This is required to query the legality more precisely in the LoopVectorizer.
This adds another TTI function named 'forceScalarizeMaskedGather/Scatter'
function to work around the hack introduced for MVE, where
isLegalMaskedGather/Scatter would return an answer by second-guessing
where the function was called from, based on the Type passed in (vector
vs scalar). The new interface makes this explicit. It is also used by
X86 to check for vector widths where gather/scatters aren't profitable
(or don't exist) for certain subtargets.
Differential Revision: https://reviews.llvm.org/D115329
X86 allows inlining functions if the callee target features are a
subset of the caller target features. This ensures that we don't
inline something into a caller that does not support it.
However, this does not account for possible call ABI mismatches as
a result of inlining. If a call passing a vector argument was
originally in a -avx function, calling another -avx function, the
vector is passed in xmm. If we now inline it into a +avx function,
then it will be passed in ymm, even though the callee expects it in xmm.
Fix this by scanning over all calls in the function and checking
whether ABI incompatibility is possible. Calls that only pass scalar
types are excluded, as I believe those always use the same ABI
independent of target features.
Fixes https://github.com/llvm/llvm-project/issues/52660.
Differential Revision: https://reviews.llvm.org/D116036
The areFunctionArgsABICompatible() hook currently accepts a list of
pointer arguments, though what we're actually interested in is the
ABI compatibility after these pointer arguments have been converted
into value arguments.
This means that a) the current API is incompatible with opaque
pointers (because it requires inspection of pointee types) and
b) it can only be used in the specific context of ArgPromotion.
I would like to reuse the API when inspecting calls during inlining.
This patch converts it into an areTypesABICompatible() hook, which
accepts a list of types. This makes the method more generally usable,
and compatible with opaque pointers from an API perspective (the
actual usage in ArgPromotion/Attributor is still incompatible,
I'll follow up on that in separate patches).
Differential Revision: https://reviews.llvm.org/D116031
i64 mul cost is 1cy for all cpu that support avx512. Currently
all X86 cpu uses i64 mul cost in X64 cost table which is not
true for cpu that support avx512 (skx, icx).
Reviewed By: pengfei, RKSimon
Differential Revision: https://reviews.llvm.org/D115016
We ask `TTI.getAddressComputationCost()` about the cost of computing vector address,
and then multiply it by the vector width. This doesn't make any sense,
it implies that we'd do a vector GEP and then scalarize the vector of pointers,
but there is no such thing in the vectorized IR, we perform scalar GEP's.
This is *especially* bad on X86, and was effectively prohibiting any scalarized
vectorization of gathers/scatters, because `X86TTIImpl::getAddressComputationCost()`
says that cost of vector address computation is `10` as compared to `1` for scalar.
The computed costs are similar to the ones with D111222+D111220,
but we end up without masked memory intrinsics that we'd then have to
expand later on, without much luck. (D111363)
Differential Revision: https://reviews.llvm.org/D111460
... to actually ask about i1-elt-wide mask, since that is what will probably be used on AVX512.
This unblocks D111460.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D114316
I believe, this effectively completes `X86TTIImpl::getReplicationShuffleCost()`
for AVX512, other than the question of handling plain AVX512F,
where we end up with some really ugly "shuffles",
but then is there any CPU's that support AVX512, but not AVX512DQ/AVX512BW?
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D114315
Apparently my methodology was suboptimal, and not only did miss all the +VL tuples,
i also missed some plain tuples. I believe, this adds everything missing.
Indeed, these manual costmodels are just not okay long-term.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D114334
Much like the VPMOVM2[BW] / VPMOV[BW]2M from AVX512BW,
these either sign-extent the mask register into a vector,
or pack the mask from vector register.
Apparently, we didn't even have MCA tests for these,
added in rG2f364f6f0d3a2420ca78cbd80abb186657180e05,
so i'm just guessing that their perf characteristics
are optimal.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D114314
If in addition to AVX512BW (that provides `{k}<->{i8,i16}` casts and i16 shuffles),
we have AVX512VBMI, which provides i8 shuffles, we are in an optimal situation.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D114071
Note that there are many other missing costs, i'm *only* adding the ones that are queried
from `getReplicationShuffleCost()` for the existing (quite exhaustive) test coverage.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D114070
Here we get pretty lucky. AVX512F does not provide any instructions
to convert between a `k` vector mask and a vector,
but AVX512BW adds `{k}<->nX{i8,i16}`conversions,
and just as it happens, with AVX512BW we have a i16 shuffle.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D113915
Currently `X86TTIImpl::getInterleavedMemoryOpCostAVX512()` asks about i8 elt type,
so this change does affect vectorization. In the end, it will ask about i1.
We should also try to promote to i16 if we have AVX512BW, i'll do that in a follow-up.
