llvm-project/polly
Michael Kruse 3b425ff232 Allow overflow of indices with constant dim-sizes.
Allow overflow of indices into the next higher dimension if it has
constant size. E.g.

    float A[32][2];
    ((float*)A)[5];

is effectively the same as

    A[2][1];

This can happen since r265379 as a side effect if ScopDetection
recognizes an access as affine, but ScopInfo rejects the GetElementPtr.

Differential Revision: http://reviews.llvm.org/D18878

llvm-svn: 265942
2016-04-11 14:34:08 +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 Allow overflow of indices with constant dim-sizes. 2016-04-11 14:34:08 +00:00
lib Allow overflow of indices with constant dim-sizes. 2016-04-11 14:34:08 +00:00
test Allow overflow of indices with constant dim-sizes. 2016-04-11 14:34:08 +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 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.