llvm-project/polly
Eli Friedman 9b9454af8a Require "target datalayout" to be at the beginning of an IR file.
This will allow us to use the datalayout to disambiguate other
constructs in IR, like load alignment. Split off from D78403.

Differential Revision: https://reviews.llvm.org/D78413
2020-04-20 11:55:49 -07:00
..
cmake [cmake] Use source-groups in Polly. 2020-01-07 14:20:06 -06:00
docs [Polly] Add -polly-isl-arg command line option. 2020-04-06 08:56:57 -05:00
include/polly [polly][opaque pointers] Remove use of deprecated APIs. 2020-04-03 18:00:33 -07:00
lib Fix interaction of static plugins with -DLLVM_LINK_LLVM_DYLIB=ON. 2020-04-17 11:49:05 -07:00
test Require "target datalayout" to be at the beginning of an IR file. 2020-04-20 11:55:49 -07:00
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 [NFC] correct "thier" to "their" 2020-04-15 14:38:52 -07:00
.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 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.