.. geohpc documentation master file, created by
   sphinx-quickstart on Thu Nov 16 13:23:50 2023.
   You can adapt this file completely to your liking, but it should at least
   contain the root `toctree` directive.

.. figure:: _static/web-banner.png


The **Spatial Data Science with High Performance Computing (HPC)** web is a course 
designed for students, professionals, and especially personnel of higher-education 
institutions in Finland who are working with CSC's supercomputers and willing 
to use the computational resources in *Parallel* for *Spatial Data Science* processes 
with Python. 

The course is composed by a short **Introduction** to CSC's resources and followed by 
a **Getting started** section where you will find briefly how to set up a HPC environment 
for further processes. Then, short examples of how to use the **HPC storage** in case you 
want to use it straightforward. Finally, you will see separated **Lessons** with different 
*Spatial Data Processes* using HPC resources in Parallel showing how supercomputers can 
facilitate your work using the right Python programing tools.


Prerequirements
-----------------
The HPC Lessons requires previous knowledge in spatial algorithms (Spatial Analysis) 
and some programing skills. I a more specific specific way as next:

- Medium/Advanced Python programming skills
- Basic knowledge on Jupyter Lab
- Basic spatial algorithms knowledge
- Basic CSC's set up knowledge especifically for Puhti supercomputer (Optional)

The intructions about how to access and set up Puhti supercomputer are included so in case 
you haven't used it before you will be able to.

Course format
----------------
The course start with **Introduction** for theoretical overview of HPC resources and it continues 
with a **Getting started** section that will show you how to acess and create an online session 
in you browser for using the HPC computational resources for the Lessons. Then, it has a previous 
overview of how to manage Allas **HPC storage** in case you need for your projects (nice to have), 
and then the Lessons starts where you can see an overview on the web.

Running Lessons
------------------

Once you have cloned and installed the environment especified in the section 
**Installing customized HPC environment** you will be able to run the Lessons 
located under the folder:

.. code-block:: bash

    GeoHPC/source/lessons

Simply open every notebook and follow the instructions cell by cell.


Content
---------
Find a detailed structure of the website here.

.. toctree::
   :maxdepth: 1
   :caption: Course information

   course-info/introduction
   course-info/overview

.. toctree::
   :maxdepth: 2
   :caption: Getting started

   getting-started/activate-account
   getting-started/install-env
   getting-started/set-up-jupyter
   getting-started/desktop-connect

.. toctree::
   :maxdepth: 2
   :caption: HPC storage

   connect-hpc/allas-access

.. toctree::
   :maxdepth: 3
   :caption: Lesson 1

   lessons/L1/01_CellularTowers-Parallelization.ipynb

.. toctree::
   :maxdepth: 3
   :caption: Lesson 2

   lessons/L2/02_ShortestPath-Parallelization.ipynb

.. toctree::
   :maxdepth: 3
   :caption: Lesson 3 - SYKE

   lessons/L3/03_LandCoverClassification_syke_Parallelization.ipynb

.. toctree::
   :maxdepth: 3
   :caption: Lesson 4 - FGI

   lessons/L4/04_MergedTiledVectorData-Parallel.rst

.. toctree::
   :maxdepth: 3
   :caption: Lesson 5 - Overture Maps

   lessons/L5/05_OvertureMaps-POI-Parallelization.ipynb



.. .. toctree::
..    :maxdepth: 2
..    :caption: Long run development test

..    lessons/test/01_ShortestPath-LongRun-16cores.ipynb











..
   * :ref:`genindex`
   * :ref:`modindex`
   * :ref:`search`