llvm-capstone/polly
Siddharth Bhat 4fe11cf95f [DependenceInfo] Remove idempotent union: must-writes with may-writes [NFC]
Since may-writes are always a superset of the must-writes, there is no
point in taking a union of one with the other.

llvm-svn: 298085
2017-03-17 13:26:10 +00:00
..
cmake [Cmake] Generate a PollyConfig.cmake. 2017-03-09 17:58:20 +00:00
docs Porting the example illustrating Polly from HTML to reStructuredText 2017-02-10 11:46:57 +00:00
include/polly [PruneUnprofitable] Add -polly-prune-unprofitable pass. 2017-03-17 13:09:52 +00:00
lib [DependenceInfo] Remove idempotent union: must-writes with may-writes [NFC] 2017-03-17 13:26:10 +00:00
test [PruneUnprofitable] Add -polly-prune-unprofitable pass. 2017-03-17 13:09:52 +00:00
tools GPURuntime: ensure compilation with C99 2016-09-11 07:32:50 +00:00
unittests [unittest] Do not convert large unsigned long to isl::val 2017-03-10 22:25:39 +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] Generate a PollyConfig.cmake. 2017-03-09 17:58:20 +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

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.