AI Training - Capabilities and Limitations

Last updated 20th April, 2021.

Capabilities and known limits

Jobs resources and limitations

• No duration limitation on job execution
• No limitation on number of parallel execution

You can either choose the number of GPU or CPU for a job, not both. By default, a job uses one GPU. The memory resource is not customisable.

If you chose the number of GPU:

• CPU, memory and local storage resources are not customisable but scaled linearly with each additional GPU.

If you chose the number of CPU:

• Memory and local storage resource is not customisable but scaled linearly with each additional CPU.

Information about maximum number of CPU/GPU, memory per CPU/GPU and local storage are available with the ovhai CLI.

ovhai capabilities flavor list

Available ports to public network

Each job has a public URL, by default this URL accesses the port 8080 of the job. The default port can be configured when you submit a new job.

You can also access other ports by appending them to the URL.

Job URL for accessing the default port (starting with the job's ID):

• https://00000000-0000-0000-0000-000000000000.job.gra.training.ai.cloud.ovh.net

Job URL for accessing the port 9000 (starting with the job's ID followed by the port number):

• https://00000000-0000-0000-0000-000000000000-9000.job.gra.training.ai.cloud.ovh.net

Only the HTTP layer is accessible.

OVHcloud vRack

• AI Training cannot use or access OVHcloud vRack.

Available hardware for jobs

• Nvidia V100S pricing available here

Available regions for jobs

• GRA (Gravelines in France)
• BHS (Beauharnois in Canada)

Available storage for data volumes

• Public Cloud Object Storage (Any Region)

Feedback

Please send us your questions, feedback and suggestions to improve the service:

• On the OVHcloud Discord server

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