forked from OSchip/llvm-project
d840fc7277
This allows code such as: void multiple_types(char *Short, char *Float, char *Double) { for (long i = 0; i < 100; i++) { Short[i] = *(short *)&Short[2 * i]; Float[i] = *(float *)&Float[4 * i]; Double[i] = *(double *)&Double[8 * i]; } } To model such code we use as canonical element type of the modeled array the smallest element type of all original array accesses, if type allocation sizes are multiples of each other. Otherwise, we use a newly created iN type, where N is the gcd of the allocation size of the types used in the accesses to this array. Accesses with types larger as the canonical element type are modeled as multiple accesses with the smaller type. For example the second load access is modeled as: { Stmt_bb2[i0] -> MemRef_Float[o0] : 4i0 <= o0 <= 3 + 4i0 } To support code-generating these memory accesses, we introduce a new method getAccessAddressFunction that assigns each statement instance a single memory location, the address we load from/store to. Currently we obtain this address by taking the lexmin of the access function. We may consider keeping track of the memory location more explicitly in the future. We currently do _not_ handle multi-dimensional arrays and also keep the restriction of not supporting accesses where the offset expression is not a multiple of the access element type size. This patch adds tests that ensure we correctly invalidate a scop in case these accesses are found. Both types of accesses can be handled using the very same model, but are left to be added in the future. We also move the initialization of the scop-context into the constructor to ensure it is already available when invalidating the scop. Finally, we add this as a new item to the 2.9 release notes Reviewers: jdoerfert, Meinersbur Differential Revision: http://reviews.llvm.org/D16878 llvm-svn: 259784 |
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cmake | ||
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include/polly | ||
lib | ||
test | ||
tools | ||
utils | ||
www | ||
.arcconfig | ||
.arclint | ||
.gitattributes | ||
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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.