llvm-project/polly
Tobias Grosser 7164b7d347 Update isl-cpp bindings
We upstreamed the export of isl_val_2exp, to the official cpp bindings.
In this process, we concluded that pow2 is a better and more widely used
name for this functionality. Hence, both the official isl-cpp bindings
and our derived variant use now the term pow2.

llvm-svn: 339312
2018-08-09 05:07:14 +00:00
..
cmake [JSONExporter] Replace bundled Jsoncpp with llvm/Support/JSON.h. NFC. 2018-08-01 00:15:16 +00:00
docs Update docs version and clear release notes after 8.0.0 version bump 2018-08-01 14:11:32 +00:00
include/polly [ScopBuilder] Set domain to empty instead of NULL. 2018-08-01 22:28:32 +00:00
lib Update isl-cpp bindings 2018-08-09 05:07:14 +00:00
test [ScopBuilder] Set domain to empty instead of NULL. 2018-08-01 22:28:32 +00:00
tools Update copyright year to 2018. 2018-06-18 12:22:17 +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 [Polly] Information about generalized matrix multiplication 2017-09-24 19:00:25 +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 [External] Move lib/JSON to lib/External/JSON. NFC. 2017-02-05 15:26:56 +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.