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@@ -1208,6 +1208,13 @@ starpu_codelet cl = @{
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Measured at runtime and refined by regression (STARPU_REGRESSION_BASED model
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type). This still assumes performance regularity, but can work with various data
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input sizes, by applying a*n^b+c regression over observed execution times.
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+
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+@item
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+Provided explicitly by the application (STARPU_PER_ARCH model type): the
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+@code{.per_arch[i].cost_model} fields have to be filled with pointers to
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+functions which return the expected duration of the task in micro-seconds, one
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+per architecture.
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+
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@end itemize
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How to use schedulers which can benefit from such performance model is explained
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