llvm-project/polly
Michael Kruse bd93df937a [Polly] Mark classes as final by default. NFC.
This make is obivious that a class was not intended to be derived from.

NPM analysis pass can unfortunately not marked as final because they are
derived from a llvm::Checker<T> template internally by the NPM.

Also normalize the use of classes/structs
 * NPM passes are structs
 * Legacy passes are classes
 * structs that have methods and are not a visitor pattern are classes
 * structs have public inheritance by default, remove "public" keyword
 * Use typedef'ed type instead of inline forward declaration
2022-05-17 12:05:39 -05:00
..
cmake [polly][cmake] Use `GNUInstallDirs` to support custom installation dirs 2022-01-18 20:33:42 +00:00
docs Bump the trunk major version to 15 2022-02-01 23:54:52 -08:00
include/polly [Polly] Mark classes as final by default. NFC. 2022-05-17 12:05:39 -05:00
lib [Polly] Mark classes as final by default. NFC. 2022-05-17 12:05:39 -05:00
test [polly] Load NPM pass plugin for NPM test. 2022-05-09 16:10:01 -05:00
tools
unittests [polly][unittests] Link DeLICMTests with libLLVMCore 2022-01-28 21:58:40 +01:00
utils Harmonize Python shebang 2020-07-16 21:53:45 +02:00
www [Polly] Clean up Polly's getting started docs. 2021-10-14 12:26:57 -05:00
.arclint
.gitattributes
.gitignore
CMakeLists.txt [cmake] Make include(GNUInstallDirs) always below project(..) 2022-01-20 18:59:17 +00:00
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.