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Philip Pfaffe 4f4dfbacad [isl] Simplify iterator implementation by building on top of list accessors 
Summary:
With the new accessors, it's straightforward to use the templated
iterator instead of subclassing it for all the list types.

Depends on D49019

Reviewers: grosser, Meinersbur, bollu

Reviewed By: grosser

Subscribers: mehdi_amini, steven_wu, dexonsmith, pollydev, llvm-commits

Differential Revision: https://reviews.llvm.org/D49021

llvm-svn: 337702
 		2018-07-23 15:28:50 +00:00
..
cmake [CMake] Use only keyword-version of target_link_library. NFC. 2018-01-12 16:09:18 +00:00
docs [Docs] Fix generation of manpages. 2018-07-09 20:26:11 +00:00
include/polly [isl] Simplify iterator implementation by building on top of list accessors 2018-07-23 15:28:50 +00:00
lib [DependenceInfo] Use isl++ to replace foreach_set with for loop 2018-07-17 07:08:06 +00:00
test Fix for r336080: Missing colon in REQUIRES line 2018-07-02 08:36:49 +00:00
tools Update copyright year to 2018. 2018-06-18 12:22:17 +00:00
unittests [unittest/DeLICM] Replace isl foreach calls with for loops 2018-07-17 06:08:04 +00:00
utils [arc] Remove unittesting from arcconfig 2018-05-15 13:43:42 +00:00
www [Polly] Information about generalized matrix multiplication 2017-09-24 19:00:25 +00:00
.arcconfig [arc] Remove unittesting from arcconfig 2018-05-15 13:43:42 +00:00
.arclint [External] Move lib/JSON to lib/External/JSON. NFC. 2017-02-05 15:26:56 +00:00
.gitattributes
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.gitignore
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CMakeLists.txt Back out of GPU Codegen if NVPTX is not available 2018-06-07 21:10:49 +00:00
CREDITS.txt
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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.