hanchenye-llvm-project/polly
Michael Kruse b6b65834a1 [Simplify] Mark (and sweep) based on latest access relation.
Previously we marked scalars based on the original access function. However,
when a scalar read access is redirected, the original definition
(or incoming values of a PHI) is not used anymore, and can be deleted
(unless referenced by use that has not been redirected).

llvm-svn: 316660
2017-10-26 12:34:36 +00:00
..
cmake [CMake] FindJsoncpp.cmake: Use descriptive variable name for libjsoncpp.so path. 2017-07-18 10:10:02 +00:00
docs [Docs] Replace 0-byte incorrect GEMM_double image with the one from www/images 2017-09-28 15:31:24 +00:00
include/polly [ScopBuilder] Introduce -polly-stmt-granularity=scalar-indep option. 2017-10-05 13:43:00 +00:00
lib [Simplify] Mark (and sweep) based on latest access relation. 2017-10-26 12:34:36 +00:00
test [Simplify] Mark (and sweep) based on latest access relation. 2017-10-26 12:34:36 +00:00
tools [GPUJIT] Improved temporary file handling. 2017-09-19 10:41:29 +00:00
unittests [test] Add some test cases for computeArrayUnused. 2017-08-21 23:04:55 +00:00
utils
www [Polly] Information about generalized matrix multiplication 2017-09-24 19:00:25 +00:00
.arcconfig
.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 [Polly][CMake] Skip unit-tests in lit if gtest is not available 2017-07-11 11:37:35 +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.