Added getting started section

docs/getting_started.rst

@@ -1,6 +1,24 @@
-Hello
+Getting Started
+===============
 
-Getting started
----------------
+Start out by installing the package. 
+The simplest way to do this is ``pip install autotuning_methodology``. 
+Python 3.9 and up are supported. 
 
-Hello world
+To get started, all you need is an experiments file. 
+This is a `json` file that describes the details of your comparison: which algorithms to use, which programs to tune on which devices, the graphs to output and so on. 
+A simple example experiments file is as follows:
+
+.. literalinclude:: ../experiment_files/simple_example.json
+    :language: JSON
+
+To use these experiment files, two entry points are defined: ``autotuning_experiment`` and ``autotuning_visualize``. 
+Both entrypoints take one argument: the path to the experiments file. 
+The first runs the experiment and saves the results, the second visualizes the results. 
+``autotuning_experiment`` is intended for situations where you do not evaluate on the same machine as you visualize on (e.g. running on a cluster and visualizing on your laptop). 
+If the results do not yet exists, ``autotuning_visualize`` will automatically trigger ``autotuning_experiment``, so when running on the same machine, ``autotuning_visualize`` is all you need. 
+
+A note on file references:
+File references in experiments files are relative to the location of the experiment file itself. 
+File references in tuning scripts are relative to the location of the tuning script itself. Tuning scripts need to have the global literals `file_path_results` and `file_path_metadata` for this package to know where to get the results. 
+Plots outputted by this package are placed in a folder called `generated_plots` relative to the current working directory.