Code duplication (subsequently removed by refactoring) allowed
a logic discrepancy to creep in here.
We were being conservative about creating a vector binop -- but
not a vector cmp -- in the case where a vector op has the same
estimated cost as the scalar op. We want to be more aggressive
here because that can allow other combines based on reduced
instruction count/uses.
We can reverse the transform in DAGCombiner (potentially with a
more accurate cost model) if this causes regressions.
AFAIK, this does not conflict with InstCombine. We have a
scalarize transform there, but it relies on finding a constant
operand or a matching insertelement, so that means it eliminates
an extractelement from the sequence (so we won't have 2 extracts
by the time we get here if InstCombine succeeds).
Differential Revision: https://reviews.llvm.org/D75062
This should be the last step in the current cleanup.
Follow-ups should resolve the TODO about cost calc
and enable the more general case where we extract
different elements.
getOperationCost() is not the cost we wanted; that's not the
throughput value that the rest of the calculation uses.
We may want to switch everything in this code to use the
getInstructionThroughput() wrapper to avoid these kinds of
problems, but I'll look at that as a follow-up because that
can create other logical diffs via using optional parameters
(we'd need to speculatively create the vector instruction to
make a fair(er) comparison).
binop (extelt X, C), (extelt Y, C) --> extelt (binop X, Y), C
This is a transform that has been considered for canonicalization (instcombine)
in the past because it reduces instruction count. But as shown in the x86 tests,
it's impossible to know if it's profitable without a cost model. There are many
potential target constraints to consider.
We have implemented similar transforms in the backend (DAGCombiner and
target-specific), but I don't think we have this exact fold there either (and if
we did it in SDAG, it wouldn't work across blocks).
Note: this patch was intended to handle the more general case where the extract
indexes do not match, but it got too big, so I scaled it back to this pattern
for now.
Differential Revision: https://reviews.llvm.org/D74495
The variable was added to the initial commit via copy/paste of existing
code, but it wasn't actually used in the code. We can add it back with
the proper usage if/when that is needed.
We have several bug reports that could be characterized as "reducing scalarization",
and this topic was also raised on llvm-dev recently:
http://lists.llvm.org/pipermail/llvm-dev/2020-January/138157.html
...so I'm proposing that we deal with these patterns in a new, lightweight IR vector
pass that runs before/after other vectorization passes.
There are 4 alternate options that I can think of to deal with this kind of problem
(and we've seen various attempts at all of these), but they all have flaws:
InstCombine - can't happen without TTI, but we don't want target-specific
folds there.
SDAG - too late to assist other vectorization passes; TLI is not equipped
for these kind of cost queries; limited to a single basic block.
CGP - too late to assist other vectorization passes; would need to re-implement
basic cleanups like CSE/instcombine.
SLP - doesn't fit with existing transforms; limited to a single basic block.
This initial patch/transform is based on existing code in AggressiveInstCombine:
we walk backwards through the function looking for a pattern match. But we diverge
from that cost-independent IR canonicalization pass by using TTI to decide if the
vector alternative is profitable.
We probably have at least 10 similar bug reports/patterns (binops, constants,
inserts, cheap shuffles, etc) that would fit in this pass as follow-up enhancements.
It's possible that we could iterate on a worklist to fix-point like InstCombine does,
but it's safer to start with a most basic case and evolve from there, so I didn't
try to do anything fancy with this initial implementation.
Differential Revision: https://reviews.llvm.org/D73480
