- added function to VectorTargetTransformInfo to query cost of intrinsics
- vectorize trivially vectorizable intrinsic calls such as sin, cos, log, etc.
Reviewed by: Nadav
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@169711 91177308-0d34-0410-b5e6-96231b3b80d8
reduction variable is not used outside the loop then we ran into an
endless loop. This change checks if we found the original PHI.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@169324 91177308-0d34-0410-b5e6-96231b3b80d8
Added the code that actually performs the if-conversion during vectorization.
We can now vectorize this code:
for (int i=0; i<n; ++i) {
unsigned k = 0;
if (a[i] > b[i]) <------ IF inside the loop.
k = k * 5 + 3;
a[i] = k; <---- K is a phi node that becomes vector-select.
}
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@169217 91177308-0d34-0410-b5e6-96231b3b80d8
Previously in a vector of pointers, the pointer couldn't be any pointer type,
it had to be a pointer to an integer or floating point type. This is a hassle
for dragonegg because the GCC vectorizer happily produces vectors of pointers
where the pointer is a pointer to a struct or whatever. Vector getelementptr
was restricted to just one index, but now that vectors of pointers can have
any pointer type it is more natural to allow arbitrary vector getelementptrs.
There is however the issue of struct GEPs, where if each lane chose different
struct fields then from that point on each lane will be working down into
unrelated types. This seems like too much pain for too little gain, so when
you have a vector struct index all the elements are required to be the same.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@167828 91177308-0d34-0410-b5e6-96231b3b80d8
If the arrays are found to be disjoint then we run the vectorized version of
the loop. If they are not, we run the scalar code.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@167608 91177308-0d34-0410-b5e6-96231b3b80d8
This is important for loops in the LAPACK test-suite.
These loops start at 1 because they are auto-converted from fortran.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@167084 91177308-0d34-0410-b5e6-96231b3b80d8
Add getCostXXX calls for different families of opcodes, such as casts, arithmetic, cmp, etc.
Port the LoopVectorizer to the new API.
The LoopVectorizer now finds instructions which will remain uniform after vectorization. It uses this information when calculating the cost of these instructions.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@166836 91177308-0d34-0410-b5e6-96231b3b80d8
We used a SCEV to detect that A[X] is consecutive. We assumed that X was
the induction variable. But X can be any expression that uses the induction
for example: X = i + 2;
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@166388 91177308-0d34-0410-b5e6-96231b3b80d8
This is important for nested-loop reductions such as :
In the innermost loop, the induction variable does not start with zero:
for (i = 0 .. n)
for (j = 0 .. m)
sum += ...
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@166387 91177308-0d34-0410-b5e6-96231b3b80d8
If the pointer is consecutive then it is safe to read and write. If the pointer is non-loop-consecutive then
it is unsafe to vectorize it because we may hit an ordering issue.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@166371 91177308-0d34-0410-b5e6-96231b3b80d8
