llvm-project

History

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

configure

do not require cloog from configure

2012-11-26 23:03:41 +00:00

CREDITS.txt

(Test commit for polly)

2011-07-16 13:30:03 +00:00

LICENSE.txt

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

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.