update doc for CF
@@ -11,6 +11,9 @@ Requirements
* If you have multiple versions of CUDA Toolkit installed, CuPy will automatically choose one of the CUDA installations.
See :ref:`install_cuda` for details.
+ * This requirement is optional if you install CuPy from ``conda-forge``. However, you still need to have a compatible
+ driver installed for your GPU. See :ref:`install_cupy_from_conda_forge` for details.
+
* `Python <https://python.org/>`_: v3.6.0+ / v3.7.0+ / v3.8.0+ / v3.9.0+
.. note::
@@ -104,26 +107,28 @@ Please make sure that only one CuPy package (``cupy`` or ``cupy-cudaXX`` where X
$ pip freeze | grep cupy
+.. _install_cupy_from_conda_forge:
Installing CuPy from Conda-Forge
--------------------------------
Conda/Anaconda is a cross-platform package management solution widely used in scientific computing and other fields.
-The above ``pip install`` instruction is compatible with ``conda`` environments. Alternatively, for Linux 64 systems
-once the CUDA driver is correctly set up, you can install CuPy from the ``conda-forge`` channel::
+The above ``pip install`` instruction is compatible with ``conda`` environments. Alternatively, for both Linux and
+Windows once the CUDA driver is correctly set up, you can also install CuPy from the ``conda-forge`` channel::
$ conda install -c conda-forge cupy
and ``conda`` will install a pre-built CuPy binary package for you, along with CUDA runtime libraries
-(``cudatoolkit``). It is not necessary to install CUDA Toolkit in advance. If you need to enforce
-the installation of a particular CUDA version (say 10.0) for driver compatibility, you can do::
+(``cudatoolkit``). It is not necessary to install CUDA Toolkit in advance.
+
+Conda has a built-in mechanism to determine the latest version of ``cudatoolkit`` supported by your driver. However,
+if for any reason you need to force-install a particular CUDA version (say 10.0), you can do::
$ conda install -c conda-forge cupy cudatoolkit=10.0
.. note::
cuDNN, cuTENSOR, and NCCL are available on ``conda-forge`` as optional dependencies. The following command can install them all at once:
- support enabled, you can do::
$ conda install -c conda-forge cupy cudatoolkit=10.1 cudnn cutensor nccl
@@ -138,7 +143,8 @@ the installation of a particular CUDA version (say 10.0) for driver compatibilit
.. note::
If you did not install CUDA Toolkit yourselves, the ``nvcc`` compiler might not be available.
- The ``cudatoolkit`` package from Anaconda does not have ``nvcc`` included.
+ The ``cudatoolkit`` package from ``conda-forge`` does not have ``nvcc`` included. If you would like to use
+ a local CUDA installation, you need to make sure its version matches that of ``cudatoolkit`` to avoid surprises.
.. _install_cupy_from_source:
