explaining the structure of the lessons

Author: psteinb

_episodes/02-00-environment-modules.md

@@ -1,5 +1,5 @@
 ---
-title: "Changing the Environment"
+title: "Recap: Changing the Environment"
 teaching: 20
 exercises: 10
 questions:

_extras/guide.md

@@ -7,23 +7,34 @@ title: "Instructor Notes"
 
 This document tries to describe what preparations are required of instructors to make the workshop work as smooth as possible. In order to build the materials for the workshop at your site, consult the `_config.yaml` file before you generate the site with `make site`. It contains the 'environment variables' that are specific to your workshop, such as the name of the login node, the root folder of the shared file system etc.
 
-## Chapter 1
+## Rational
 
-### Section 1, Taking the space shuttle
+The lineup of lessons is meant to be as flexible as possible. Skip lessons if needed.
 
-At some point a folder named `this_weeks_canteen_menus` will be needed under `/tmp/this_weeks_canteen_menus` on the login node. Make sure before the lesson, that this folder is present. [/home/rob/this_weeks_canteen_menus](filesystem/home/rob/this_weeks_canteen_menus) of this material contains synthesized pdfs of a computerized canteen if you wish. You can use either these or prepare the menu of the canteen as single pdf files per day you'll go for the workshop into in this folder.
+### Recap: Changing the Environment
 
-### Section 2, Navigating Files and Directories
+We start with environment variables as a recap and to get all learners on board. Feel free to skip this if you know from the pre-workshop survey that your learners are capable of this.
 
-Make sure that for this lesson, that the contents of [filesystem](../filesystem) folder are available somewhere for the learners to download and unpack.
+### Estimation of Pi for Pedestrians
 
-## Chapter 2
+This lessons introduces the computational working hourse for all of this material. We use this way to calculate pi as it is compute intensive and typically doesn't need any I/O. As it is compute intensive it renders itself as a good example to illustrate data parallelism. Other types of parallism (task parallelism, latency hiding, ...) are exluded from the material on purpose in order to keep the cognitive load on the learners low.
 
-None so far.
+In addition, this lesson does nothing more than profile the code to find hot spots with respect to performance, i.e. runtime.
 
-## Chapter 3
+### Parallel Estimation of Pi for Pedestrians
+
+This lesson uses `multiprocessing` to parallelise the code in a shared memory environment.
+
+### Higher levels of parallelism
+
+This lesson introduces dask as a representative candidatae for cloud-native parallelisation approaches. This offers multiple things to the learners which often induce trouble in understanding.
+
+It shows that there are libraries out there that perform parallization automatically. It also tries to demo the infrastructure required for this, i.e. setting up a server process that dispatches work to worker processes etc.
+
+### Searching for Pi
+
+This introduces concepts from high throughput computing by illustrating map-reduce style searches through files.
 
-### Section 4, Searching for Pi
 
 Use the file [generate_scrambled_data.py](./code/03_parallel_jobs/generate_scrambled_data.py) to produce 16 files that comply to the files used in this section, e.g. : 
 
@@ -44,3 +55,9 @@ $ for i in `seq -f "%02.0f" 1 16`;do python3 ./generate_scrambled_data.py pi_est
 At best, create directories for the each learner so that they don't get into each other's way.
 
 Note, that this lesson is currently quite fragile as the i/o caching can easily get into the way of the learners. 
+
+
+### Bonus session: Distributing computations among computers
+
+A guided tour through a mpi program with all it's nuances and brain quirks in program flow.
+