forked from OSchip/llvm-project
77a98366ce
Summary: This change is step four in the series of changes to remove alignment argument from memcpy/memmove/memset in favour of alignment attributes. Steps: Step 1) Remove alignment parameter and create alignment parameter attributes for memcpy/memmove/memset. ( rL322965, rC322964, rL322963 ) Step 2) Expand the IRBuilder API to allow creation of memcpy/memmove with differing source and dest alignments. ( rL323597 ) Step 3) Update Clang to use the new IRBuilder API. ( rC323617 ) Step 4) Update Polly to use the new IRBuilder API. Step 5) Update LLVM passes that create memcpy/memmove calls to use the new IRBuilder API, and those that use use MemIntrinsicInst::[get|set]Alignment() to use [get|set]DestAlignment() and [get|set]SourceAlignment() instead. Step 6) Remove the single-alignment IRBuilder API for memcpy/memmove, and the MemIntrinsicInst::[get|set]Alignment() methods. Reference http://lists.llvm.org/pipermail/llvm-dev/2015-August/089384.html http://lists.llvm.org/pipermail/llvm-commits/Week-of-Mon-20151109/312083.html Reviewers: jdoerfert, grosser, bollu Subscribers: llvm-commits Differential Revision: https://reviews.llvm.org/D41677 llvm-svn: 323618 |
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cmake | ||
docs | ||
include/polly | ||
lib | ||
test | ||
tools | ||
unittests | ||
utils | ||
www | ||
.arcconfig | ||
.arclint | ||
.gitattributes | ||
.gitignore | ||
CMakeLists.txt | ||
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.