
  • Handle GPU memory allocation failures gracefully
• 3.4 Update backend/app/services/ocr_service.py
  • Modify PaddleOCR initialization for PaddleOCR 3.x API
  • Add GPU status logging
  • Add error handling for GPU-related issues

4. Health Check and Monitoring

• 4.1 Add GPU status to health check endpoint
  • Report GPU availability (true/false)
  • Report GPU device name and compute capability
  • Report CUDA version
  • Report current GPU memory usage
• 4.2 Update backend/app/main.py
  • Add GPU status fields to health check response
  • Handle cases where GPU detection fails

5. Documentation Updates

• 5.1 Update README.md
  • Add GPU requirements section
  • Document GPU detection and setup process
  • Add troubleshooting for GPU issues
• 5.2 Update openspec/project.md
  • Add GPU hardware recommendations
  • Document CUDA version compatibility
  • Add GPU-specific configuration options
• 5.3 Create GPU setup guide
  • Document NVIDIA driver installation for WSL
  • Document CUDA toolkit installation
  • Provide GPU verification steps
• 5.4 Document known limitations
  • Chart recognition feature disabled (PaddlePaddle 3.0.0 API limitation) RESOLVED
  • Document fused_rms_norm_ext API incompatibility RESOLVED in PaddlePaddle 3.2.1+
  • Updated README to reflect chart recognition is now enabled
  • Created CHART_RECOGNITION.md with detailed status and history

6. Testing

• 6.1 Test GPU detection on GPU-enabled system
  • Verify correct CUDA version detection
  • Verify correct PaddlePaddle GPU installation
  • Verify OCR processing uses GPU
• 6.2 Test CPU fallback on non-GPU system
  • Verify CPU-only installation
  • Verify OCR processing works without GPU
  • Verify no errors or warnings about missing GPU
• 6.3 Test FORCE_CPU_MODE override
  • Verify GPU is ignored when FORCE_CPU_MODE=true
  • Verify CPU processing works on GPU-enabled system
• 6.4 Performance benchmarking
  • Measure OCR processing time with GPU
  • Measure OCR processing time with CPU
  • Document performance improvements

7. Error Handling and Edge Cases

• 7.1 Handle GPU out-of-memory errors
  • Catch CUDA OOM exceptions
  • Automatically fall back to CPU mode
  • Log warning message to user
• 7.2 Handle CUDA version mismatch
  • Detect PaddlePaddle/CUDA compatibility issues
  • Provide clear error messages
  • Suggest correct CUDA version installation
• 7.3 Handle missing NVIDIA drivers
  • Detect when GPU hardware exists but drivers are missing
  • Provide installation instructions
  • Fall back to CPU mode gracefully