forked from OSchip/llvm-project
883f8c1d2f
This will allow to generate non-wrap assumptions for integer expressions that are part of the SCoP. We compare the common isl representation of the expression with one computed with modulo semantic. For all parameter combinations they are not equal we can have integer overflows. The nsw flags are respected when the modulo representation is computed, nuw and nw flags are ignored for now. In order to not increase compile time to much, the non-wrap assumptions are collected in a separate boundary context instead of the assumed context. This helps compile time as the boundary context can become complex and it is therefor not advised to use it in other operations except runtime check generation. However, the assumed context is e.g., used to tighten dependences. While the boundary context might help to tighten the assumed context it is doubtful that it will help in practice (it does not effect lnt much) as the boundary (or no-wrap assumptions) only restrict the very end of the possible value range of parameters. PET uses a different approach to compute the no-wrap context, though lnt runs have shown that this version performs slightly better for us. llvm-svn: 247732 |
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| tools | ||
| utils | ||
| www | ||
| .arcconfig | ||
| .arclint | ||
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| CMakeLists.txt | ||
| CREDITS.txt | ||
| LICENSE.txt | ||
| Makefile | ||
| Makefile.common.in | ||
| Makefile.config.in | ||
| README | ||
| configure | ||
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.