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llvm-project/polly
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Sebastian Pop 784c012982 scop detection: remove an iteration over all uses 
reenabled reverted patch after checking that it passes without regressions on
the nightly test-suite.  Added testcase from Tobi.

llvm-svn: 185720
 		2013-07-05 20:24:47 +00:00
..
autoconf [autoconf/cmake] Make sure we detect the latest version of isl. 2013-07-02 14:11:32 +00:00
cmake [autoconf/cmake] Make sure we detect the latest version of isl. 2013-07-02 14:11:32 +00:00
docs
…
include clang-format latest changes 2013-07-02 16:13:07 +00:00
lib scop detection: remove an iteration over all uses 2013-07-05 20:24:47 +00:00
test scop detection: remove an iteration over all uses 2013-07-05 20:24:47 +00:00
tools Reformat with clang-format 2013-05-07 07:30:56 +00:00
utils Update CLooG such that the isl test cases are really up to date 2013-06-24 07:38:29 +00:00
www Remove .htaccess file 2013-05-21 11:58:47 +00:00
.gitattributes Add the git attributes file. 2013-06-29 07:21:57 +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 [autoconf/cmake] Make sure we detect the latest version of isl. 2013-07-02 14:11:32 +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.