llvm-project/polly
Michael Kruse c0a19b079d Reapply "Add update_test.py script."
Originally committed in r261899 and reverted in r262202 due to failing
in out-of-LLVM tree builds.

Replace the use of LLVM_TOOLS_BINARY_DIR by LLVM_TOOLS_DIR which exists
in both, in-tree and out-of-tree builds.

Original commit message:
The script updates a lit test case that uses FileCheck using the actual
output of the 'RUN:'-lines program. Useful when updating test cases due
to expected output changes and diff'ing expected and actual output.

llvm-svn: 262227
2016-02-29 14:58:13 +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 LoopGenerators: Expose some parts of the parallel loop generator 2016-02-27 06:24:58 +00:00
lib ScopInfo: Remove indentation in hoistInvariantLoads 2016-02-29 07:29:42 +00:00
test Reapply "Add update_test.py script." 2016-02-29 14:58:13 +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 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 Add basic doxygen infrastructure for Polly 2016-02-04 07:16:36 +00:00
CREDITS.txt Add myself to the credits 2014-08-10 03:37:29 +00:00
LICENSE.txt Update the copyright credits -- Happy new year 2014! 2014-01-01 08:27:31 +00:00
README Trivial change to the README, mainly to test commit access. 2012-10-09 04:59:42 +00:00

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.