llvm-project/polly
Michael Kruse 5f58aae8f3 [Polly][CodeGen] Allow nesting of BandAttr mark without loop.
BandAttr markers are added as parents of schedule tree bands. These also
appear as markers its equivalent AST, but a band does not necessarily
corresponds to a loop in this. Iterations may be peeled or the loop
being unrolled (e.g. if it has just one iteration). In such cases it may
happend that there is not loop between a BandAttr marker and the marker
for a loop nested in the former parent band/loop.

Handle the situation by giving priority to the inner marker over the
outer.

Fixes the polly-x86_64-linux-test-suite buildbot.
2021-03-16 16:17:07 -05:00
..
cmake [Windows][Polly] Disable LLVMPolly module for all compilers on Windows 2020-09-15 09:12:38 +03:00
docs Bump the trunk major version to 13 2021-01-26 19:37:55 -08:00
include/polly [Polly][Optimizer] Apply user-directed unrolling. 2021-03-15 13:05:39 -05:00
lib [Polly][CodeGen] Allow nesting of BandAttr mark without loop. 2021-03-16 16:17:07 -05:00
test [Polly][Unroll] Fix unroll_double test. 2021-03-16 09:00:42 -05:00
tools Fix typos throughout the license files that somehow I and my reviewers 2019-01-21 09:52:34 +00:00
unittests [Polly] Regenerate isl-noexceptions.h. 2021-02-14 19:17:54 -06:00
utils Harmonize Python shebang 2020-07-16 21:53:45 +02:00
www [Branch-Rename] Fix some links 2021-02-01 16:43:21 +05:30
.arclint
.gitattributes
.gitignore
CMakeLists.txt Remove .svn from exclude list as we moved to git 2020-10-21 16:09:21 +02:00
CREDITS.txt
LICENSE.TXT Rename top-level LICENSE.txt files to LICENSE.TXT 2021-03-10 21:26:24 -08:00
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.