llvm-project/polly
Tobias Grosser c49f115b27 [RuntimeDebugBuilder] Do not break for 64 bit integers
In r330292 this assert was turned incorrectly into an unreachable, but
the correct behavior (thanks Michael) is to assert for anything that is
not 64 bit, but falltrough for 64 bit. I document this in the source
code.

llvm-svn: 330309
2018-04-19 05:38:12 +00:00
..
cmake [CMake] Use only keyword-version of target_link_library. NFC. 2018-01-12 16:09:18 +00:00
docs [doc] Overhaul doc on preparing IR for processing by Polly. 2018-04-06 19:24:18 +00:00
include/polly [RuntimeDebugBuilder] Print vectors passed without withspaces 2018-04-18 20:28:26 +00:00
lib [RuntimeDebugBuilder] Do not break for 64 bit integers 2018-04-19 05:38:12 +00:00
test [ScopDetect / ScopInfo] Get statistics for scops without any loop correctly 2018-04-18 20:03:36 +00:00
tools [GPUJIT] Improved temporary file handling. 2017-09-19 10:41:29 +00:00
unittests Add isl operator overloads for isl::pw_aff (Try II) 2018-04-12 06:15:17 +00:00
utils Revise polly-{update|check}-format targets 2015-09-14 16:59:50 +00:00
www [Polly] Information about generalized matrix multiplication 2017-09-24 19:00:25 +00:00
.arcconfig [polly] Set up .arcconfig to point to new Diffusion PLO repository 2017-11-27 17:34:03 +00:00
.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 [CMake] Use only keyword-version of target_link_library. NFC. 2018-01-12 16:09:18 +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.