Cache partitioning is all about predictability, not performance. Your code may execute faster on average without cache partitioning, but it probably wouldn't be as predictable and could be quite sensitive to whatever executes in parallel.
Cache partitioning aims to remove all the sensitivity to other tasks sharing the caches, thus making your task more predictable – but potentially at the expense of overall performance. In critical systems, predictability is of far greater importance than performance.
Rapita’s solution for multicore timing analysis can be used to exercise cache partitioning mechanisms by analyzing any shared – and usually undocumented – structures internal to the caches.