llvm-project/polly
Michael Kruse ab0556bb20 [Polly] Regenerate isl-noexceptions.h.
Regenerate the C++ wrapper header from the current isl version's
headers.

The most notable change is that some dimension sizes are represented by
an isl_size (instead of unsigned), which is a signed int. Additionally,
some function may return -1 in case of an error which already had been
fixed in the past. The C++ may no return -1 instead of UINT_MAX which
caused the problems.

Some types in Polly had been changed from unsigned to isl_size
(that were not already auto) and some loops/comparision had to be
changed to avoid unsigned/signed comparison warnings.
2021-02-14 19:17:54 -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] Regenerate isl-noexceptions.h. 2021-02-14 19:17:54 -06:00
lib [Polly] Regenerate isl-noexceptions.h. 2021-02-14 19:17:54 -06:00
test [Polly] Test all optimization levels. 2021-02-14 00:31:10 -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.