C++ Installation
C++ Installation
Use this page when you need the NVIDIA cuVS C++ headers, libcuvs shared library, and native C++ APIs.
All NVIDIA cuVS routine implementations live in the C++ core. The C++ API links directly to libcuvs; the C API and all non-C++ language bindings also need libcuvs_c installed with libcuvs.
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.
The libcuvs package installs the C++ headers, C headers, libcuvs, and libcuvs_c.
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:
Add the extracted library directory to your loader path:
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:
This installs libcuvs.so, libcuvs_c.so, headers, and downloaded dependencies into $INSTALL_PREFIX by default. Pass -n to build without installing.
Uninstall the native libraries with:
Disable multi-GPU features with:
Build the C and C++ tests with:
Use CMake Directly
Use the root build.sh script for most builds. When you need finer CMake control, configure from the cpp directory:
Common CMake flags include: