forked from OSchip/llvm-project
349d1c3368
Summary: Both `canUseISLTripCount()` and `addOverApproximatedRegion()` contained checks to reject endless loops which are now removed and replaced by a single check in `isValidLoop()`. For reporting such loops the `ReportLoopOverlapWithNonAffineSubRegion` is renamed to `ReportLoopHasNoExit`. The test case `ReportLoopOverlapWithNonAffineSubRegion.ll` is adapted and renamed as well. The schedule generation in `buildSchedule()` is based on the following assumption: Given some block B that is contained in a loop L and a SESE region R, we assume that L is contained in R or the other way around. However, this assumption is broken in the presence of endless loops that are nested inside other loops. Therefore, in order to prevent erroneous behavior in `buildSchedule()`, r265280 introduced a corresponding check in `canUseISLTripCount()` to reject endless loops. Unfortunately, it was possible to bypass this check with -polly-allow-nonaffine-loops which was fixed by adding another check to reject endless loops in `allowOverApproximatedRegion()` in r273905. Hence there existed two separate locations that handled this case. Thank you Johannes Doerfert for helping to provide the above background information. Reviewers: Meinersbur, grosser Subscribers: _jdoerfert, pollydev Differential Revision: https://reviews.llvm.org/D24560 Contributed-by: Matthias Reisinger <d412vv1n@gmail.com> llvm-svn: 281987 |
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README
Polly - Polyhedral optimizations for LLVM ----------------------------------------- http://polly.llvm.org/ Polly uses a mathematical representation, the polyhedral model, to represent and transform loops and other control flow structures. Using an abstract representation it is possible to reason about transformations in a more general way and to use highly optimized linear programming libraries to figure out the optimal loop structure. These transformations can be used to do constant propagation through arrays, remove dead loop iterations, optimize loops for cache locality, optimize arrays, apply advanced automatic parallelization, drive vectorization, or they can be used to do software pipelining.