hanchenye-llvm-project/polly
Roman Gareev 5f99f8656e Add a flag to dump SCoP optimized with the IslScheduleOptimizer pass
Dump polyhedral descriptions of Scops optimized with the isl scheduling
optimizer and the set of post-scheduling transformations applied
on the schedule tree to be able to check the work of the IslScheduleOptimizer
pass at the polyhedral level.

Reviewed-by: Tobias Grosser <tobias@grosser.es>

Differential Revision: https://reviews.llvm.org/D23740

llvm-svn: 279395
2016-08-21 11:20:39 +00:00
..
cmake Respect LLVM_INSTALL_TOOLCHAIN_ONLY. 2016-06-21 18:14:01 +00:00
docs docs: Remove reference to PoCC 2016-05-17 19:44:16 +00:00
include/polly Simplify AccFuncMap to vector<> AccessFunctions 2016-08-21 11:09:19 +00:00
lib Add a flag to dump SCoP optimized with the IslScheduleOptimizer pass 2016-08-21 11:20:39 +00:00
test Add a flag to dump SCoP optimized with the IslScheduleOptimizer pass 2016-08-21 11:20:39 +00:00
tools GPGPU: Cache PTX kernels 2016-08-04 09:15:58 +00:00
utils Revise polly-{update|check}-format targets 2015-09-14 16:59:50 +00:00
www Fix spacing around variable initializations and for-loops. NFC. 2016-08-09 17:49:24 +00:00
.arcconfig Upgrade all the .arcconfigs to https. 2016-07-14 13:15:37 +00:00
.arclint Adjusted arc linter config for modern version of arcanist 2015-08-12 09:01:16 +00:00
.gitattributes
.gitignore
CMakeLists.txt GPGPU: Shorten ppcg include paths to avoid conflict with cuda.h 2016-07-15 07:50:36 +00:00
CREDITS.txt
LICENSE.txt Update copyright year to 2016. 2016-03-30 22:41:38 +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.