llvm-project/polly
Michael Kruse e448364320 [SCEVAffinator] Fix assertion checking for constant divisor.
An assertion in visitSDivInstruction() checked whether the divisor is constant
by checking whether the argument is a ConstantInt. However, SCEVValidator allows
the divisor to be simplified to a constant by ScalarEvolution.

We synchronize the implementation of SCEVValidator and SCEVAffinator to both
accept simplified SCEV expressions.

llvm-svn: 275174
2016-07-12 15:08:47 +00:00
..
cmake Respect LLVM_INSTALL_TOOLCHAIN_ONLY. 2016-06-21 18:14:01 +00:00
docs docs: Remove reference to PoCC 2016-05-17 19:44:16 +00:00
include/polly Fix gcc compile failure 2016-07-11 12:27:04 +00:00
lib [SCEVAffinator] Fix assertion checking for constant divisor. 2016-07-12 15:08:47 +00:00
test [SCEVAffinator] Fix assertion checking for constant divisor. 2016-07-12 15:08:47 +00:00
tools GPURuntime: Only print status in debug mode 2016-07-06 03:04:53 +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: do not check-format anything in lib/External 2016-07-05 15:26:33 +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.