Files
OCR/openspec/changes/add-gpu-acceleration-support/tasks.md
egg 6452797abe feat: add GPU acceleration support OpenSpec proposal
新增 GPU 加速支援的 OpenSpec 變更提案

主要內容:
- 在環境建置腳本中加入 GPU 偵測功能
- 自動安裝對應 CUDA 版本的 PaddlePaddle GPU 套件
- 在 OCR 處理程式中加入 GPU 可用性偵測
- 自動啟用 GPU 加速(可用時)或使用 CPU(不可用時)
- 支援強制 CPU 模式選項
- 加入 GPU 狀態報告到健康檢查 API

變更範圍:
- 新增 capability: environment-setup (環境設置)
- 修改 capability: ocr-processing (加入 GPU 支援)

實作任務包含:
1. 環境設置腳本增強 (GPU 偵測、CUDA 安裝)
2. 配置更新 (GPU 相關環境變數)
3. OCR 服務 GPU 整合 (自動偵測、記憶體管理)
4. 健康檢查與監控 (GPU 狀態報告)
5. 文檔更新
6. 測試與效能評估
7. 錯誤處理與邊界情況

預期效果:
- GPU 系統: 3-10x OCR 處理速度提升
- CPU 系統: 無影響,向後相容
- 自動硬體偵測與優化配置

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-14 07:34:06 +08:00

3.9 KiB

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 (11.2, 11.6, 11.7, 12.0, etc.)
  • 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 CUDA_VERSION for manual override
    • 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
    • Set appropriate use_gpu parameter for PaddleOCR initialization
  • 3.3 Add GPU memory management
    • Set GPU memory fraction to prevent OOM errors
    • Adjust batch size based on GPU memory availability
    • Handle GPU memory allocation failures gracefully
  • 3.4 Update backend/app/services/ocr_service.py
    • Modify PaddleOCR initialization with GPU parameters
    • 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/api/v1/endpoints/health.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

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