dask dashboard

examples/Dask/README.md

@@ -9,3 +9,62 @@ client
 Make sure to check the ip-address of your Compute vm, you can find it at the comm field in the Scheduler box:
 ![Scheduler address](scheduler_address.png)
 
+To add workers: you can use a simple Slurm job script:
+```
+#!/bin/bash
+
+conda init
+source activate base
+pip install dask==2023.2.0 distributed==2023.2.0 
+export PATH=$PATH:/home/azureuser/.local/bin
+dask worker tcp://10.0.1.5:12345
+```
+
+Make sure to check the scheduler address on the last line, that takes care of connecting back to the Dask controller you started in the first step.
+Submit the script through the terminal with the following command, in this case to add 5 worker vm's:
+```
+sbatch -p f4s --array 1-4 ./dask.job
+```
+
+Now it is a good time to add some small functions to be used for calculations:
+```
+import time
+import random
+
+def inc(x):
+    time.sleep(random.random())
+    return x + 1
+
+def double(x):
+    time.sleep(random.random())
+    return 2 * x
+
+def add(x, y):
+    time.sleep(random.random())
+    return x + y
+```
+
+and to create an empty array for the results:
+```
+zs = []
+``` 
+
+To start the actual work, this is a small loop that uses the functions to manipulate the input and adds all of them in the output array:
+```
+%%time
+
+for i in range(1024):
+    x = client.submit(inc, i)     # x = inc(i)
+    y = client.submit(double, x)  # y = inc(x)
+    z = client.submit(add, x, y)  # z = inc(y)
+    zs.append(z)
+```
+
+In the Dask dashboard, for which the link you can find through Compute -> Applications (you may have to press the 3 dots to expand), 
+you should now be able to see the tasks being executed:
+![Dask Dashboard](dask_dashboard.png)
+
+Once you are done, shutdown the dask controller and all of it's workers. This will finalize the jobs and shut down the worker vm's as well:
+```
+client.shutdown()
+```