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@@ -1196,7 +1196,7 @@ input sizes, by applying a*n^b+c regression over observed execution times.
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@end itemize
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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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How to use schedulers which can benefit from such performance model is explained
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-in section @ref{Task scheduling policy}.
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+in @ref{Task scheduling policy}.
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The same can be done for task power consumption estimation, by setting the
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The same can be done for task power consumption estimation, by setting the
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@code{power_model} field the same way as the @code{model} field. Note: for
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@code{power_model} field the same way as the @code{model} field. Note: for
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@@ -1445,7 +1445,7 @@ priority information to StarPU.
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By default, StarPU uses the @code{eager} simple greedy scheduler. This is
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By default, StarPU uses the @code{eager} simple greedy scheduler. This is
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because it provides correct load balance even if the application codelets do not
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because it provides correct load balance even if the application codelets do not
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have performance models. If your application codelets have performance models
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have performance models. If your application codelets have performance models
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-(see section @ref{Performance model example} for examples showing how to do it),
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+(@pxref{Performance model example} for examples showing how to do it),
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you should change the scheduler thanks to the @code{STARPU_SCHED} environment
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you should change the scheduler thanks to the @code{STARPU_SCHED} environment
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variable. For instance @code{export STARPU_SCHED=dmda} . Use @code{help} to get
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variable. For instance @code{export STARPU_SCHED=dmda} . Use @code{help} to get
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the list of available schedulers.
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the list of available schedulers.
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