llvm-project/polly
Johannes Doerfert d5c369f460 Do not check all GEPs for assumptions
Before, we checked all GEPs in a statement in order to derive
  out-of-bound assumptions. However, this can not only introduce new
  parameters but it is also not clear what we can learn from GEPs that
  are not immediately used in a memory accesses inside the SCoP. As this
  case is very rare, no actual change in the behaviour is expected.

llvm-svn: 267442
2016-04-25 18:55:15 +00:00
..
cmake Fix: Always honor LLVM_LIBDIR_SUFFIX. 2016-04-09 14:09:08 +00:00
docs docs: Fix section header committed in r264575 2016-03-28 17:00:14 +00:00
include/polly Do not check all GEPs for assumptions 2016-04-25 18:55:15 +00:00
lib Do not check all GEPs for assumptions 2016-04-25 18:55:15 +00:00
test Do not check all GEPs for assumptions 2016-04-25 18:55:15 +00:00
tools Update copyright year to 2016. 2016-03-30 22:41:38 +00:00
utils Revise polly-{update|check}-format targets 2015-09-14 16:59:50 +00:00
www [WWW] Update passes 2016-04-05 16:15:44 +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 gitattributes: .png and .txt are no text files 2013-07-28 09:05:20 +00:00
.gitignore Add git patch files to .gitignore 2015-06-23 20:55:01 +00:00
CMakeLists.txt cmake: Ensure tools/* is still formatted 2016-03-25 12:16:17 +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.