llvm-project/polly
Roman Gareev b196055c0c Check reduction dependencies in case of the matrix multiplication optimization
To determine parameters of the matrix multiplication, we check RAW dependencies
that can be expressed using only reduction dependencies. Consequently, we
should check the reduction dependencies, if this is the case.

Reviewed-by: Tobias Grosser <tobias@grosser.es>,
             Sven Verdoolaege <skimo-polly@kotnet.org>
             Michael Kruse <llvm@meinersbur.de>

Differential Revision: https://reviews.llvm.org/D29814

llvm-svn: 294836
2017-02-11 09:59:09 +00:00
..
cmake
docs Porting the example illustrating Polly from HTML to reStructuredText 2017-02-10 11:46:57 +00:00
include/polly [ScopInfo] Use ScopArrayInfo instead of base address 2017-02-09 23:12:22 +00:00
lib Check reduction dependencies in case of the matrix multiplication optimization 2017-02-11 09:59:09 +00:00
test Check reduction dependencies in case of the matrix multiplication optimization 2017-02-11 09:59:09 +00:00
tools
unittests [Support] Add convertZoneToTimepoints. NFC. 2017-02-04 15:42:17 +00:00
utils
www Porting the example illustrating Polly from HTML to reStructuredText 2017-02-10 11:46:57 +00:00
.arcconfig
.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 [External] Move lib/JSON to lib/External/JSON. NFC. 2017-02-05 15:26:56 +00:00
CREDITS.txt
LICENSE.txt [External] Move lib/JSON to lib/External/JSON. NFC. 2017-02-05 15:26:56 +00:00
README

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.