llvm-project/polly
Mateusz Mikuła e71cda21d7 [Windows][Polly] Disable LLVMPolly module for all compilers on Windows
Before this patch, the cmake disabled loadable modules when compiling
with Visual Studio. However, the reason for this is a limitation of the
Windows DLLs, thus this restriction should apply to any compiler for the
Windows platform, such as MinGW, Cygwin, icc, etc.

Differential Revision: https://reviews.llvm.org/D87524
2020-09-15 09:12:38 +03:00
..
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 12 2020-07-15 12:05:05 +02:00
include/polly [Polly] Use llvm::function_ref. NFC. 2020-08-26 13:15:23 -05:00
lib [Windows][Polly] Disable LLVMPolly module for all compilers on Windows 2020-09-15 09:12:38 +03:00
test [Polly] Fix use-after-free. 2020-08-22 10:10:49 -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] Support linking ScopPassManager against LLVM dylib 2020-08-07 06:46:35 +02:00
utils Harmonize Python shebang 2020-07-16 21:53:45 +02:00
www [BasicAA] Replace -basicaa with -basic-aa in polly 2020-06-30 15:50:17 -07:00
.arclint
.gitattributes
.gitignore
CMakeLists.txt [cmake] Make gtest include directories a part of the library interface 2020-08-27 15:35:57 +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 Test commit 2017-06-28 12:58:44 +00:00

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.