requirements-gpu.txt

# Requirements file for GPU-accelerated dependencies
# Based on CUDA and PyTorch requirements from protein design tools

# PyTorch with CUDA 12.1 support
torch>=2.0.0
torchvision>=0.15.0
torchaudio>=2.0.0

# CUDA-accelerated scientific computing
cupy-cuda12x>=12.0.0
numba>=0.58.0

# GPU-accelerated data processing
cudf>=23.0.0; platform_machine == "x86_64"
cuml>=23.0.0; platform_machine == "x86_64"
cugraph>=23.0.0; platform_machine == "x86_64"

# GPU monitoring and profiling
nvidia-ml-py>=12.0.0
py-spy>=0.3.14
memory-profiler>=0.61.0

# Distributed computing with GPU support
dask[distributed]>=2023.5.0
dask-cuda>=23.0.0; platform_machine == "x86_64"

# Machine learning accelerated libraries
xgboost[gpu]>=1.7.0
lightgbm>=4.0.0
catboost>=1.2.0

# Image processing with GPU acceleration
opencv-python-headless>=4.8.0
pillow-simd>=9.0.0; platform_machine == "x86_64"

# GPU-accelerated linear algebra
scipy>=1.11.0
scikit-learn>=1.3.0

# NVIDIA RAPIDS (for compatible systems)
# Note: These may require specific CUDA versions and architectures
# rapids-cudf>=23.0.0; platform_machine == "x86_64"
# rapids-cuml>=23.0.0; platform_machine == "x86_64"

# GPU profiling and debugging tools
tensorboard>=2.13.0
pytest-benchmark>=4.0.0

# Memory optimization for GPU workloads
psutil>=5.9.0
pympler>=0.9