llvm-project/polly
Tobias Grosser eec7f6daa1 Add test showing the update of access functions with in-scop defined base ptrs
This feature is currently not supported and an explicit assert to prevent the
introduction of such accesses has been added in r282893. This test case allows
to reproduce the assert (and without the assert the miscompile) added in
r282893. It will help when adding such support at some point.

llvm-svn: 292147
2017-01-16 17:51:28 +00:00
..
cmake Remove -fvisibility=hidden and FORCE_STATIC. 2016-09-12 18:25:00 +00:00
docs Clear the release notes for 5.0.0 2017-01-12 22:47:01 +00:00
include/polly ScopInfo: split out construction of a single alias group [NFC] 2017-01-16 15:49:07 +00:00
lib ScopInfo: document base pointers in alias-checks must be invariant [NFC] 2017-01-16 15:49:14 +00:00
test Add test showing the update of access functions with in-scop defined base ptrs 2017-01-16 17:51:28 +00:00
tools GPURuntime: ensure compilation with C99 2016-09-11 07:32:50 +00:00
unittests Adjust formatting to commit r292110 [NFC] 2017-01-16 14:08:10 +00:00
utils Revise polly-{update|check}-format targets 2015-09-14 16:59:50 +00:00
www www: Add dates RSS news 2017-01-08 09:28:10 +00:00
.arcconfig Upgrade all the .arcconfigs to https. 2016-07-14 13:15:37 +00:00
.arclint Adjusted arc linter config for modern version of arcanist 2015-08-12 09:01:16 +00:00
.gitattributes
.gitignore Do not track the isl PDF manual in SVN 2017-01-16 11:48:03 +00:00
CMakeLists.txt Teach Polly's standalone build to work now that we include the gmock 2017-01-11 01:07:37 +00:00
CREDITS.txt Add myself to the credits 2014-08-10 03:37:29 +00:00
LICENSE.txt Update copyright year to 2016. 2016-03-30 22:41:38 +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.