llvm-project/polly
Michael Kruse bfb8fa5a16 Update format after clang-format change. NFC.
In r319314 clang-format changed its reflowing logic.

llvm-svn: 319426
2017-11-30 12:05:48 +00:00
..
cmake [CMake] FindJsoncpp.cmake: Use descriptive variable name for libjsoncpp.so path. 2017-07-18 10:10:02 +00:00
docs [Docs] Replace 0-byte incorrect GEMM_double image with the one from www/images 2017-09-28 15:31:24 +00:00
include/polly Port ScopInfo to the isl cpp bindings 2017-11-19 22:13:34 +00:00
lib Update format after clang-format change. NFC. 2017-11-30 12:05:48 +00:00
test [CodeGen] Detect empty domain because of parameters context. 2017-11-21 22:11:10 +00:00
tools [GPUJIT] Improved temporary file handling. 2017-09-19 10:41:29 +00:00
unittests [test] Add some test cases for computeArrayUnused. 2017-08-21 23:04:55 +00:00
utils Revise polly-{update|check}-format targets 2015-09-14 16:59:50 +00:00
www [Polly] Information about generalized matrix multiplication 2017-09-24 19:00:25 +00:00
.arcconfig [polly] Set up .arcconfig to point to new Diffusion PLO repository 2017-11-27 17:34:03 +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.