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llvm-project/polly
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Tobias Grosser 60b54f19e6 Detect Parameters directly on the SCEV. 
Instead of using TempScop to find parameters, we detect them directly
on the SCEV. This allows us to remove the TempScop parameter detection
in a subsequent commit.

This fixes a bug reported by Marcello Maggioni <hayarms@gmail.com>

llvm-svn: 144087
 		2011-11-08 15:41:28 +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 Detect Parameters directly on the SCEV. 2011-11-08 15:41:28 +00:00
lib Detect Parameters directly on the SCEV. 2011-11-08 15:41:28 +00:00
test Detect Parameters directly on the SCEV. 2011-11-08 15:41:28 +00:00
tools Add initial version of Polly 2011-04-29 06:27:02 +00:00
utils Remove pollycc 2011-10-23 20:59:47 +00:00
www www: Change in cloog installation procedure 2011-10-26 12:25:49 +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.