Create your first compute environment
Creating a volume​
cgc volume create <name> --size <size> -sc <storage_class>
-s
- size in GiB of your volume-sc
,--storage-class
- storage class of your volume
For the created volume to be accessible, it needs to be mounted to a resource.
Output
$ cgc volume create getting-started -s 10
Volume getting-started of size 10Gi GB on SSD created from imported module. Volume is ReadWriteMany.
List of existing volumes​
List all created volumes:
cgc volume list
example:
$ cgc volume list
name used size type disks type mounted to
--------------- ------ ------ ------------- ------------ ------------
getting-started 7.67M 10Gi ReadWriteMany SSD
Compute create​
To create your first compute resource, you need to specify the name and type of entity for the compute resource.
$ cgc compute create <entity> --name --gpu -gpu-type --cpu --memory --volume
where
entity
- i.e. tensorflow-jupyter | pytorch-jupyter-n, --name
- name of the compute resource-g, --gpu
- quantity of attached GPUs, max 8 per notebook-gt, --gpu-type
- type of attached GPU (A100 | V100 | A5000) default = A5000-c, --cpu
- cpu core count-m, --memory
- amount of attached RAM in GiB-v, --volume
- volume to mountname of volume
example:
$ cgc compute create -n getting-jupyter -c 2 -m 4 -g 1 -gt A100 -v getting-started tensorflow-jupyter
tensorflow-jupyter Pod getting-jupyter has been created! Mounted volumes: getting-started
Accessible at: https://getting-jupyter.namespace.cgc-waw-01.comtegra.cloud
Jupyter token: f660c69776c647eba6d895c312388a0c
Output provides an accessible URL and generated token. Token can be changed at first login.
List of existing compute resources​
If you want to see the list of your existing compute resources, you can use the list command.
$ cgc compute list
example:
$ cgc compute list
name type status volumes mounted CPU cores RAM GPU type GPU count URL
--------------- ------------------ -------- ----------------- ----------- ----- ---------- ----------- -----------------------------------------------------
getting-jupyter tensorflow-jupyter Running getting-started 2 4Gi V100 1 https://getting-jupyter.namespace.cgc-waw-01.comtegra.cloud
To see Jupyter token add
-d
flag for more details.