llvm-project/polly
Tobias Grosser 6bbca36414 Adjust to debug info metadata format change.
Rename variable to retainedNodes. This unbreaks the Polly builds.

llvm-svn: 331960
2018-05-10 07:09:10 +00:00
..
cmake [CMake] Use only keyword-version of target_link_library. NFC. 2018-01-12 16:09:18 +00:00
docs [doc] Overhaul doc on preparing IR for processing by Polly. 2018-04-06 19:24:18 +00:00
include/polly Revert "[polly] [ScopInfo] Don't pre-compute the name of the Scop's region." 2018-05-02 14:55:39 +00:00
lib [ScopInfo] Remove bail out condition in buildMinMaxAccess(). 2018-05-09 16:23:56 +00:00
test Adjust to debug info metadata format change. 2018-05-10 07:09:10 +00:00
tools [GPUJIT] Improved temporary file handling. 2017-09-19 10:41:29 +00:00
unittests Remove the last uses of isl::give and isl::take 2018-04-29 00:28:26 +00:00
utils Revise polly-{update|check}-format targets 2015-09-14 16:59:50 +00:00
www [Polly] Information about generalized matrix multiplication 2017-09-24 19:00:25 +00:00
.arcconfig [polly] Set up .arcconfig to point to new Diffusion PLO repository 2017-11-27 17:34:03 +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 [CMake] Use only keyword-version of target_link_library. NFC. 2018-01-12 16:09:18 +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.