Selecting GPU Types¶
Coiled supports running computations with GPU-enabled machines in all the supported cloud providers, please refer to the GPUs documentation for more information.
In both AWS and Azure, the GPU selection is tied to the instance type
that you request. For example, in AWS if you select the instance type
g4dn.xlarge, this instance type contains an Nvidia Tesla T4 GPU.
The cloud provider that works a bit differently is the Google Cloud
Platform (GCP). In GCP, you can attach different GPUs to
The rest of the article will assume that you are using the GCP cloud provider for your account.
You can select the GPU type by using the
gpu_type keyword argument in
coiled.Cluster() constructor. For example:
import coiled cluster = coiled.Cluster(gpu_type="nvidia-tesla-t4")
Note that if you specify a
gpu_type you don’t need to pass the
worker_gpu keyword argument.
You can also specify both GPU and instance types. For example, if you wish to use a high memory instance.
import coiled cluster = coiled.Cluster(gpu_type="nvidia-tesla-t4", worker_vm_types=["n1-highmem-2"])
GPU types allowed¶
Currently we allow only the
nvidia-testla-t4 GPU, but you will be able to
choose from a wider range of GPU types in the future. You can see a list of
allowed GPU types with the command
import coiled coiled.list_gpu_types()