C Installation

Use this page when you need the NVIDIA cuVS C API, headers, and libcuvs_c shared library. The C API is the stable ABI boundary used by downstream integrations and language bindings.

All NVIDIA cuVS routine implementations live in the C++ core. The C API calls into that core, so C applications need both libcuvs_c and libcuvs installed at runtime.

Install Pre-Compiled Packages

The easiest way to install the C API is through conda. Use miniforge for a minimal conda installation, and prefer mamba when available.

$
# CUDA 13
$
conda install -c rapidsai -c conda-forge libcuvs cuda-version=13.2
$
$
# CUDA 12
$
conda install -c rapidsai -c conda-forge libcuvs cuda-version=12.9

The libcuvs package installs the C headers, C++ headers, libcuvs_c, and libcuvs.

Tarball

Pre-built tarballs are available from developer.nvidia.com/cuvs-downloads. Tarball installs require NCCL, libopenmp, CUDA Toolkit runtime 12.2 or newer, and an Ampere architecture GPU or newer.

Download the tarball for your CPU architecture and CUDA version, then extract it:

$
tar -xzvf libcuvs-linux-sbsa-26.02.00.189485_cuda12-archive.tar.xz -C /path/to/folder

Add the extracted library directory to your loader path:

$
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/path/to/folder

Build From Source

Before building from source, review the shared C++ source-build prerequisites, including the recommended conda environment setup for build dependencies.

Build and install the native C and C++ libraries together:

$
./build.sh libcuvs

This installs libcuvs_c.so, libcuvs.so, headers, and downloaded dependencies into $INSTALL_PREFIX by default. Pass -n to build without installing.

Uninstall the native libraries with:

$
./build.sh libcuvs --uninstall

Disable multi-GPU features with:

$
./build.sh libcuvs --no-mg

Build the C and C++ tests with:

$
./build.sh libcuvs tests

Build a limited set of tests with:

$
./build.sh libcuvs tests -n --limit-tests='NEIGHBORS_TEST;CAGRA_C_TEST'