Regions

Google Cloud uses regions, subdivided into zones, to define the geographic location of physical computing resources. When you run a job on AI Platform Training, you specify the region that you want it to run in.

You should typically use the region closest to your physical location or the physical location of your intended users, but note the available regions for each service as listed below.

Available regions

AI Platform Training is available in the following regions:

Americas

  • Oregon (us-west1)
  • Los Angeles (us-west2)
  • Salt Lake City (us-west3)
  • Iowa (us-central1)
  • South Carolina (us-east1)
  • N. Virginia (us-east4)

Europe

  • London (europe-west2)
  • Belgium (europe-west1)
  • Netherlands (europe-west4)
  • Zurich (europe-west6)
  • Frankfurt (europe-west3)
  • Finland (europe-north1)

Asia Pacific

  • Mumbai (asia-south1)
  • Singapore (asia-southeast1)
  • Hong Kong (asia-east2)
  • Taiwan (asia-east1)
  • Tokyo (asia-northeast1)
  • Osaka (asia-northeast2)
  • Seoul (asia-northeast3)

Google Cloud also provides additional regions for products other than AI Platform Training.

Region considerations

Training with accelerators

Accelerators are available on a region basis. Below is a table that lists all the available accelerators for each region:

Americas

Region Oregon
us-west1
Los Angeles
us-west2
Salt Lake City
us-west3
Iowa
us-central1
South Carolina
us-east1
N. Virginia
us-east4
NVIDIA Tesla K80
NVIDIA Tesla P4
NVIDIA Tesla P100
NVIDIA Tesla T4
NVIDIA Tesla V100
TPU v2
TPU v3 (Beta)

Europe

Region London
europe-west2
Belgium
europe-west1
Netherlands
europe-west4
Zurich
europe-west6
Frankfurt
europe-west3
NVIDIA Tesla K80
NVIDIA Tesla P4
NVIDIA Tesla P100
NVIDIA Tesla T4
NVIDIA Tesla V100
TPU v2
TPU v3 (Beta)

Asia Pacific

Region Mumbai
asia-south1
Singapore
asia-southeast1
Hong Kong
asia-east2
Taiwan
asia-east1
Tokyo
asia-northeast1
Osaka
asia-northeast2
Seoul
asia-northeast3
NVIDIA Tesla K80
NVIDIA Tesla P4
NVIDIA Tesla P100
NVIDIA Tesla T4
NVIDIA Tesla V100
TPU v2
TPU v3 (Beta)

If your training job uses multiple types of GPUs, they must all be available in a single zone in your region. For example, you cannot run a job in us-central1 with a master worker using NVIDIA Tesla T4 GPUs, parameter servers using NVIDIA Tesla K80 GPUs, and workers using NVIDIA Tesla P100 GPUs. While all of these GPUs are available for training jobs in us-central1, no single zone in that region provides all three types of GPU. To learn more about the zone availability of GPUs, see the comparison of GPUs for compute workloads.

Insufficient resources

Demand is high for GPUs and for compute resources in the us-central1 region. You may get an error message in your job logs that says: Resources are insufficient in region: <region>. Please try a different region..

To resolve this, try using a different region or try again later.

Cloud Storage

  • You should run your AI Platform Training job in the same region as the Cloud Storage bucket that you're using to read and write data for the job.

  • You should use the Standard Storage class for any Cloud Storage buckets that you're using to read and write data for your AI Platform Training job.