Apply suggestions from code review

Co-authored-by: Wanchao <wanchaol@users.noreply.github.com>

Author: wz337

recipes_source/distributed_device_mesh.rst

@@ -30,10 +30,10 @@ Users can also easily manage the underlying process_groups/devices for multi-dim
 
 Why DeviceMesh is Useful
 ------------------------
-DeviceMesh is useful, when composability is requried. That is when your parallelism solutions require both communication across hosts and within each host.
+DeviceMesh is useful when working with multi-dimensional parallelism (i.e. 3-D parallel) where parallelism composability is requried. For example, when your parallelism solutions require both communication across hosts and within each host.
 The image above shows that we can create a 2D mesh that connects the devices within each host, and connects each device with its counterpart on the other hosts in a homogenous setup.
 
-Without DeviceMesh, users would need to manually set up NCCL communicators before applying any parallelism.
+Without DeviceMesh, users would need to manually set up NCCL communicators, cuda devices on each process before applying any parallelism, which could be quite complicated
 The following code snippet illustrates a hybrid sharding 2-D Parallel pattern setup without :class:`DeviceMesh`.
 First, we need to manually calculate the shard group and replicate group. Then, we need to assign the correct shard and
 replicate group to each rank.
@@ -108,7 +108,7 @@ How to use DeviceMesh with HSDP
 
 Hybrid Sharding Data Parallel(HSDP) is 2D strategy to perform FSDP within a host and DDP across hosts.
 
-Let's see an example of how DeviceMesh can assist with applying HSDP to your model. With DeviceMesh,
+Let's see an example of how DeviceMesh can assist with applying HSDP to your model with a simple setup. With DeviceMesh,
 users would not need to manually create and manage shard group and replicate group.
 
 .. code-block:: python

recipes_source/recipes_index.rst

@@ -326,7 +326,7 @@ Recipes are bite-sized, actionable examples of how to use specific PyTorch featu
 
    .. customcarditem::
    :header: Getting Started with DeviceMesh
-   :card_description: Learn how to use DeviceMesh
+   :card_description: Learn how to use DeviceMesh to manage process groups easily for multi-dimensional parallelism
    :image: ../_static/img/thumbnails/cropped/profiler.png
    :link: ../recipes/distributed_device_mesh.html
    :tags: Distributed-Training