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docs/getting_started.rst

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Hello
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Getting Started
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===============
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Getting started
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---------------
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Start out by installing the package.
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The simplest way to do this is ``pip install autotuning_methodology``.
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Python 3.9 and up are supported.
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Hello world
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To get started, all you need is an experiments file.
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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.
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A simple example experiments file is as follows:
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.. literalinclude:: ../experiment_files/simple_example.json
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:language: JSON
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To use these experiment files, two entry points are defined: ``autotuning_experiment`` and ``autotuning_visualize``.
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Both entrypoints take one argument: the path to the experiments file.
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The first runs the experiment and saves the results, the second visualizes the results.
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``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).
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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.
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A note on file references:
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File references in experiments files are relative to the location of the experiment file itself.
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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.
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Plots outputted by this package are placed in a folder called `generated_plots` relative to the current working directory.

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