hanchenye-llvm-project/polly
Michael Kruse 26212da555 [ScopBuilder] Move buildInvariantEquivalenceClasses function from ScopInfo. NFC.
Refactor Scop and ScopBuilder class. Move
buildInvariantEquivalenceClasses function from Scop class to ScopBuilder
class.

Patch by: Dominik Adamski <adamski.dominik@gmail.com>

Differential Revision: https://reviews.llvm.org/D62351

llvm-svn: 361902
2019-05-28 23:47:55 +00:00
..
cmake [CMake] Fix generation of exported targets in build directory 2018-11-06 15:18:17 +00:00
docs [CodeGen] LLVM OpenMP Backend. 2019-03-19 03:18:21 +00:00
include/polly [ScopBuilder] Move buildInvariantEquivalenceClasses function from ScopInfo. NFC. 2019-05-28 23:47:55 +00:00
lib [ScopBuilder] Move buildInvariantEquivalenceClasses function from ScopInfo. NFC. 2019-05-28 23:47:55 +00:00
test [DeLICM] Use polly::singleton to allow empty result. 2019-05-21 19:18:26 +00:00
tools Fix typos throughout the license files that somehow I and my reviewers 2019-01-21 09:52:34 +00:00
unittests Update the file headers across all of the LLVM projects in the monorepo 2019-01-19 08:50:56 +00:00
utils [arc] Remove unittesting from arcconfig 2018-05-15 13:43:42 +00:00
www Adjust documentation for git migration. 2019-01-29 16:37:27 +00:00
.arcconfig [arc] Remove unittesting from arcconfig 2018-05-15 13:43:42 +00:00
.arclint
.gitattributes
.gitignore
CMakeLists.txt [JSONExporter] Replace bundled Jsoncpp with llvm/Support/JSON.h. NFC. 2018-08-01 00:15:16 +00:00
CREDITS.txt
LICENSE.txt Fix typos throughout the license files that somehow I and my reviewers 2019-01-21 09:52:34 +00:00
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.