llvm-project/polly
Kevin Zhou 1ab2753d4c [Polly] Refactoring IsInnermostParallel() in ISL to take the C++ wrapper object. NFC
Currently, the IslAst library is a C library that would be incompatible with the rest of the LLVM because LLVM is written in C++.
I took one function, IsInnermostParallel(), and refactored it so that it would take the C++ wrapper object instead of using reference counters with the C ISL library. As well, all the references that use IsInnermostParallel() will use manage_copy() since they are still expecting the C object.

Reviewed By: Meinersbur

Differential Revision: https://reviews.llvm.org/D97425
2021-02-26 18:41:44 -06:00
..
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 IsInnermostParallel() in ISL to take the C++ wrapper object. NFC 2021-02-26 18:41:44 -06:00
lib [Polly] Refactoring IsInnermostParallel() in ISL to take the C++ wrapper object. NFC 2021-02-26 18:41:44 -06:00
test [Polly] Fix test after D96534. 2021-02-19 12:49:29 -06:00
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 Fix typos throughout the license files that somehow I and my reviewers 2019-01-21 09:52:34 +00:00
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.