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@@ -239,7 +239,10 @@ STARPU_REGRESSION_BASED, but costs a lot more to compute). For instance,
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model for the @code{memset} operation. Of course, the application has to issue
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tasks with varying size so that the regression can be computed. StarPU will not
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trust the regression unless there is at least 10% difference between the minimum
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-and maximum observed input size.
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+and maximum observed input size. For non-linear regression, since computing it
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+is quite expensive, it is only done at termination of the application. This
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+means that the first execution uses history-based performance model to perform
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+scheduling.
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@item
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Provided as an estimation from the application itself (@code{STARPU_COMMON} model type and @code{cost_model} field),
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