curaster 0.2.0

CUDA-accelerated Raster Algebra Calculator

cuRaster

Curaster is a high-performance Python module written in C++ and CUDA. It is designed to compute the Normalized Difference Vegetation Index (NDVI) on massive raster datasets using GPU.

Installation

Install the precompiled wheel via pip:

pip install curaster

Requirements (for building from source)

To build and run this module from source, your system needs:

• NVIDIA GPU with CUDA Toolkit installed (nvcc)
• GDAL C++ library (libgdal-dev)
• CMake 3.18+
• pybind11 (pip install pybind11)
• A C++17-compatible compiler

Usage

Once installed, simply import it into Python:

import curaster

curaster.ndvi(
    input_file="data/massive_satellite_image.tif",
    output_file="data/output_ndvi.tif",
    red_band_index=3,
    nir_band_index=4,
    chunk_size=256,    # Align this with your TIFF's BLOCKYSIZE for max speed
    verbose=True
)

API Reference

curaster.ndvi(...)

Calculates (NIR - Red) / (NIR + Red) and saves the result to a new single-band Float32 GeoTIFF.

Argument	Type	Default	Description
input_file	str	Required	Path to the input multispectral raster.
output_file	str	Required	Path where the output NDVI raster will be saved.
red_band_index	int	Required	The GDAL band number (1-indexed) containing Red data.
nir_band_index	int	Required	The GDAL band number (1-indexed) containing NIR data.
chunk_size	int	256	The number of horizontal rows to process at a time.
verbose	bool	True	If true, prints a progress bar to the terminal.

Building from Source

To build from source using CMake:

mkdir build
cd build
cmake .. -Dpybind11_DIR=$(python -c "import pybind11; print(pybind11.get_cmake_dir())")
make

Alternatively, you can compile directly with nvcc:

nvcc -O3 -shared -std=c++17 -Xcompiler -fPIC \
    -o curaster$(python3-config --extension-suffix) src/raster.cu \
    $(python3 -m pybind11 --includes) \
    $(gdal-config --cflags) $(gdal-config --libs)

License

See LICENSE file for details.