llvm-project/polly
Tobias Grosser d614b3e6bd Preserve the isl-noexceptions.h C++ bindings when updating isl
The bindings currently need to be generated manually, as they are not yet
part of the official isl distribution. Hence, we keep them across updates
assuming they only need to be updated when new functions or functionality
should be exposed.

llvm-svn: 297710
2017-03-14 07:46:28 +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 [Simplify] Add -polly-simplify pass. 2017-03-10 16:05:24 +00:00
lib Preserve the isl-noexceptions.h C++ bindings when updating isl 2017-03-14 07:46:28 +00:00
test [ScheduleOptimizer] Allow tiling after fusion 2017-03-12 19:02:31 +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

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.