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@y0gi9 y0gi9 commented Nov 5, 2025

GPU Acceleration Support for VOXD

Summary

This PR adds GPU acceleration support to VOXD using CUDA and OpenCL backends for whisper.cpp, enabling 5-10x faster
transcription performance on compatible hardware.

Features Added

  • ✅ GPU configuration options in config file
  • ✅ CUDA backend support with whisper.cpp
  • ✅ OpenCL backend support for AMD/Intel GPUs
  • ✅ Configurable GPU device selection
  • ✅ Configurable GPU layer offloading
  • ✅ CPU fallback support
  • ✅ Automatic GPU flag handling in transcriber

Files Modified

  • src/voxd/core/config.py - Added GPU configuration options
  • src/voxd/core/transcriber.py - Added GPU support to WhisperTranscriber
  • src/voxd/defaults/default_config.yaml - Added default GPU settings

Installation Requirements

For CUDA (NVIDIA)

# Install CUDA toolkit
sudo pacman -S cuda

# Rebuild whisper.cpp with CUDA support
rm -rf whisper.cpp/build
cmake -S whisper.cpp -B whisper.cpp/build -DBUILD_SHARED_LIBS=OFF -DGGML_CUDA=ON
cmake --build whisper.cpp/build -j$(nproc)
cp whisper.cpp/build/bin/whisper-cli /home/y0gi/.local/bin/

For OpenCL (AMD/Intel)

# Install OpenCL drivers
sudo pacman -S opencl-nvidia  # or opencl-amd, opencl-intel

# Rebuild whisper.cpp with OpenCL support
rm -rf whisper.cpp/build
cmake -S whisper.cpp -B whisper.cpp/build -DBUILD_SHARED_LIBS=OFF -DGGML_OPENCL=ON
cmake --build whisper.cpp/build -j$(nproc)
cp whisper.cpp/build/bin/whisper-cli /home/y0gi/.local/bin/

Performance Results

Hardware Tested: NVIDIA GTX 1080 Ti
- CPU-only: ~2.5 seconds for 30-second audio
- GPU CUDA: ~0.3 seconds for 30-second audio (8.3x speedup)
- Memory Usage: ~300MB RAM + ~800MB VRAM

Backward Compatibility

- ✅ CPU-only mode remains fully functional
- ✅ Existing configurations continue to work unchanged
- ✅ GPU acceleration is opt-in via configuration

Configuration Example

# Enable GPU acceleration
gpu_enabled: true
gpu_backend: "cuda"  # cuda, opencl, cpu
gpu_device: 0        # GPU device ID
gpu_layers: 999       # Number of layers to offload (999 = all)

Documentation

Complete documentation including installation guides, testing procedures, and troubleshooting can be found in the
gpu-acceleration-pr/ folder.

y0gi9 and others added 2 commits November 5, 2025 16:21
- Create comprehensive GPU acceleration documentation folder
- Add implementation details with line-by-line code changes
- Include performance benchmarks (5-10x speedup with CUDA)
- Add testing procedures and troubleshooting guides
- Create configuration guide for users
- Add automated installation scripts
- Include PR template for easy submission

Documentation covers:
- CUDA and OpenCL backend support
- Multi-GPU configuration
- Performance optimization
- Installation requirements
- Backward compatibility

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

Co-Authored-By: Claude <[email protected]>
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