hanchenye-llvm-project/polly
Guillaume Chatelet ab11b9188d [Alignment][NFC] Remove AllocaInst::setAlignment(unsigned)
Summary:
This is patch is part of a series to introduce an Alignment type.
See this thread for context: http://lists.llvm.org/pipermail/llvm-dev/2019-July/133851.html
See this patch for the introduction of the type: https://reviews.llvm.org/D64790

Reviewers: courbet

Subscribers: jholewinski, arsenm, jvesely, nhaehnle, eraman, hiraditya, cfe-commits, llvm-commits

Tags: #clang, #llvm

Differential Revision: https://reviews.llvm.org/D68141

llvm-svn: 373207
2019-09-30 13:34:44 +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 [Alignment][NFC] Remove AllocaInst::setAlignment(unsigned) 2019-09-30 13:34:44 +00:00
test Revert "Update polly test for SCEV change." 2019-09-30 07:47:08 +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
www Adjust documentation for git migration. 2019-01-29 16:37:27 +00:00
.arcconfig
.arclint
.gitattributes
.gitignore
CMakeLists.txt
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

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.