forked from OSchip/llvm-project
75aa1a9a49
This commit switches Polly over to the isl::obj::foreach_* implementation, which
is part of the new isl bindings and follows the foreach pattern established in
Polly by Michael Kruse.
The original isl C function:
isl_stat isl_union_set_foreach_set(__isl_keep isl_union_set *uset,
isl_stat (*fn)(__isl_take isl_set *set, void *user), void *user);
which required the user to define a static callback function to which all
interesting parameters are passed via a 'void *' user-pointer, is on the
C++ side available as a function that takes a std::function<>, which can
carry any additional arguments without the need for a user pointer:
stat UnionSet::foreach_set(const std::function<stat(set)> &fn) const;
The following code illustrates the use of the new C++ interface:
auto Lambda = [=, &Result](isl::set Set) -> isl::stat {
auto Shifted = shiftDimension(Set, Pos, Amount);
Result = Result.add(Shifted);
return isl::stat::ok;
}
UnionSet.foreach_set(Lambda);
Polly had some specialized foreach functions which did not require the lambdas
to return a status flag. We remove these functions in this commit to move Polly
completely over to the new isl interface. We may in the future discuss if
functors without return values can be supported easily.
Another extension proposed by Michael Kruse is the use of C++ iterators to allow
the use of normal for loops to iterate over these sets. Such an extension would
allow us to further simplify the code.
Reviewed-by: Michael Kruse <llvm@meinersbur.de>
Differential Revision: https://reviews.llvm.org/D30620
llvm-svn: 300323
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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.