hanchenye-llvm-project/polly
Sanjoy Das b641a90529 Adapt to llvm change r296992 to unbreak the bots
r296992 made ScalarEvolution's CompareValueComplexity less aggressive,
and that broke the polly test being fixed in this change.  This change
explicitly bumps CompareValueComplexity in said test case to make it
pass.

Can someone from the polly team please can give me an idea on if this
case is important enough to have
scalar-evolution-max-value-compare-depth be 3 by default?

llvm-svn: 296994
2017-03-06 01:12:16 +00:00
..
cmake [Cmake] Optionally use a system isl version. 2017-02-27 17:54:25 +00:00
docs Porting the example illustrating Polly from HTML to reStructuredText 2017-02-10 11:46:57 +00:00
include/polly Fix namespaces after clang-format update 2017-03-01 15:54:27 +00:00
lib [ScopDetection] Do not allow required-invariant loads in non-affine region 2017-03-02 12:15:37 +00:00
test Adapt to llvm change r296992 to unbreak the bots 2017-03-06 01:12:16 +00:00
tools
unittests [Support] Remove NonowningIslPtr. NFC. 2017-02-23 17:57:27 +00:00
utils
www Porting the example illustrating Polly from HTML to reStructuredText 2017-02-10 11:46:57 +00:00
.arcconfig
.arclint [External] Move lib/JSON to lib/External/JSON. NFC. 2017-02-05 15:26:56 +00:00
.gitattributes
.gitignore Do not track the isl PDF manual in SVN 2017-01-16 11:48:03 +00:00
CMakeLists.txt [Cmake] Optionally use a system isl version. 2017-02-27 17:54:25 +00:00
CREDITS.txt
LICENSE.txt [External] Move lib/JSON to lib/External/JSON. NFC. 2017-02-05 15:26:56 +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.