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llvm-project/polly
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Tobias Grosser f56af204b9 Add delinearization testcase for ivs that do not follow the loop order 
This is a test case that is currently failing, but that should start working
with an upcoming version of our delinearization pass.

llvm-svn: 207678
 		2014-04-30 17:49:22 +00:00
..
autoconf Remove OpenScop 2014-04-11 09:47:45 +00:00
cmake Remove OpenScop 2014-04-11 09:47:45 +00:00
docs
…
include [Modules] Fix potential ODR violations by sinking the DEBUG_TYPE 2014-04-22 03:30:19 +00:00
lib Add missing include. 2014-04-30 07:26:28 +00:00
test Add delinearization testcase for ivs that do not follow the loop order 2014-04-30 17:49:22 +00:00
tools Update the copyright credits -- Happy new year 2014! 2014-01-01 08:27:31 +00:00
utils Update isl to fix memory bugs 2014-04-13 16:37:18 +00:00
www www: Reference phone call notes 2014-04-23 18:09:24 +00:00
.gitattributes gitattributes: .png and .txt are no text files 2013-07-28 09:05:20 +00:00
CMakeLists.txt Remove OpenScop 2014-04-11 09:47:45 +00:00
CREDITS.txt (Test commit for polly) 2011-07-16 13:30:03 +00:00
LICENSE.txt Update the copyright credits -- Happy new year 2014! 2014-01-01 08:27:31 +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 Remove OpenScop 2014-04-11 09:47:45 +00:00
README Trivial change to the README, mainly to test commit access. 2012-10-09 04:59:42 +00:00
configure Remove OpenScop 2014-04-11 09:47:45 +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.