hanchenye-llvm-project/polly
Tobias Grosser c00bd98695 Update to a newer CLooG version
This update fixes the test cases to give correct results with the isl version
we are currently using.

llvm-svn: 184064
2013-06-16 19:55:07 +00:00
..
autoconf 'chmod -x' on files that do not need the executable bits 2012-12-29 15:09:03 +00:00
cmake autoconf/cmake: Always require isl code generation. 2012-10-21 21:48:21 +00:00
docs
include Fix typo in header guards 2013-06-15 18:52:49 +00:00
lib scop detection: inline and remove isValidBasicBlock 2013-06-14 20:20:43 +00:00
test Correctly convert APInt to gmp values 2013-06-14 16:23:38 +00:00
tools Reformat with clang-format 2013-05-07 07:30:56 +00:00
utils Update to a newer CLooG version 2013-06-16 19:55:07 +00:00
www Remove .htaccess file 2013-05-21 11:58:47 +00:00
CMakeLists.txt cmake: Add target to reformat with clang-format 2013-05-07 07:30:31 +00:00
CREDITS.txt (Test commit for polly) 2011-07-16 13:30:03 +00:00
LICENSE.txt Update the copyright coredits -- Happy new year 2013! 2013-01-01 10:00:19 +00:00
Makefile Revert "Fix a bug introduced by r153739: We are not able to provide the correct" 2012-04-11 07:43:13 +00:00
Makefile.common.in 'chmod -x' on files that do not need the executable bits 2012-12-29 15:09:03 +00:00
Makefile.config.in 'chmod -x' on files that do not need the executable bits 2012-12-29 15:09:03 +00:00
README Trivial change to the README, mainly to test commit access. 2012-10-09 04:59:42 +00:00
configure do not require cloog from configure 2012-11-26 23:03:41 +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.