maxjhandsome
/
llvm-project
forked from OSchip/llvm-project
1
0
Fork 0
Code Issues Pull Requests Packages Releases Wiki Activity
llvm-project/polly
History
Tobias Grosser ad41c4ce20 Add dependency to intrinsics_gen 
The IndVarSimplify pass in Polly uses the intrinsics header. We need to ensure
that the header is generated, before we use it. This patch fixes the problem
for the cmake build (it did not show up in the autoconf one).

Contributed by:   Sameer Sahasrabuddhe  <sameer.sahasrabuddhe@amd.com>

llvm-svn: 163130
 		2012-09-04 08:19:12 +00:00
..
autoconf autoconf: Only define GPGPU_CODEGEN, if that feature is requested 2012-08-21 12:29:10 +00:00
cmake Add support for libpluto as the scheduling optimizer. 2012-08-02 07:47:26 +00:00
docs
…
include Pocc: Fix some bugs in the PoCC optimizer pass 2012-08-30 11:49:38 +00:00
lib Add dependency to intrinsics_gen 2012-09-04 08:19:12 +00:00
test Add preliminary implementation for GPGPU code generation. 2012-08-03 12:50:07 +00:00
tools Update libGPURuntime to be dual licensed under MIT and UIUC license. 2012-07-06 10:40:15 +00:00
utils Update isl to a newer version 2012-09-03 07:42:40 +00:00
www Remove executable bits from html files 2012-08-15 05:50:24 +00:00
CMakeLists.txt Add preliminary implementation for GPGPU code generation. 2012-08-03 12:50:07 +00:00
CREDITS.txt (Test commit for polly) 2011-07-16 13:30:03 +00:00
LICENSE.txt Happy new year 2012! 2012-01-01 08:16:56 +00:00
Makefile Revert "Fix a bug introduced by r153739: We are not able to provide the correct" 2012-04-11 07:43:13 +00:00
Makefile.common.in
…
Makefile.config.in Add support for libpluto as the scheduling optimizer. 2012-08-02 07:47:26 +00:00
README Remove some empty lines 2011-10-04 06:56:36 +00:00
configure autoconf: Only define GPGPU_CODEGEN, if that feature is requested 2012-08-21 12:29:10 +00:00

README 

Polly - Polyhedral optimizations for LLVM

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.