llvm-project/polly
Reid Kleckner 1dfede3122 Move CodeGenFileType enum to Support/CodeGen.h
Avoids the need to include TargetMachine.h from various places just for
an enum. Various other enums live here, such as the optimization level,
TLS model, etc. Data suggests that this change probably doesn't matter,
but it seems nice to have anyway.
2019-11-13 16:39:34 -08:00
..
cmake [CMake] Fix generation of exported targets in build directory 2018-11-06 15:18:17 +00:00
docs Bump the trunk version to 10.0.0svn 2019-07-18 11:51:05 +00:00
include/polly [NFC][ScopBuilder] Move buildDomains and its callees to ScopBuilder. 2019-08-06 21:51:18 +00:00
lib Move CodeGenFileType enum to Support/CodeGen.h 2019-11-13 16:39:34 -08:00
test [GPGPU] Fix regression test after 395124. 2019-11-13 06:20:17 +00:00
tools Fix typos throughout the license files that somehow I and my reviewers 2019-01-21 09:52:34 +00:00
unittests Update the file headers across all of the LLVM projects in the monorepo 2019-01-19 08:50:56 +00:00
utils [arc] Remove unittesting from arcconfig 2018-05-15 13:43:42 +00:00
www [www] More HTTPS and outdated link fixes. 2019-11-08 14:41:27 -08:00
.arcconfig [arc] Remove unittesting from arcconfig 2018-05-15 13:43:42 +00:00
.arclint
.gitattributes
.gitignore
CMakeLists.txt [JSONExporter] Replace bundled Jsoncpp with llvm/Support/JSON.h. NFC. 2018-08-01 00:15:16 +00:00
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.