AI Training - Capacités et limites (EN)
Découvrez toutes les capacités et limites d'AI Training
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
Local storage refers to a drive mounted on the node. It's limited and not the recommended way to handle data, see OVHcloud documentation on data
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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