Are there any cases in which anything more than a linear speed increase comes from parallelising an algorithm ?
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The maximum you can reach from a theory viewpoint is linear speedup.
In practice, it is possible super linear speedup. If you can distribute your problem in a away that you can leverage effects of processor caches, e.g. because it does not fit in the cache of a single core, your problem can scale better than linear.