llvm-project/polly
Arthur Eubanks 34a8a437bf [NewPM] Hide pass manager debug logging behind -debug-pass-manager-verbose
Printing pass manager invocations is fairly verbose and not super
useful.

This allows us to remove DebugLogging from pass managers and PassBuilder
since all logging (aside from analysis managers) goes through
instrumentation now.

This has the downside of never being able to print the top level pass
manager via instrumentation, but that seems like a minor downside.

Reviewed By: ychen

Differential Revision: https://reviews.llvm.org/D101797
2021-05-07 21:51:47 -07:00
..
cmake [Windows][Polly] Disable LLVMPolly module for all compilers on Windows 2020-09-15 09:12:38 +03:00
docs Fixed Typos 2021-04-28 08:55:03 +05:30
include/polly [Polly][ManualOpt] Match interpretation of unroll metadata to LoopUnrolls's. 2021-04-24 04:30:19 -05:00
lib [NewPM] Hide pass manager debug logging behind -debug-pass-manager-verbose 2021-05-07 21:51:47 -07:00
test [Polly][ManualOpt] Match interpretation of unroll metadata to LoopUnrolls's. 2021-04-24 04:30:19 -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.