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llvm-project/polly
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Tobias Grosser 5d45381294 ScopInfo: Only give away a copy of the access relation. 
Also take the chance and rename access functions to access relations. This is
because we do not only allow plain functions to describe an access, but we
can have any access relation that can be described with linear constraints.

llvm-svn: 141257
 		2011-10-06 00:04:11 +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 ScopInfo: Only give away a copy of the access relation. 2011-10-06 00:04:11 +00:00
lib ScopInfo: Only give away a copy of the access relation. 2011-10-06 00:04:11 +00:00
test ScopInfo: Use separate function to build context 2011-10-06 00:03:48 +00:00
tools Add initial version of Polly 2011-04-29 06:27:02 +00:00
utils Adapt to introduction of isl_space 2011-10-06 00:03:35 +00:00
www Adapt to introduction of isl_space 2011-10-06 00:03:35 +00:00
CMakeLists.txt Buildsystem: Add -no-rtti 2011-06-30 19:50:04 +00:00
CREDITS.txt (Test commit for polly) 2011-07-16 13:30:03 +00:00
LICENSE.txt Add initial version of Polly 2011-04-29 06:27:02 +00:00
Makefile Add initial version of Polly 2011-04-29 06:27:02 +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.