llvm-project/polly
Michael Kruse 0e93f3b0a0 [Polly] Replace use of std::stringstream. NFC.
Use of std::-style (io)streams is discouraged in the LLVM coding style
(https://llvm.org/docs/CodingStandards.html#include-iostream-is-forbidden).
Replace with a use of llvm::Twine (which uses llvm::raw_ostream behind
the scenes).
2020-03-09 11:35:34 -05:00
..
cmake [cmake] Use source-groups in Polly. 2020-01-07 14:20:06 -06:00
docs [Polly][Docs] Fix wrong claim about optimization levels. 2020-02-10 20:14:40 -06:00
include/polly [polly] Don't count scops in a global variable. 2020-02-24 17:12:08 -08:00
lib [Polly] Replace use of std::stringstream. NFC. 2020-03-09 11:35:34 -05:00
test Revert "Revert "Reland "[Support] make report_fatal_error `abort` instead of `exit`""" 2020-02-13 10:16:06 -08:00
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www [www] More HTTPS and outdated link fixes. 2019-11-08 14:41:27 -08:00
.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.