llvm-project/polly
Tobias Grosser 4e8d1475bd ScopInfo: use correct enum type in type definition
Instead of a plain 'int' we use the correct enum type. This does not give
us type safety yet, but at least makes the code more correct in terms of typing.
To avoid such mismatches it might sense to switch these enums to C++11 typed
enums.

llvm-svn: 291960
2017-01-13 21:46:48 +00:00
..
cmake Remove -fvisibility=hidden and FORCE_STATIC. 2016-09-12 18:25:00 +00:00
docs Clear the release notes for 5.0.0 2017-01-12 22:47:01 +00:00
include/polly ScopInfo: use correct enum type in type definition 2017-01-13 21:46:48 +00:00
lib Update to recent clang-format changes 2017-01-12 21:05:19 +00:00
test Update tests to more precise analysis results in LLVM core 2017-01-11 22:53:34 +00:00
tools GPURuntime: ensure compilation with C99 2016-09-11 07:32:50 +00:00
unittests Teach Polly's unittest macro to link LLVMDemangle which LLVMSupport now 2017-01-11 01:07:35 +00:00
utils Revise polly-{update|check}-format targets 2015-09-14 16:59:50 +00:00
www www: Add dates RSS news 2017-01-08 09:28:10 +00:00
.arcconfig Upgrade all the .arcconfigs to https. 2016-07-14 13:15:37 +00:00
.arclint Adjusted arc linter config for modern version of arcanist 2015-08-12 09:01:16 +00:00
.gitattributes
.gitignore Add git patch files to .gitignore 2015-06-23 20:55:01 +00:00
CMakeLists.txt Teach Polly's standalone build to work now that we include the gmock 2017-01-11 01:07:37 +00:00
CREDITS.txt Add myself to the credits 2014-08-10 03:37:29 +00:00
LICENSE.txt Update copyright year to 2016. 2016-03-30 22:41:38 +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.