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Michael Kruse 06ed529205 Add more statistics. 
Add statistics about
- Which optimizations are applied
- Number of loops in Scops at various stages
- Number of scalar/singleton writes at various stages representative
  for scalar false dependencies
- Number of parallel loops

These will be useful to find regressions due to moving Polly further
down of LLVM's pass pipeline.

Differential Revision: https://reviews.llvm.org/D37049

llvm-svn: 311553
 		2017-08-23 13:50:30 +00:00
..
cmake [CMake] FindJsoncpp.cmake: Use descriptive variable name for libjsoncpp.so path. 2017-07-18 10:10:02 +00:00
docs Tiny docs fix 2017-07-27 18:14:00 +00:00
include/polly Add more statistics. 2017-08-23 13:50:30 +00:00
lib Add more statistics. 2017-08-23 13:50:30 +00:00
test [ScopDetect] Include zero-iteration loops in loop count. 2017-08-23 13:29:59 +00:00
tools [GPUJIT] Make max managed pointers an environment variable. 2017-08-22 17:32:27 +00:00
unittests [test] Add some test cases for computeArrayUnused. 2017-08-21 23:04:55 +00:00
utils
…
www [WWW] Add a section to Getting Started about building out-of-tree 2017-07-11 20:37:28 +00:00
.arcconfig Upgrade all the .arcconfigs to https. 2016-07-14 13:15:37 +00:00
.arclint [External] Move lib/JSON to lib/External/JSON. NFC. 2017-02-05 15:26:56 +00:00
.gitattributes
…
.gitignore Do not track the isl PDF manual in SVN 2017-01-16 11:48:03 +00:00
CMakeLists.txt [Polly][CMake] Skip unit-tests in lit if gtest is not available 2017-07-11 11:37:35 +00:00
CREDITS.txt
…
LICENSE.txt [External] Move lib/JSON to lib/External/JSON. NFC. 2017-02-05 15:26:56 +00:00
README Test commit 2017-06-28 12:58:44 +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.