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Summary: When checking the parallelism of a scheduling dimension, we first check if excluding reduction dependences the loop is parallel or not. If the loop is not parallel, then we need to return the minimal dependence distance of all data dependences, including the previously subtracted reduction dependences. Reviewers: grosser, Meinersbur, efriedma, eli.friedman, jdoerfert, bollu Reviewed By: Meinersbur Subscribers: llvm-commits, pollydev Tags: #polly Differential Revision: https://reviews.llvm.org/D45236 llvm-svn: 329214
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.