llvm-project/polly
patacca 812ce7f9be [Polly] Refactoring isInnermost() from isl to use the C++ wrapper
Polly use algorithms from the Integer Set Library (isl), which is a library written in C and which is incompatible with the rest of the LLVM as it is written in C++.

Changes made:
 - Refactoring isInnermost() to take C++ bindings instead of the plain isl C api.
 - Addition of manage_copy() when needed to get the reference for the isl_ast_node object

Reviewed By: Meinersbur

Differential Revision: https://reviews.llvm.org/D99841
2021-04-05 21:16:52 -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] Refactoring isInnermost() from isl to use the C++ wrapper 2021-04-05 21:16:52 -05:00
lib [Polly] Refactoring isInnermost() from isl to use the C++ wrapper 2021-04-05 21:16:52 -05:00
test [Polly] Port DeadCodeElim to the NewPM. 2021-03-24 01:01:29 -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.