llvm-project/polly
Eli Friedman f26bdb539e Make Value::getPointerAlignment() return an Align, not a MaybeAlign.
If we don't know anything about the alignment of a pointer, Align(1) is
still correct: all pointers are at least 1-byte aligned.

Included in this patch is a bugfix for an issue discovered during this
cleanup: pointers with "dereferenceable" attributes/metadata were
assumed to be aligned according to the type of the pointer.  This
wasn't intentional, as far as I can tell, so Loads.cpp was fixed to
stop making this assumption. Frontends may need to be updated.  I
updated clang's handling of C++ references, and added a release note for
this.

Differential Revision: https://reviews.llvm.org/D80072
2020-05-20 16:37:20 -07:00
..
cmake [cmake] Use source-groups in Polly. 2020-01-07 14:20:06 -06:00
docs [Polly] Add -polly-isl-arg command line option. 2020-04-06 08:56:57 -05:00
include/polly [polly][opaque pointers] Remove use of deprecated APIs. 2020-04-03 18:00:33 -07:00
lib [Polly] Update ScalarEvolutionExpander.h include. 2020-05-20 12:21:32 +01:00
test Make Value::getPointerAlignment() return an Align, not a MaybeAlign. 2020-05-20 16:37:20 -07:00
tools Fix typos throughout the license files that somehow I and my reviewers 2019-01-21 09:52:34 +00:00
unittests Make Polly tests dependencies explicit 2020-05-04 08:06:39 +02:00
utils [arc] Remove unittesting from arcconfig 2018-05-15 13:43:42 +00:00
www [NFC] correct "thier" to "their" 2020-04-15 14:38:52 -07:00
.arclint
.gitattributes
.gitignore
CMakeLists.txt [JSONExporter] Replace bundled Jsoncpp with llvm/Support/JSON.h. NFC. 2018-08-01 00:15:16 +00:00
CREDITS.txt
LICENSE.txt Fix typos throughout the license files that somehow I and my reviewers 2019-01-21 09:52:34 +00:00
README Test commit 2017-06-28 12:58:44 +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.