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If a region does not have more than one loop, we do not identify it as a Scop in ScopDetection. The main optimizations Polly is currently performing (tiling, preparation for outer-loop vectorization and loop fusion) are unlikely to have a positive impact on individual loops. In some cases, Polly's run-time alias checks or conditional hoisting may still have a positive impact, but those are mostly enabling transformations which LLVM already performs for individual loops. As we do not focus on individual loops, we leave them untouched to not introduce compile time regressions and execution time noise. This results in good compile time reduction (oourafft: -73.99%, smg2000: -56.25%). Contributed-by: Pratik Bhatu <cs12b1010@iith.ac.in> Reviewers: grosser Differential Revision: http://reviews.llvm.org/D12268 llvm-svn: 246161 |
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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.