docs: resource pool fixes
Minor docs fixes
@@ -21,9 +21,9 @@ resource pool handles scheduling and instance provisioning
independently.
When you configure a cluster, you set which pool is the default for CPU
-tasks and which pool is the default for GPU tasks. CPU-only tasks such a
-Tensorboards will run on the default CPU pool unless you specify that it
-should run in a different pool when launching the task. Tasks which
+tasks and which pool is the default for GPU tasks. CPU-only tasks such
+as Tensorboards will run on the default CPU pool unless you specify that
+they should run in a different pool when launching the task. Tasks which
require a slot, such as experiments or GPU-notebooks, will use the
default GPU pool unless otherwise specified. For this reason we
recommend that you always create a cluster with at least two pools, one
@@ -78,7 +78,7 @@ resource pools:
You have one pool with less expensive GPUs that you use for initial
prototyping on small data sets and another pool that you use for
- training more mature models on large datasets,
+ training more mature models on large datasets.
*************
Limitations
@@ -91,9 +91,9 @@ will need to manually decide to shift an experiment from one pool to
another.
We do not currently allow a cluster to have resource pools in multiple
-AWS regions/GCP zones or across multiple cloud providers. If the master
-is running in one AWS region/GCP zone, all resource pools must also be
-in that AWS region/GCP zone.
+AWS/GCP regions or across multiple cloud providers. If the master is
+running in one AWS/GCP region, all resource pools must also be in that
+AWS/GCP region.
If you create a task that needs slots and specify a pool that will never
have slots (i.e. a pool with CPU-only instances), that task can never
