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Merge pull request #150 from DrDaveD/sylabs117
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Update Windows instructions to WSL2
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@DrDaveD
DrDaveD authored Mar 8, 2024
2 parents 9624c5d + 45d8aa2 commit 74172a6
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Expand Up @@ -530,89 +530,96 @@ targets from the ``builddir`` directory in the source tree:

Linux container runtimes like {Project} cannot run natively on
Windows or Mac because of basic incompatibilities with the host kernel.
(Contrary to a popular misconception, MacOS does not run on a Linux
(Contrary to a popular misconception, macOS does not run on a Linux
kernel. It runs on a kernel called Darwin originally forked from BSD.)

In order to use {Project} on these platforms, you can install Vagrant
Boxes via `Vagrant Cloud <https://www.vagrantup.com/>`__, one of
`Hashicorp's <https://www.hashicorp.com/>`_
tools, by following the instructions below. Then you can install
{Project} in the base VM of your choice by following the linux
:ref:`installation instructions <installation>` above.

You can also use `Lima <https://github.com/lima-vm/lima>`_ to install
both the Linux VM and {Project} for access from the host operating system.
It will install the "cloud" version of the selected VM operating system.
To run {Project} on a Windows or macOS computer, a Linux virtual machine
(VM) is required. There are various ways to configure a VM on both Windows and
macOS. On Windows, we recommend the Windows Subsystem for Linux (WSL2), and
on macOS, we recommend Lima.

Windows
=======

Vagrant
-------

Install the following programs:

- `Git for Windows <https://git-for-windows.github.io/>`_
- `VirtualBox for Windows <https://www.virtualbox.org/wiki/Downloads>`_
- `Vagrant for Windows <https://www.vagrantup.com/downloads.html>`_
- `Vagrant Manager for Windows <http://vagrantmanager.com/downloads/>`_

Lima
----

The Windows version of Lima (using Hyper-V) is still in development.
Recent builds of Windows 10, and all builds of Windows 11, include version 2 of
the Windows Subsystem for Linux. WSL2 provides a Linux virtual machine that is
tightly integrated with the Windows environment. The default Linux distribution
used by WSL2 is Ubuntu. It is straightforward to install {Project} inside
WSL2 Ubuntu, and use all of its features.

You can use `WSL <https://docs.microsoft.com/en-us/windows/wsl/>`_ instead:
Follow the `WSL2 installation instructions
<https://docs.microsoft.com/en-us/windows/wsl/install>`__ to enable WSL2 with
the default Ubuntu 22.04 environment. On Windows 11 and the most recent builds
of Windows 10 this is as easy as opening an administrator command prompt or
Powershell window and entering:

.. code::
> wsl --install
wsl --install
And use the Linux instructions.
Follow the prompts. A restart is required, and when you open the 'Ubuntu' app
for the first time you'll be asked to set a username and password for the Linux
environment.

Mac
===
You can then install {Project} from `source <#install-from-source>`_,
from the `Debian packages <#install-debian-packages>`_
on the {Project} release page,
or from the `Ubuntu PPA <#install-ubuntu-packages>`_.

Vagrant
-------

{Project} is available via Vagrant (installable with `Homebrew
<https://brew.sh>`_ or manually)
GPU Support
-----------

To use Vagrant via Homebrew:
WSL2 supports using an NVIDIA GPU from the Linux environment. To use a GPU from
{Project} in WSL2, you must first install ``libnvidia-container-tools``,
following the instructions in the `libnvidia-container documentation
<https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html>`__:

.. code::
$ /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
$ brew install --cask virtualbox vagrant vagrant-manager
Use ``vagrant init`` to create a new Vagrantfile, or use this example:

.. code-block:: ruby
:class: copy-button
Vagrant.configure("2") do |config|
# Choose operating system distribution
config.vm.box = "fedora/38-cloud-base"
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list \
sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit
config.vm.provider "virtualbox" do |vb|
# Customize the number of cpus on the VM:
vb.cpus = "1"
Once this process has been completed, GPU containers can be run under WSL2 using
the ``--nv`` and ``--nvccli`` flags together:

# Customize the amount of memory on the VM:
vb.memory = "1024"
end
config.vm.provision "shell", inline: <<-SHELL
# Matching linux installation instructions
yum install -y {command}
SHELL
end
.. code::
Then do ``vagrant up``, and ``vagrant ssh`` to access the virtual machine.
$ {command} pull docker://tensorflow/tensorflow:latest-gpu
$ {command} run --nv --nvccli tensorflow_latest-gpu.sif
INFO: Setting 'NVIDIA_VISIBLE_DEVICES=all' to emulate legacy GPU binding.
INFO: Setting --writable-tmpfs (required by nvidia-container-cli)
________ _______________
___ __/__________________________________ ____/__ /________ __
__ / _ _ \_ __ \_ ___/ __ \_ ___/_ /_ __ /_ __ \_ | /| / /
_ / / __/ / / /(__ )/ /_/ / / _ __/ _ / / /_/ /_ |/ |/ /
/_/ \___//_/ /_//____/ \____//_/ /_/ /_/ \____/____/|__/
You are running this container as user with ID 1000 and group 1000,
which should map to the ID and group for your user on the Docker host. Great!
{Project}> python
Python 3.8.10 (default, Nov 26 2021, 20:14:08)
[GCC 9.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> tf.config.list_physical_devices('GPU')
2022-03-25 11:42:25.672088: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:922] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2022-03-25 11:42:25.713295: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:922] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2022-03-25 11:42:25.713892: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:922] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]
Note that the ``--nvccli`` flag is required to enable container setup using the
``nvidia-container-cli`` utility. {Project}'s simpler library binding
approach (``--nv`` only) is not sufficient for GPU support under WSL2.

Lima
----
Mac
===

{Project} is available via Lima (installable with `Homebrew
<https://brew.sh>`_ or manually)
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