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---
parent: Setup
nav_order: 0
---
# Requirements
All requirements are applicable to the `main` branch on GitHub.
For details on specific releases, please see the [changelog].
## Usage Requirements
To use the NVIDIA C++ Standard Library, you must meet the following
requirements.
### System Software
The NVIDIA C++ Standard Library requires either the [NVIDIA HPC SDK] or the
[CUDA Toolkit].
libcu++ was first released in NVHPC 20.3 and CUDA 10.2.
Some features are only available in newer releases.
Please see the [Standard API section], [Extended API section], and
[release section] to find which features require newer releases.
Releases of libcu++ are only tested against the latest releases of NVHPC and
CUDA.
It may be possible to use a newer version of libcu++ with an older NVHPC or
CUDA installation by using a libcu++ release from GitHub, but please be aware
this is not officially supported.
### C++ Dialects
The NVIDIA C++ Standard Library supports the following C++ dialects:
- C++11
- C++14
- C++17
A number of features have been backported to earlier standards.
Please see the [API section] for more details.
### NVCC Host Compilers
When used with NVCC, the NVIDIA C++ Standard Library supports the following host
compilers:
- MSVC 2017 and 2019.
- GCC 5, 6, 7, 8, 9, and 10.
- Clang 7, 8, 9, and 10.
- ICPC latest.
- NVHPC 20.9 and 20.11.
### Device Architectures
The NVIDIA C++ Standard Library fully supports the following NVIDIA device
architectures:
- Volta: SM 70 and 72.
- Turing: SM 75.
- Ampere: SM 80.
The following NVIDIA device architectures are partially supported:
- Maxwell: SM 50, 52 and 53.
- Synchronization facilities are supported.
- Pascall: SM 60, 61 and 62.
- Blocking synchronization facilities (e.g. most of the synchronization
primitives) are not supported.
Please see the [synchronization primitives section] for details.
### Host Architectures
The NVIDIA C++ Standard Library supports the following host architectures:
- aarch64.
- x86-64.
- ppc64le.
### Host Operating Systems
The NVIDIA C++ Standard Library supports the following host operating systems:
- Linux.
- Windows.
- Android.
- QNX.
## Build and Test Requirements
To build and test libcu++ yourself, you will need the following in addition to
the usage requirements:
- [CMake].
- [LLVM].
- You do not have to build LLVM; we only need its CMake modules.
- [lit], the LLVM Integrated Tester.
- We recommend installing lit using Python's pip package manager.
[Standard API section]: ../standard_api.md
[Extended API section]: ../extended_api.md
[synchronization primitives section]: ../extended_api/synchronization_primitives.md
[changelog]: ../releases/changelog.md
[NVIDIA HPC SDK]: https://developer.nvidia.com/hpc-sdk
[CUDA Toolkit]: https://developer.nvidia.com/cuda-toolkit
[CMake]: https://cmake.org
[LLVM]: https://github.com/llvm
[lit]: https://pypi.org/project/lit/
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