Add documentation
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Aurelien Lourot
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README.md
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README.md
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This subordinate charm provides the Nvidia vGPU support to the
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[OpenStack Nova Compute service][charm-nova-compute].
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# Usage
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## Deployment
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We are assuming a pre-existing OpenStack deployment (Queens or newer).
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Deploy nova-compute-nvidia-vgpu as a subordinate to the nova-compute charm:
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juju deploy ch:nova-compute-nvidia-vgpu --channel=yoga/edge
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juju add-relation nova-compute-nvidia-vgpu:nova-vgpu nova-compute:nova-vgpu
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Pass the [proprietary NVIDIA software package][nvidia-software] (`510.47.03` or
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newer) as a resource to the charm:
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juju attach nova-compute-nvidia-vgpu \
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nvidia-vgpu-software=./nvidia-vgpu-ubuntu-510_510.47.03_amd64.deb
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Once the model settles, reboot the corresponding compute nodes:
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juju run -a nova-compute-nvidia-vgpu -- sudo reboot
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### vGPU type definition
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Each compute node has one or several physical GPUs. Each physical GPU can then
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be divided into one or several [virtual GPUs][virtual-gpu] of a given type.
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Virtual GPUs will later be claimed by and exposed to guests upon guest
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creation. Start by listing the available vGPU types for each physical GPU:
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juju run-action nova-compute-nvidia-vgpu/0 list-vgpu-types --wait
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[...]
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nvidia-256, 0000:41:00.0, GRID RTX6000-1Q, num_heads=4, frl_config=60, framebuffer=1024M, max_resolution=5120x2880, max_instance=24
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nvidia-257, 0000:41:00.0, GRID RTX6000-2Q, num_heads=4, frl_config=60, framebuffer=2048M, max_resolution=7680x4320, max_instance=12
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nvidia-258, 0000:41:00.0, GRID RTX6000-3Q, num_heads=4, frl_config=60, framebuffer=3072M, max_resolution=7680x4320, max_instance=8
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nvidia-259, 0000:41:00.0, GRID RTX6000-4Q, num_heads=4, frl_config=60, framebuffer=4096M, max_resolution=7680x4320, max_instance=6
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[...]
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nvidia-105, 0000:c1:00.0, GRID V100-1Q, num_heads=4, frl_config=60, framebuffer=1024M, max_resolution=5120x2880, max_instance=16
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nvidia-106, 0000:c1:00.0, GRID V100-2Q, num_heads=4, frl_config=60, framebuffer=2048M, max_resolution=7680x4320, max_instance=8
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nvidia-107, 0000:c1:00.0, GRID V100-4Q, num_heads=4, frl_config=60, framebuffer=4096M, max_resolution=7680x4320, max_instance=4
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nvidia-108, 0000:c1:00.0, GRID V100-8Q, num_heads=4, frl_config=60, framebuffer=8192M, max_resolution=7680x4320, max_instance=2
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[...]
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As we can see, `nova-compute-nvidia-vgpu/0` has two physical GPUs:
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`0000:41:00.0` and `0000:c1:00.0`. By selecting the vGPU type `nvidia-108` on
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`0000:c1:00.0`, two vGPUs will be available for future guests:
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juju config nova-compute-nvidia-vgpu vgpu-device-mappings="{'nvidia-108': ['0000:c1:00.0']}"
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> **NOTE**: on releases older than Stein, only one vGPU type can be selected
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> accross all available physical GPUs. Starting from Stein each physical GPU
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> can be assigned a different vGPU type.
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On OpenStack Stein and newer, once the model has settled, these vGPUs can be
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listed via the OpenStack CLI:
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openstack resource provider list
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+--------------------------------------+-----------------------------------+------------+--------------------------------------+--------------------------------------+
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| uuid | name | generation | root_provider_uuid | parent_provider_uuid |
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+--------------------------------------+-----------------------------------+------------+--------------------------------------+--------------------------------------+
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| 0883c2b5-bad2-4abc-a179-e33344361475 | node-sparky.maas | 2 | 0883c2b5-bad2-4abc-a179-e33344361475 | None |
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| 4b0dbc58-0c85-4a80-8dd6-d43d1bd6ec53 | node-sparky.maas_pci_0000_c1_00_0 | 1 | 0883c2b5-bad2-4abc-a179-e33344361475 | 0883c2b5-bad2-4abc-a179-e33344361475 |
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+--------------------------------------+-----------------------------------+------------+--------------------------------------+--------------------------------------+
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openstack resource provider inventory list 4b0dbc58-0c85-4a80-8dd6-d43d1bd6ec53
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+----------------+------------------+----------+----------+----------+-----------+-------+------+
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| resource_class | allocation_ratio | min_unit | max_unit | reserved | step_size | total | used |
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+----------------+------------------+----------+----------+----------+-----------+-------+------+
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| VGPU | 1.0 | 1 | 2 | 0 | 1 | 2 | 0 |
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+----------------+------------------+----------+----------+----------+-----------+-------+------+
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### Nova flavor definition
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In order to expose a vGPU of the type defined earlier to any guest created with
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the `m1.small` flavor, create a new trait and assign it to the flavor:
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openstack --os-placement-api-version 1.6 trait create CUSTOM_NVIDIA_108
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openstack --os-placement-api-version 1.6 resource provider trait set --trait CUSTOM_NVIDIA_108 4b0dbc58-0c85-4a80-8dd6-d43d1bd6ec53
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openstack flavor set m1.small --property resources:VGPU=1 --property trait:CUSTOM_NVIDIA_108=required
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> **NOTE**: on releases older than Stein, since there is only one vGPU type
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> and it doesn't show up in the resource provider list, no trait can be
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> created. The flavor can simply be modified with
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> `openstack flavor set m1.small --property resources:VGPU=1`
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After creating an instance of this flavor, the resource provider inventory
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list will show one vGPU being used:
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openstack server create --flavor m1.small ...
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openstack resource provider inventory list 4b0dbc58-0c85-4a80-8dd6-d43d1bd6ec53
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+----------------+------------------+----------+----------+----------+-----------+-------+------+
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| resource_class | allocation_ratio | min_unit | max_unit | reserved | step_size | total | used |
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+----------------+------------------+----------+----------+----------+-----------+-------+------+
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| VGPU | 1.0 | 1 | 2 | 0 | 1 | 2 | 1 |
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+----------------+------------------+----------+----------+----------+-----------+-------+------+
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# Bugs
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Please report bugs on [Launchpad][lp-bugs-nova-nvidia].
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@ -14,3 +108,5 @@ For general questions please refer to the [OpenStack Charm Guide][cg].
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[charm-nova-compute]: https://jaas.ai/nova-compute
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[cg]: https://docs.openstack.org/charm-guide
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[lp-bugs-nova-nvidia]: https://bugs.launchpad.net/charm-nova-compute-nvidia-vgpu/+filebug
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[nvidia-software]: https://docs.nvidia.com/grid/index.html
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[virtual-gpu]: https://docs.openstack.org/nova/ussuri/admin/virtual-gpu.html
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