KMeans Readme Update for node and mode (oneapi-src#525)

* KMeans Readme Update for node and mode

* KMeans Readme Update for node and mode

Author: bdmoore1

AI-and-Analytics/Features-and-Functionality/IntelPython_daal4py_DistributedKMeans/README.md

@@ -24,6 +24,9 @@ Code samples are licensed under the MIT license. See
 
 Third party program Licenses can be found here: [third-party-programs.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/third-party-programs.txt)
 
+## Running Samples on the Intel® DevCloud
+If you are running this sample on the DevCloud, see [Running Samples on the Intel® DevCloud](#run-samples-on-devcloud)
+
 ## Building daal4py for CPU
 
 oneAPI Data Analytics Library is ready for use once you finish the Intel® oneAPI AI Analytics Toolkit installation and have run the post installation script.
@@ -72,7 +75,7 @@ Launch Jupyter Notebook in the directory housing the code example
 jupyter notebook
 ```
 
-### Running the Sample as a Python File
+### Running the Sample as a Python File<a name="running-the-sample"></a>
 
 When using daal4py for distributed memory systems, the command needed to execute the program should be executed in a bash shell. To execute this example, run the following command, where the number **4** is chosen as an example and means that it will run on **4 processes**:
 
@@ -84,6 +87,29 @@ The output of the script will be saved in the included models and result directo
 
 _Note: This code samples focus on using daal4py to do distributed ML computations on chunks of data. The `mpirun` command above will only run on a single local node. To launch on a cluster, you will need to create a host file on the master node, among other steps. The **TensorFlow_Multinode_Training_with_Horovod** code sample explains this process well._
 
+## Running Samples on the Intel&reg; DevCloud (Optional)<a name="run-samples-on-devcloud"></a>
+
+<!---Include the next paragraph ONLY if the sample runs in batch mode-->
+### Run in Batch Mode
+This sample runs in batch mode, so you must have a script for batch processing. Once you have a script set up, refer to [Running the Sample](#running-the-sample).
+
+<!---Include the next paragraph ONLY if the sample DOES NOT RUN in batch mode-->
+### Run in Interactive Mode
+This sample runs in interactive mode. For more information, see [Run as Juypter Notebook](#run-as-jupyter-notebook).
+
+### Request a Compute Node
+In order to run on the DevCloud, you need to request a compute node using node properties such as: `gpu`, `xeon`, `fpga_compile`, `fpga_runtime` and others. For more information about the node properties, execute the `pbsnodes` command.
+ This node information must be provided when submitting a job to run your sample in batch mode using the qsub command. When you see the qsub command in the Run section of the [Hello World instructions](https://devcloud.intel.com/oneapi/get_started/aiAnalyticsToolkitSamples/), change the command to fit the node you are using. Nodes which are in bold indicate they are compatible with this sample:
+
+<!---Mark each compatible Node in BOLD-->
+| Node              | Command                                                 |
+| ----------------- | ------------------------------------------------------- |
+| GPU               | qsub -l nodes=1:gpu:ppn=2 -d . hello-world.sh           |
+| __CPU__           | __qsub -l nodes=1:xeon:ppn=2 -d . hello-world.sh__      |
+| FPGA Compile Time | qsub -l nodes=1:fpga\_compile:ppn=2 -d . hello-world.sh |
+| FPGA Runtime      | qsub -l nodes=1:fpga\_runtime:ppn=2 -d . hello-world.sh |
+
+
 ##### Expected Printed Output (with similar numbers, printed 4 times):
 ```