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llvm-capstone/polly
History
Philip Pfaffe e12d036d13 [WWW] Add a section to Getting Started about building out-of-tree 
llvm-svn: 307704
2017-07-11 20:37:28 +00:00
..
cmake [Polly][CMake] Use the CMake Package instead of llvm-config in out-of-tree builds 2017-07-11 11:24:25 +00:00
docs [doc] Add Davide's links regarding automated bisecting 2017-06-17 08:44:12 +00:00
include/polly Always export the latest memory access relations 2017-07-11 10:10:13 +00:00
lib [Simplify] Also remove redundant writes which originally came from PHI nodes 2017-07-11 14:29:39 +00:00
test [Simplify] Also remove redundant writes which originally came from PHI nodes 2017-07-11 14:29:39 +00:00
tools [CMake] Retire Polly's FindCUDA.cmake in favour of CMake's default FindCUDA.cmake script. 2017-06-06 19:20:48 +00:00
unittests Update Polly to reflect a change to a clang-format patch. I'm not sure 2017-06-29 23:58:03 +00:00
utils
www [WWW] Add a section to Getting Started about building out-of-tree 2017-07-11 20:37:28 +00:00
.arcconfig Upgrade all the .arcconfigs to https. 2016-07-14 13:15:37 +00:00
.arclint [External] Move lib/JSON to lib/External/JSON. NFC. 2017-02-05 15:26:56 +00:00
.gitattributes
.gitignore Do not track the isl PDF manual in SVN 2017-01-16 11:48:03 +00:00
CMakeLists.txt [Polly][CMake] Skip unit-tests in lit if gtest is not available 2017-07-11 11:37:35 +00:00
CREDITS.txt
LICENSE.txt [External] Move lib/JSON to lib/External/JSON. NFC. 2017-02-05 15:26:56 +00:00
README Test commit 2017-06-28 12:58:44 +00:00

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.