llvm-capstone/polly
Michael Kruse acbdd07de6 [DependenceInfo] Compute WAR dependence info using ISL kills. NFC.
When reading code of Dependences::calculateDependences, I noticed that
WAR is computed specifically by buildWAR.  Given ISL now
supports "kills" in approximate dataflow analysis, this patch takes
advantage of it.

This patch also cleans up a couple lines redundant codes.

Patch by bin.narwal <bin.narwal@gmail.com>

Differential Revision: https://reviews.llvm.org/D66741

llvm-svn: 370396
2019-08-29 18:55:55 +00:00
..
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 [DependenceInfo] Compute WAR dependence info using ISL kills. NFC. 2019-08-29 18:55:55 +00:00
test [Polly-ACC] Fix test after IR-printer change. 2019-08-13 22:42:08 +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 Adjust documentation for git migration. 2019-01-29 16:37:27 +00:00
.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

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.