8f2c17e334
Refresh and rebuild charm for awareness of Dalmatian and Epoxy Cloud Archive releases. Change-Id: I7e7b7ef9f503794c40a648c4bef53cb14ee4f2bf |
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src | ||
templates | ||
tests | ||
unit_tests | ||
.gitignore | ||
.gitreview | ||
.stestr.conf | ||
.zuul.yaml | ||
actions.yaml | ||
charmcraft.yaml | ||
config.yaml | ||
metadata.yaml | ||
osci.yaml | ||
pip.sh | ||
README.md | ||
rebuild | ||
rename.sh | ||
requirements.txt | ||
test-requirements.txt | ||
tox.ini |
Overview
This subordinate charm provides the Nvidia vGPU support to the OpenStack Nova Compute service.
Usage
Deployment
We are assuming a pre-existing OpenStack deployment (Queens or newer).
Deploy nova-compute-nvidia-vgpu as a subordinate to the nova-compute charm:
juju deploy ch:nova-compute-nvidia-vgpu --channel=yoga/edge
juju add-relation nova-compute-nvidia-vgpu:nova-vgpu nova-compute:nova-vgpu
Pass the proprietary NVIDIA software package (510.47.03
or
newer) as a resource to the charm:
juju attach nova-compute-nvidia-vgpu \
nvidia-vgpu-software=./nvidia-vgpu-ubuntu-510_510.47.03_amd64.deb
Once the model settles, reboot the corresponding compute nodes:
juju run -a nova-compute-nvidia-vgpu -- sudo reboot
vGPU type definition
Each compute node has one or several physical GPUs. Each physical GPU can then be divided into one or several virtual GPUs of a given type. Virtual GPUs will later be claimed by and exposed to guests upon guest creation. Start by listing the available vGPU types for each physical GPU:
juju run-action nova-compute-nvidia-vgpu/0 list-vgpu-types --wait
[...]
nvidia-256, 0000:41:00.0, GRID RTX6000-1Q, num_heads=4, frl_config=60, framebuffer=1024M, max_resolution=5120x2880, max_instance=24
nvidia-257, 0000:41:00.0, GRID RTX6000-2Q, num_heads=4, frl_config=60, framebuffer=2048M, max_resolution=7680x4320, max_instance=12
nvidia-258, 0000:41:00.0, GRID RTX6000-3Q, num_heads=4, frl_config=60, framebuffer=3072M, max_resolution=7680x4320, max_instance=8
nvidia-259, 0000:41:00.0, GRID RTX6000-4Q, num_heads=4, frl_config=60, framebuffer=4096M, max_resolution=7680x4320, max_instance=6
[...]
nvidia-105, 0000:c1:00.0, GRID V100-1Q, num_heads=4, frl_config=60, framebuffer=1024M, max_resolution=5120x2880, max_instance=16
nvidia-106, 0000:c1:00.0, GRID V100-2Q, num_heads=4, frl_config=60, framebuffer=2048M, max_resolution=7680x4320, max_instance=8
nvidia-107, 0000:c1:00.0, GRID V100-4Q, num_heads=4, frl_config=60, framebuffer=4096M, max_resolution=7680x4320, max_instance=4
nvidia-108, 0000:c1:00.0, GRID V100-8Q, num_heads=4, frl_config=60, framebuffer=8192M, max_resolution=7680x4320, max_instance=2
[...]
As we can see, nova-compute-nvidia-vgpu/0
has two physical GPUs:
0000:41:00.0
and 0000:c1:00.0
. By selecting the vGPU type nvidia-108
on
0000:c1:00.0
, two vGPUs will be available for future guests:
juju config nova-compute-nvidia-vgpu vgpu-device-mappings="{'nvidia-108': ['0000:c1:00.0']}"
Note
: on releases older than Stein, only one vGPU type can be selected accross all available physical GPUs. Starting from Stein each physical GPU can be assigned a different vGPU type.
On OpenStack Stein and newer, once the model has settled, these vGPUs can be listed via the OpenStack CLI:
openstack resource provider list
+--------------------------------------+-----------------------------------+------------+--------------------------------------+--------------------------------------+
| uuid | name | generation | root_provider_uuid | parent_provider_uuid |
+--------------------------------------+-----------------------------------+------------+--------------------------------------+--------------------------------------+
| 0883c2b5-bad2-4abc-a179-e33344361475 | node-sparky.maas | 2 | 0883c2b5-bad2-4abc-a179-e33344361475 | None |
| 4b0dbc58-0c85-4a80-8dd6-d43d1bd6ec53 | node-sparky.maas_pci_0000_c1_00_0 | 1 | 0883c2b5-bad2-4abc-a179-e33344361475 | 0883c2b5-bad2-4abc-a179-e33344361475 |
+--------------------------------------+-----------------------------------+------------+--------------------------------------+--------------------------------------+
openstack resource provider inventory list 4b0dbc58-0c85-4a80-8dd6-d43d1bd6ec53
+----------------+------------------+----------+----------+----------+-----------+-------+------+
| resource_class | allocation_ratio | min_unit | max_unit | reserved | step_size | total | used |
+----------------+------------------+----------+----------+----------+-----------+-------+------+
| VGPU | 1.0 | 1 | 2 | 0 | 1 | 2 | 0 |
+----------------+------------------+----------+----------+----------+-----------+-------+------+
Nova flavor definition
In order to expose a vGPU of the type defined earlier to any guest created with
the m1.small
flavor, create a new trait and assign it to the flavor:
openstack --os-placement-api-version 1.6 trait create CUSTOM_NVIDIA_108
openstack --os-placement-api-version 1.6 resource provider trait set --trait CUSTOM_NVIDIA_108 4b0dbc58-0c85-4a80-8dd6-d43d1bd6ec53
openstack flavor set m1.small --property resources:VGPU=1 --property trait:CUSTOM_NVIDIA_108=required
Note
: on releases older than Stein, since there is only one vGPU type and it doesn't show up in the resource provider list, no trait can be created. The flavor can simply be modified with
openstack flavor set m1.small --property resources:VGPU=1
After creating an instance of this flavor, the resource provider inventory list will show one vGPU being used:
openstack server create --flavor m1.small ...
openstack resource provider inventory list 4b0dbc58-0c85-4a80-8dd6-d43d1bd6ec53
+----------------+------------------+----------+----------+----------+-----------+-------+------+
| resource_class | allocation_ratio | min_unit | max_unit | reserved | step_size | total | used |
+----------------+------------------+----------+----------+----------+-----------+-------+------+
| VGPU | 1.0 | 1 | 2 | 0 | 1 | 2 | 1 |
+----------------+------------------+----------+----------+----------+-----------+-------+------+
Bugs
Please report bugs on Launchpad.
For general questions please refer to the OpenStack Charm Guide.