llvm-project/polly
Tobias Grosser 71036882d2 cmake: Install all polly include files
Contributed-by: Richard Membarth <richard.membarth@informatik.uni-erlangen.de>
llvm-svn: 172903
2013-01-19 14:17:52 +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 Add missing __isl_give 2013-01-18 00:09:42 +00:00
lib clang-format goodness 2013-01-14 22:40:23 +00:00
test isl: vector code generation based on ISL ast 2012-12-18 07:46:13 +00:00
tools Update the copyright coredits -- Happy new year 2013! 2013-01-01 10:00:19 +00:00
utils User isl sha commit id instead of the git tag 2012-12-04 21:54:37 +00:00
www www: Add kernelgen publications 2013-01-18 00:26:39 +00:00
CMakeLists.txt cmake: Install all polly include files 2013-01-19 14:17:52 +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.