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llvm-project/polly
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Tobias Grosser 325812ac6d Simplify: Adopt for translation of MemoryAccess::getAccessRelation 
For some reason this one was missed earlier.

llvm-svn: 308845
 		2017-07-23 08:15:28 +00:00
..
cmake [CMake] FindJsoncpp.cmake: Use descriptive variable name for libjsoncpp.so path. 2017-07-18 10:10:02 +00:00
docs [docs] Minor formatting fixes. 2017-07-19 18:18:37 +00:00
include/polly Move MemoryAccess::get*ArrayId to isl++ 2017-07-23 04:08:59 +00:00
lib Simplify: Adopt for translation of MemoryAccess::getAccessRelation 2017-07-23 08:15:28 +00:00
test [Simplify] Remove partial write accesses with empty domain. 2017-07-22 20:33:09 +00:00
tools [Polly][GPGPU] Added SPIR Code Generation and Corresponding Runtime Support for Intel 2017-07-21 16:11:06 +00:00
unittests Update Polly to reflect a change to a clang-format patch. I'm not sure 2017-06-29 23:58:03 +00:00
utils Revise polly-{update|check}-format targets 2015-09-14 16:59:50 +00:00
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 Add myself to the credits 2014-08-10 03:37:29 +00:00
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.