forked from OSchip/llvm-project
113fa82c3c
multiplication
The following code modifies elements of the array D.
for (i = 0; i < _PB_NI; i++)
for (j = 0; j < _PB_NJ; j++)
{
for (k = 0; k < _PB_NK; k++)
{
double Mul = A[i][k] * B[k][j];
D[i][j][k] += Mul;
C[i][j] += Mul;
}
}
Nevertheless, the code is recognised as a matrix-matrix multiplication, since
the second and third dimensions of D are accessed with non-zero strides.
This fixes the typo, which was made during the translation to C++ bindings
(https://reviews.llvm.org/D35845).
Reviewed By: Michael Kruse <llvm@meinersbur.de>
Differential Revision: https://reviews.llvm.org/D110491
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| cmake | ||
| docs | ||
| include/polly | ||
| lib | ||
| test | ||
| tools | ||
| unittests | ||
| utils | ||
| www | ||
| .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.