hanchenye-llvm-project

History

Michael Kruse c7e0d9c216 Fix non-synthesizable loop exit values. Polly recognizes affine loops that ScalarEvolution does not, in particular those with loop conditions that depend on hoisted invariant loads. Check for SCEVAddRec dependencies on such loops and do not consider their exit values as synthesizable because SCEVExpander would generate them as expressions that depend on the original induction variables. These are not available in generated code. llvm-svn: 262404		2016-03-01 21:44:06 +00:00
..
cmake	Compile ISL into its own library	2015-09-24 11:30:22 +00:00
docs	Support accesses with differently sized types to the same array	2016-02-04 13:18:42 +00:00
include/polly	Fix non-synthesizable loop exit values.	2016-03-01 21:44:06 +00:00
lib	Fix non-synthesizable loop exit values.	2016-03-01 21:44:06 +00:00
test	Fix non-synthesizable loop exit values.	2016-03-01 21:44:06 +00:00
tools	Remove autotools build system	2016-01-28 12:00:33 +00:00
utils	Revise polly-{update\|check}-format targets	2015-09-14 16:59:50 +00:00
www	www: Fix typo	2016-02-25 15:21:02 +00:00
.arcconfig	Adjusted arc linter config for modern version of arcanist	2015-08-12 09:01:16 +00:00
.arclint	Adjusted arc linter config for modern version of arcanist	2015-08-12 09:01:16 +00:00
.gitattributes	…
.gitignore	Add git patch files to .gitignore	2015-06-23 20:55:01 +00:00
CMakeLists.txt	Add basic doxygen infrastructure for Polly	2016-02-04 07:16:36 +00:00
CREDITS.txt	…
LICENSE.txt	…
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.