forked from OSchip/llvm-project
469bdefd44
This installs the new developer policy and moves all of the license files across all LLVM projects in the monorepo to the new license structure. The remaining projects will be moved independently. Note that I've left odd formatting and other idiosyncracies of the legacy license structure text alone to make the diff easier to read. Critically, note that we do not in any case *remove* the old license notice or terms, as that remains necessary until we finish the relicensing process. I've updated a few license files that refer to the LLVM license to instead simply refer generically to whatever license the LLVM project is under, basically trying to minimize confusion. This is really the culmination of so many people. Chris led the community discussions, drafted the policy update and organized the multi-year string of meeting between lawyers across the community to figure out the strategy. Numerous lawyers at companies in the community spent their time figuring out initial answers, and then the Foundation's lawyer Heather Meeker has done *so* much to help refine and get us ready here. I could keep going on, but I just want to make sure everyone realizes what a huge community effort this has been from the begining. Differential Revision: https://reviews.llvm.org/D56897 llvm-svn: 351631 |
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| cmake | ||
| docs | ||
| include/polly | ||
| lib | ||
| test | ||
| tools | ||
| unittests | ||
| utils | ||
| www | ||
| .arcconfig | ||
| .arclint | ||
| .gitattributes | ||
| .gitignore | ||
| CMakeLists.txt | ||
| CREDITS.txt | ||
| LICENSE.txt | ||
| README | ||
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.