llvm-project/polly
James Y Knight 693d39dd12 Remove irrelevant references to legacy git repositories from
compiler identification lines in test-cases.

(Doing so only because it's then easier to search for references which
are actually important and need fixing.)

llvm-svn: 351200
2019-01-15 16:18:52 +00:00
..
cmake [CMake] Fix generation of exported targets in build directory 2018-11-06 15:18:17 +00:00
docs [doc] Fix HowToManuallyUseTheIndividualPiecesOfPolly 2018-09-26 15:22:39 +00:00
include/polly [TI removal] Make `getTerminator()` return a generic `Instruction`. 2018-10-15 10:42:50 +00:00
lib Fix clang -Wimplicit-fallthrough warnings across llvm, NFC 2018-11-01 19:54:45 +00:00
test Remove irrelevant references to legacy git repositories from 2019-01-15 16:18:52 +00:00
tools Update year in license files 2019-01-15 15:10:32 +00:00
unittests Update isl-cpp bindings 2018-08-09 05:07:14 +00:00
utils [arc] Remove unittesting from arcconfig 2018-05-15 13:43:42 +00:00
www Move www/experiments to docs/experiments 2018-09-26 15:21:43 +00:00
.arcconfig [arc] Remove unittesting from arcconfig 2018-05-15 13:43:42 +00:00
.arclint [External] Move lib/JSON to lib/External/JSON. NFC. 2017-02-05 15:26:56 +00:00
.gitattributes
.gitignore Do not track the isl PDF manual in SVN 2017-01-16 11:48:03 +00:00
CMakeLists.txt [JSONExporter] Replace bundled Jsoncpp with llvm/Support/JSON.h. NFC. 2018-08-01 00:15:16 +00:00
CREDITS.txt
LICENSE.txt Update year in license files 2019-01-15 15:10:32 +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.