llvm-project

History

Hongbin Zheng 4ac4e15582 Refactor: Pass the argument 'IRBuilder' and 'AfterBlock' of function 'createLoop' by reference, so that we do not need to type an extra '&' operator when calling the function. llvm-svn: 155349		2012-04-23 13:03:56 +00:00
..
autoconf	configure: Add gmp_inc when checking for CLooG	2011-10-04 06:55:03 +00:00
cmake	Add initial version of Polly	2011-04-29 06:27:02 +00:00
docs	Add initial version of Polly	2011-04-29 06:27:02 +00:00
include	Refactor: Pass the argument 'IRBuilder' and 'AfterBlock' of function 'createLoop' by	2012-04-23 13:03:56 +00:00
lib	Refactor: Pass the argument 'IRBuilder' and 'AfterBlock' of function 'createLoop' by	2012-04-23 13:03:56 +00:00
test	ScheduleOpt: Fix crash with -enable-polly-vector	2012-04-16 11:06:06 +00:00
tools	Add initial version of Polly	2011-04-29 06:27:02 +00:00
utils	Update isl	2012-02-20 08:41:44 +00:00
www	www: Update matmul example slightly.	2012-04-17 21:38:20 +00:00
CMakeLists.txt	Out of tree build support: Set TARGET_TRIPLE from the result of "llvm-config --host-target"	2012-03-27 07:56:07 +00:00
CREDITS.txt	(Test commit for polly)	2011-07-16 13:30:03 +00:00
LICENSE.txt	Happy new year 2012!	2012-01-01 08:16:56 +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	Add initial version of Polly	2011-04-29 06:27:02 +00:00
Makefile.config.in	Buildsystem: Add -no-rtti	2011-06-30 19:50:04 +00:00
README	Remove some empty lines	2011-10-04 06:56:36 +00:00
configure	configure: Add gmp_inc when checking for CLooG	2011-10-04 06:55:03 +00:00

README

Polly - Polyhedral optimizations for LLVM

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.