hanchenye-llvm-project/polly
Johannes Doerfert 99f6630c82 [Refactor] Remove unecessary check and function
+ Perform the parallelism check on the innermost loop only once.
  + Inline the markOpenmpParallel function.
  + Rename all IslAstUserPayload * into Payload to make it consistent.

llvm-svn: 214448
2014-07-31 21:34:32 +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 [Refactor] Remove unecessary check and function 2014-07-31 21:34:32 +00:00
lib [Refactor] Remove unecessary check and function 2014-07-31 21:34:32 +00:00
test [Refactor] Use nicer print callback function in IslAst 2014-07-31 21:33:49 +00:00
tools Update the copyright credits -- Happy new year 2014! 2014-01-01 08:27:31 +00:00
utils Update to isl-0.13.0 2014-07-15 11:25:32 +00:00
www www: Fix grammar. 2014-06-10 20:18:16 +00:00
.gitattributes gitattributes: .png and .txt are no text files 2013-07-28 09:05:20 +00:00
CMakeLists.txt Reorder cmake include folders (polly source first) 2014-05-28 16:54:42 +00:00
CREDITS.txt Add "Yabin Hu" to CREDITS.txt 2014-06-21 18:35:33 +00:00
LICENSE.txt Update the copyright credits -- Happy new year 2014! 2014-01-01 08:27:31 +00:00
Makefile
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
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.