llvm-project/polly
Michael Kruse 8474470500 [DeLICM] Fix wrong comment. NFC.
Correct a comment that claimed that a store after load was detected
when the code checks a load after a store.

llvm-svn: 295835
2017-02-22 14:14:40 +00:00
..
cmake Remove -fvisibility=hidden and FORCE_STATIC. 2016-09-12 18:25:00 +00:00
docs Porting the example illustrating Polly from HTML to reStructuredText 2017-02-10 11:46:57 +00:00
include/polly [ScopInfo] Add statistics to count loops after scop modeling 2017-02-17 08:12:36 +00:00
lib [DeLICM] Fix wrong comment. NFC. 2017-02-22 14:14:40 +00:00
test [DeLICM] Map values hoisted by LICM back to the array. 2017-02-21 10:20:54 +00:00
tools GPURuntime: ensure compilation with C99 2016-09-11 07:32:50 +00:00
unittests [DeLICM] Add forgotten unittests in previous commit. NFC. 2017-02-15 17:19:22 +00:00
utils Revise polly-{update|check}-format targets 2015-09-14 16:59:50 +00:00
www Porting the example illustrating Polly from HTML to reStructuredText 2017-02-10 11:46:57 +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 [Cmake] Bump required cmake version to 3.4.3. 2017-02-20 17:06:31 +00:00
CREDITS.txt Add myself to the credits 2014-08-10 03:37:29 +00:00
LICENSE.txt [External] Move lib/JSON to lib/External/JSON. NFC. 2017-02-05 15:26:56 +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.