Accuracy tuning

[stijnh]

This draft PR will integrate the ability to tune the arguments of kernels for different floating-point precision.

It is a draft for now. Let's see what the CI has to say.

[sonarqubecloud]

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0.0% Duplication

[sonarqubecloud]

Kudos, SonarCloud Quality Gate passed!   

0 Bugs
0 Vulnerabilities
0 Security Hotspots
20 Code Smells

No Coverage information
0.0% Duplication

[stijnh]

This PR is ready to be merged! @benvanwerkhoven @fjwillemsen

In short, this PR adds the following:

• A new type of observer called OutputObserver that is called with the output of the kernel once for each configuration.
• A subclass of this observer called AccuracyObserver that can calculate an error on the output.
• Built-in support for 10 types of error metrics (see error_metric_from_name).
• A new data structure called Tunable that can be passed to a kernel to make one of its arguments tunable.
• A subclass of this data structure called TunablePrecision that can be used to tune the precision of a kernel argument.
• Changes in how metrics are calculated. Previously, cached entries were directly added to the results. Now, cached entries have their metrics recomputed in every run.
• Adds an example of how to do accuracy tuning for CUDA.