hanchenye-llvm-project/polly
Tobias Grosser 249c4b1ad5 ScheduleOptimizer: Use isl_map_from_union_map to extract map.
llvm-svn: 179268
2013-04-11 05:55:13 +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 Update formatting to latest version of clang-format 2013-04-10 06:55:45 +00:00
lib ScheduleOptimizer: Use isl_map_from_union_map to extract map. 2013-04-11 05:55:13 +00:00
test ScheduleOpt: Do not crash on statements with empty iteration domains 2013-04-10 22:48:08 +00:00
tools Update formatting to latest version of clang-format 2013-04-10 06:55:45 +00:00
utils check that clang-format exists 2013-02-15 21:26:50 +00:00
www www: Add kernelgen publications 2013-01-18 00:26:39 +00:00
CMakeLists.txt cmake: Do not clang-format check the externally imported json library 2013-03-23 01:04:48 +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.