hanchenye-llvm-project/polly
Philip Pfaffe 66a05ad672 Simplify the implementation of getCUDALibDeviceFunction. NFC.
Summary:
The function is currently awfully complicated. Drop the IILE and use
StringRef over std::string.

Reviewers: Meinersbur, grosser, bollu

Reviewed By: Meinersbur

Subscribers: nemanjai, kbarton, bollu, llvm-commits, pollydev

Differential Revision: https://reviews.llvm.org/D48070

llvm-svn: 334695
2018-06-14 08:54:55 +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 [OpTree] Introduce shortcut for computing the def->target mapping. NFCI. 2018-06-06 21:37:35 +00:00
lib Simplify the implementation of getCUDALibDeviceFunction. NFC. 2018-06-14 08:54:55 +00:00
test [test] Fix a typo in a test case [NFCI] 2018-06-13 21:46:29 +00:00
tools [GPUJIT] Improved temporary file handling. 2017-09-19 10:41:29 +00:00
unittests Remove the last uses of isl::give and isl::take 2018-04-29 00:28:26 +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
.gitattributes
.gitignore
CMakeLists.txt Back out of GPU Codegen if NVPTX is not available 2018-06-07 21:10:49 +00:00
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.