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llvm-capstone/polly
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Tobias Grosser 8c4cfc327b CodeGeneration: Do not delete the old version of the Scop. 
Instead of deleting the old code, keep it on the side in an if-branch. It will
either be deleted by the dead code elimination or we can use it as fallback.

llvm-svn: 131352
2011-05-14 19:01:49 +00:00
..
autoconf Add initial version of Polly 2011-04-29 06:27:02 +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 CodeGeneration: Do not delete the old version of the Scop. 2011-05-14 19:01:49 +00:00
lib CodeGeneration: Do not delete the old version of the Scop. 2011-05-14 19:01:49 +00:00
test CodeGeneration: Do not delete the old version of the Scop. 2011-05-14 19:01:49 +00:00
tools Add initial version of Polly 2011-04-29 06:27:02 +00:00
utils Add a converter from jscop to iscc input 2011-04-29 06:29:20 +00:00
www www: Update status of our move to the LLVM infrastructure 2011-05-13 20:51:45 +00:00
CMakeLists.txt Add initial version of Polly 2011-04-29 06:27:02 +00:00
configure Add initial version of Polly 2011-04-29 06:27:02 +00:00
CREDITS.txt Add e-mail to credits file. 2011-04-29 07:54:20 +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 Add initial version of Polly 2011-04-29 06:27:02 +00:00
README Add initial version of Polly 2011-04-29 06:27:02 +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.