llvm-project

History

Karthika Devi C 283feb42ee

[polly] Make reduction detection checks more robust - part 2 (#80721 )

Existing reduction detection algorithm does two types of memory checks
before marking a load store pair as reduction.
Second check is to verify there is no other memory access in ScopStmt
overlapping with the memory of load and store that forms the reduction.
Existing check misses cases where there could be probable overlap such
as
	A[V] += A[P];
In the above case there is chance of overlap between A[V] and A[P] which
is missed.
This commit addresses this by removing the parameter from space before
checking for compatible space.

Part 1 of this patch :
[75297](https://github.com/llvm/llvm-project/pull/75297)

2024-02-12 13:49:32 -08:00

cmake

[polly] [CMake] Create component and install target in add_polly_library (#66598 )

2023-12-25 10:31:16 +00:00

docs

Clear release notes for 18.x

2023-07-25 13:58:49 +02:00

include/polly

[llvm][NFC] A start at cleaning up zero byte files that should have been removed (#74404 )

2023-12-05 01:57:14 -05:00

lib

[polly] Make reduction detection checks more robust - part 2 (#80721 )

2024-02-12 13:49:32 -08:00

test

[polly] Make reduction detection checks more robust - part 2 (#80721 )

2024-02-12 13:49:32 -08:00

unittests

…

utils

…

www

[polly][www] Remove unused VideoJS

2023-09-13 12:24:46 -07:00

.arclint

…

.gitattributes

…

.gitignore

…

CMakeLists.txt

…

CREDITS.txt

…

LICENSE.TXT

…

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.