BBVectorize would, except for loads and stores, always fuse instructions
so that the first instruction (in the current source order) would always
represent the low part of the input vectors and the second instruction
would always represent the high part. This lead to too many shuffles
being produced because sometimes the opposite order produces fewer of them.
With this change, BBVectorize tracks the kind of pair connections that form
the DAG of candidate pairs, and uses that information to reorder the pairs to
avoid excess shuffles. Using this information, a future commit will be able
to add VTTI-based shuffle costs to the pair selection procedure. Importantly,
the number of remaining shuffles can now be estimated during pair selection.
There are some trivial instruction reorderings in the test cases, and one
simple additional test where we certainly want to do a reordering to
avoid an unnecessary shuffle.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@167122 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
Instead of recomputing relative pointer information just prior to fusing,
cache this information (which also needs to be computed during the
candidate-pair selection process). This cuts down on the total number of
SE queries made, and also is a necessary intermediate step on the road toward
including shuffle costs in the pair selection procedure.
No functionality change is intended.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@167049 91177308-0d34-0410-b5e6-96231b3b80d8
Stop propagating the FlipMemInputs variable into the routines that
create the replacement instructions. Instead, just flip the arguments
of those routines. This allows for some associated cleanup (not all
of which is done here). No functionality change is intended.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@167042 91177308-0d34-0410-b5e6-96231b3b80d8
SE was being called during the instruction-fusion process (when the result
is unreliable, and thus ignored). No functionality change is intended.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@167037 91177308-0d34-0410-b5e6-96231b3b80d8
The monolithic interface for instruction costs has been split into
several functions. This is the corresponding change. No functionality
change is intended.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@166865 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
This is needed so that perl's SHA can be compiled (otherwise
BBVectorize takes far too long to find its fixed point).
I'll try to come up with a reduced test case.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@166738 91177308-0d34-0410-b5e6-96231b3b80d8
This is the first of several steps to incorporate information from the new
TargetTransformInfo infrastructure into BBVectorize. Two things are done here:
1. Target information is used to determine if it is profitable to fuse two
instructions. This means that the cost of the vector operation must not
be more expensive than the cost of the two original operations. Pairs that
are not profitable are no longer considered (because current cost information
is incomplete, for intrinsics for example, equal-cost pairs are still
considered).
2. The 'cost savings' computed for the profitability check are also used to
rank the DAGs that represent the potential vectorization plans. Specifically,
for nodes of non-trivial depth, the cost savings is used as the node
weight.
The next step will be to incorporate the shuffle costs into the DAG weighting;
this will give the edges of the DAG weights as well. Once that is done, when
target information is available, we should be able to dispense with the
depth heuristic.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@166716 91177308-0d34-0410-b5e6-96231b3b80d8
Unreachable blocks can have invalid instructions. For example,
jump threading can produce self-referential instructions in
unreachable blocks. Also, we should not be spending time
optimizing unreachable code. Fixes PR14133.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@166423 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
