llvm-project/polly
Mandeep Singh Grang 02e789c9bf [polly] Remove redundant return [NFC]
Reviewers: grosser, bollu

Reviewed By: grosser

Subscribers: nemanjai, kbarton, llvm-commits

Tags: #polly

Differential Revision: https://reviews.llvm.org/D39916

llvm-svn: 317922
2017-11-10 20:33:08 +00:00
..
cmake [CMake] FindJsoncpp.cmake: Use descriptive variable name for libjsoncpp.so path. 2017-07-18 10:10:02 +00:00
docs [Docs] Replace 0-byte incorrect GEMM_double image with the one from www/images 2017-09-28 15:31:24 +00:00
include/polly Update formatting to reflect change in clang-format. NFC. 2017-11-09 16:33:29 +00:00
lib [polly] Remove redundant return [NFC] 2017-11-10 20:33:08 +00:00
test [ZoneAlgo/ForwardOpTree] Normalize PHIs to their known incoming values. 2017-10-31 16:11:46 +00:00
tools [GPUJIT] Improved temporary file handling. 2017-09-19 10:41:29 +00:00
unittests [test] Add some test cases for computeArrayUnused. 2017-08-21 23:04:55 +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 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.