llvm-project/polly
Johannes Doerfert e6e3c9246a Check late for profitability
Before this patch we only expanded valid __and__ profitable region. Therefor
  we did not allow the expansion to create a profitable region from a
  non-profitable one.  With this patch we will remember and expand all valid
  regions and check for profitability only at the end.

  This patch increases the number of valid SCoPs in the LLVM-TS and SPEC
  2000/2006 by 28% (from 303 to 390), including the hot loop in hmmer.

llvm-svn: 269343
2016-05-12 20:21:50 +00:00
..
cmake Fix: Always honor LLVM_LIBDIR_SUFFIX. 2016-04-09 14:09:08 +00:00
docs doc: A source code with Polly does not use a separate module (by default) 2016-04-29 12:35:46 +00:00
include/polly Cleanup rejection log handling [NFC] 2016-05-12 18:50:01 +00:00
lib Check late for profitability 2016-05-12 20:21:50 +00:00
test Cleanup rejection log handling [NFC] 2016-05-12 18:50:01 +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] Mark task as done and me as owner of some task 2016-05-02 11:21:30 +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.