hanchenye-llvm-project/polly
Michael Kruse 426e6f71f8 [ScopInfo] Fix: use raw source pointer.
When adding an llvm.memcpy instruction to AliasSetTracker, it uses the raw
source and target pointers which preserve bitcasts.
MemAccInst::getPointerOperand() also returns the raw target pointers, but
Scop::buildAliasGroups() did not for the source pointer. This lead to mismatches
between AliasSetTracker and ScopInfo on which pointer to use.

Fixed by also using raw pointers in Scop::buildAliasGroups().

llvm-svn: 285071
2016-10-25 13:37:43 +00:00
..
cmake Remove -fvisibility=hidden and FORCE_STATIC. 2016-09-12 18:25:00 +00:00
docs docs: Remove reference to PoCC 2016-05-17 19:44:16 +00:00
include/polly [polly] Change SmallPtrSet which is being iterated to SmallSetVector in ScopInfo.h 2016-10-21 21:00:11 +00:00
lib [ScopInfo] Fix: use raw source pointer. 2016-10-25 13:37:43 +00:00
test [ScopInfo] Fix: use raw source pointer. 2016-10-25 13:37:43 +00:00
tools GPURuntime: ensure compilation with C99 2016-09-11 07:32:50 +00:00
unittests Add -polly-flatten-schedule pass. 2016-09-08 15:02:36 +00:00
utils Revise polly-{update|check}-format targets 2015-09-14 16:59:50 +00:00
www www: Add Loopy publication 2016-09-29 18:17:30 +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
CMakeLists.txt Query llvm-config to get system libs required for linking. 2016-08-25 14:58:29 +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.