update conda-forge installation guide
@@ -70,6 +70,9 @@ Part of the CUDA features in CuPy will be activated only when the corresponding
Installing CuPy
---------------
+Installing CuPy from PyPI
+~~~~~~~~~~~~~~~~~~~~~~~~~
+
Wheels (precompiled binary packages) are available for Linux (x86_64) and Windows (amd64).
Package names are different depending on your CUDA Toolkit version.
@@ -115,7 +118,7 @@ Please make sure that only one CuPy package (``cupy`` or ``cupy-cudaXX`` where X
.. _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 both Linux (x86_64,
@@ -136,9 +139,9 @@ However, if for any reason you need to force-install a particular CUDA version (
cuDNN, cuTENSOR, and NCCL are available on ``conda-forge`` as optional dependencies. The following command can install them all at once::
- $ conda install -c conda-forge cupy cudatoolkit=10.1 cudnn cutensor nccl
+ $ conda install -c conda-forge cupy cudnn cutensor nccl
- Each of them can also be installed separately as needed. Note that cuTENSOR is available since CUDA 10.1+.
+ Each of them can also be installed separately as needed. Note that cuTENSOR is available since CUDA 10.2+.
.. note::
@@ -153,15 +156,11 @@ However, if for any reason you need to force-install a particular CUDA version (
it from a local CUDA installation, you need to make sure the version of CUDA Toolkit matches that of ``cudatoolkit`` to
avoid surprises.
-.. note::
-
- Use ``conda install -c conda-forge/label/cupy_rc cupy`` if you want to install pre-release (development) versions.
-
.. _install_cupy_from_source:
Installing CuPy from Source
----------------------------
+~~~~~~~~~~~~~~~~~~~~~~~~~~~
Use of wheel packages is recommended whenever possible.
However, if wheels cannot meet your requirements (e.g., you are running non-Linux environment or want to use a version of CUDA / cuDNN / NCCL not supported by wheels), you can also build CuPy from source.
