Selecting Instance Types#
An instance is a server hosted by a cloud provider and instance types
(or machine types) are defined by combinations of CPU, memory, storage, and networking capacity
(see GCP supported instance types and AWS supported instance types for more details).
When creating a cluster, Coiled will find all available instance types with the
requirements that you specify for CPU, memory, and GPU.
To allow for more fine-grain control of the type of cluster you create, you can
provide a list of instance types for the scheduler and workers
worker_vm_types keyword arguments.
import coiled cluster = coiled.Cluster( scheduler_vm_types=["t3.large", "t3.xlarge"], worker_vm_types=["m5n.large", "m5zn.large"], )
It’s recommended you specify more than one instance type in your list to avoid instance availability issues in the cloud provider and region that you are using Coiled.
If you provide a list of specific instance types, Coiled will prioritize them in order of decreasing priority. If you instead specify the number of CPUs or memory, compatible instance types are prioritized in order of lowest to highest estimated cost.
Allowable Instance Types#
You can use
coiled.list_instance_types() to see a list of all
allowed instance types for your configured cloud provider. For example:
import coiled coiled.list_instance_types()
For more details on supported instance types see
You can specify a single keyword argument or a combination (e.g.
gpus) to filter the results.
import coiled # Filter instances that have 4 cores only coiled.list_instance_types(cores=4) # Filter instances by cores and memory coiled.list_instance_types(cores=2, memory="8 Gib")
You can also provide
list_instance_types with a range of values, for example:
import coiled coiled.list_instance_types(cores=[2, 8])
You might be also interested in the tutorial on Selecting GPU Types.