hanchenye-llvm-project/polly
Tobias Grosser cf7f6db300 cmake: Add option POLLY_USE_CLOOG
This allows to build Polly without CLooG.

llvm-svn: 195344
2013-11-21 11:48:07 +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 IslCodegen: Support for run-time conditions 2013-11-17 03:18:25 +00:00
lib Fix 80 column violation 2013-11-17 03:18:32 +00:00
test IslCodegen: Support for run-time conditions 2013-11-17 03:18:25 +00:00
tools Reformat with clang-format 2013-05-07 07:30:56 +00:00
utils Move to CLooG 0.18.1 and isl 0.12.1 2013-10-11 07:38:50 +00:00
www Fix a typo in my family name. Tobias: ;) 2013-10-29 11:05:18 +00:00
.gitattributes gitattributes: .png and .txt are no text files 2013-07-28 09:05:20 +00:00
CMakeLists.txt cmake: Add option POLLY_USE_CLOOG 2013-11-21 11:48:07 +00:00
CREDITS.txt
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.