llvm-project/polly
Siddharth Bhat dd616e9519 [ScpInliner] Move DEBUG-TYPE to below all includes to prevent cross-module interaction. [NFC]
This fixes compile errors.

llvm-svn: 311130
2017-08-17 22:21:16 +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 [GPGPU] Only collect the access that belong to an array [NFC] 2017-08-17 22:04:53 +00:00
lib [ScpInliner] Move DEBUG-TYPE to below all includes to prevent cross-module interaction. [NFC] 2017-08-17 22:21:16 +00:00
test [ScopInliner] Add a simple Scop-based inliner to polly. 2017-08-17 21:57:23 +00:00
tools [Polly] [GPUJIT] Set min size to 1 on CUDA allocation calls. [NFC] 2017-08-15 18:21:38 +00:00
unittests Add forgotten CMakeLists.txt file in unit-test 2017-08-05 09:44:11 +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.