forked from OSchip/llvm-project
2dab88e652
In case the schedule has not changed and the operand tree root uses a
value defined in an ancestor loop, the def-to-target mapping is trivial.
For instance, the SCoP
for (int i < 0; i < N; i+=1) {
DefStmt:
D = ...;
for (int j < 0; j < N; j+=1) {
TargetStmt:
use(D);
}
}
has DefStmt-to-TargetStmt mapping of
{ DefStmt[i] -> TargetStmt[i,j] }
This should apply on the majority of def-to-target mappings.
This patch detects this case and directly constructs the expected
mapping. It assumes that the mapping never crosses the loop header
DefStmt is in, which ForwardOpTree does not support at the moment
anyway.
Differential Revision: https://reviews.llvm.org/D47752
llvm-svn: 334134
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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.