925ce50f1b
The remaining parts produced by the full partial tile isolation can contain hot spots that are worth to be optimized. Currently, we rely on the simple loop unrolling pass, LiCM and the SLP vectorizer to optimize such parts. However, the approach can suffer from the lack of the information about aliasing that Polly provides using additional alias metadata or/and the lack of the information required by simple loop unrolling pass. This patch is the first step to optimize the remaining parts. To do it, we unroll and separate them. In case of, for instance, Intel Kaby Lake, it helps to increase the performance of the generated code from 39.87 GFlop/s to 49.23 GFlop/s. The next possible step is to avoid unrolling performed by Polly in case of isolated and remaining parts and rely only on simple loop unrolling pass and the Loop vectorizer. Reviewed-by: Tobias Grosser <tobias@grosser.es> Differential Revision: https://reviews.llvm.org/D37692 llvm-svn: 312929 |
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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.