hanchenye-llvm-project/polly
Tobias Grosser 457eb579dd ScopInfo: No need to keep ReadOnlyAccesses in an additional map [NFC]
It seems over time we added an additional map that maps from the base address
of a read-only access to the actual access. However this map is never used.
Drop the creation and use of this map to simplify our alias check generation
code.

llvm-svn: 292126
2017-01-16 14:24:48 +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: Extract out splitAliasGroupsByDomain [NFC] 2017-01-16 14:08:00 +00:00
lib ScopInfo: No need to keep ReadOnlyAccesses in an additional map [NFC] 2017-01-16 14:24:48 +00:00
test Un-XFAIL test case after half support was added to PTX backend in r291956 2017-01-16 14:08:14 +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
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.