llvm-project/polly
Tobias Grosser 3e030e178a Correctly convert APInt to gmp values
Previously this happend to work for integers up to i64, but we got it wrong
for larger numbers. Fix this and add test cases to verify this keeps working.

Reported by: Sven Verdoolaege <skimo at kotnet dot org>

llvm-svn: 183986
2013-06-14 16:23:38 +00:00
..
autoconf 'chmod -x' on files that do not need the executable bits 2012-12-29 15:09:03 +00:00
cmake autoconf/cmake: Always require isl code generation. 2012-10-21 21:48:21 +00:00
docs
include TempScopInfo: Add code to build the scalar dependences. 2013-06-10 13:55:34 +00:00
lib Correctly convert APInt to gmp values 2013-06-14 16:23:38 +00:00
test Correctly convert APInt to gmp values 2013-06-14 16:23:38 +00:00
tools Reformat with clang-format 2013-05-07 07:30:56 +00:00
utils Update isl to include isl_val changes 2013-05-31 18:04:56 +00:00
www Remove .htaccess file 2013-05-21 11:58:47 +00:00
CMakeLists.txt cmake: Add target to reformat with clang-format 2013-05-07 07:30:31 +00:00
CREDITS.txt (Test commit for polly) 2011-07-16 13:30:03 +00:00
LICENSE.txt Update the copyright coredits -- Happy new year 2013! 2013-01-01 10:00:19 +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 'chmod -x' on files that do not need the executable bits 2012-12-29 15:09:03 +00:00
Makefile.config.in 'chmod -x' on files that do not need the executable bits 2012-12-29 15:09:03 +00:00
README Trivial change to the README, mainly to test commit access. 2012-10-09 04:59:42 +00:00
configure do not require cloog from configure 2012-11-26 23:03:41 +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.