All costs here look good, i've added the missing truncation costs in preparatory patches.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D113853
Some of the costs get larger here,
but i suppose that makes sense since we'd previously query
scalarization costs that may not be really representative of the reality.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D113852
While this one is trivial and identical to the previous patch,
there is a weird cost change in a follow-up patch that i'm not sure about.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D113851
While this one is trivial and identical to the previous patch,
there is a weird cost change in a follow-up patch that i'm not sure about.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D113850
The basic idea is simple, if we don't have native shuffle for this element type,
then we must have native shuffle for wider element type,
so promote, replicate, demote.
I believe, asking `getCastInstrCost(Instruction::Trunc` is correct semantically,
case in point `trunc <32 x i32> to <32 x i8>` aka 2 * ZMM will naively result in
2 * XMM, that then will be packed into 1 * YMM,
and it should count the cost of said packing,
not just the truncations.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D113609
This was noticed in D113609, hopefully it unblocks that patch.
There are likely other similar problems.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D113842
VBMI introduced VPERMB, so cost-model i8 replication shuffle using it.
Note that we can still model i8 replication shufflle without VBMI,
by promoting to i16/i32. That will be done in follow-ups.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D113479
BWI introduced VPERMW, so cost-model i16 replication shuffle using it.
Note that we can still model i16 replication shufflle without BWI,
by promoting to i32. That will be done in follow-ups.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D113478
This models lowering to `vpermd`/`vpermq`/`vpermps`/`vpermpd`,
that take a single input vector and a single index vector,
and are cross-lane. So far i haven't seen evidence that
replication ever results in demanding more than a single
input vector per output vector.
This results in *shockingly* lesser costs :)
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D113350
It is trivial to produce DemandedSrcElts given DemandedReplicatedElts,
so don't pass the former. Also, it isn't really useful so far
to have the overload taking the Mask, so just inline it.
Hiding it in `getInterleavedMemoryOpCost()` is problematic for a number of reasons,
including testability and reuse, let's do better.
In a followup `getUserCost()` will be taught to use to to estimate the mask costs,
which will allow for better cost model tests for it.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D113313
Even though AVX512's masked mem ops (unlike AVX1/2) have a mask
that is a `VF x i1`, replication of said masks happens after
promotion of it to `VF x i8`, so we should use `i8`, not `i1`,
when calculating the cost of mask replication.
I don't really buy that masked interleaved memory loads/stores are supported on X86.
There is zero costmodel test coverage, no actual cost modelling for the generation
of the mask repetition, and basically only two LV tests.
Additionally, i'm not very interested in AVX512.
I don't know if this really helps "soft" block over at
https://reviews.llvm.org/D111460#inline-1075467,
but i think it can't make things worse at least.
When we are being told that there is a masking, instead of
completely giving up and falling back to
fully scalarizing `BasicTTIImplBase::getInterleavedMemoryOpCost()`,
let's correctly query the cost of masked memory ops,
keep all the pretty shuffle cost modelling,
but scalarize the cost computation for the mask replication.
I think, not scalarizing the shuffles themselves
may adjust the computed costs a bit,
and maybe hopefully just enough to hide the "regressions"
at https://reviews.llvm.org/D111460#inline-1075467
I do mean hide, because the test coverage is non-existent.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D112873
Similar to AVX1, the cost of splitting/merging 512-bit -> 256-bits vectors for arithmetic operations are typically hidden due to different used ports etc.
By definition, interleaving load of stride N means:
load N*VF elements, and shuffle them into N VF-sized vectors,
with 0'th vector containing elements `[0, VF)*stride + 0`,
and 1'th vector containing elements `[0, VF)*stride + 1`.
Example: https://godbolt.org/z/df561Me5E (i64 stride 4 vf 2 => cost 6)
Now, not fully interleaved load, is when not all of these vectors is demanded.
So at worst, we could just pretend that everything is demanded,
and discard the non-demanded vectors. What this means is that the cost
for not-fully-interleaved group should be not greater than the cost
for the same fully-interleaved group, but perhaps somewhat less.
Examples:
https://godbolt.org/z/a78dK5Geq (i64 stride 4 (indices 012u) vf 2 => cost 4)
https://godbolt.org/z/G91ceo8dM (i64 stride 4 (indices 01uu) vf 2 => cost 2)
https://godbolt.org/z/5joYob9rx (i64 stride 4 (indices 0uuu) vf 2 => cost 1)
Right now, for such not-fully-interleaved loads we just use the costs
for fully-interleaved loads. But at least **in general**,
that is obviously overly pessimistic, because **in general**,
not all the shuffles needed to perform the full interleaving
will end up being live.
So what this does, is naively scales the interleaving cost
by the fraction of the live members. I believe this should still result
in the right ballpark cost estimate, although it may be over/under -estimate.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D112307
Replace X86ProcFamilyEnum::IntelSLM enum with a TuningUseSLMArithCosts flag instead, matching what we already do for Goldmont.
This just leaves X86ProcFamilyEnum::IntelAtom to replace with general Tuning/Feature flags and we can finally get rid of the old X86ProcFamilyEnum enum.
Differential Revision: https://reviews.llvm.org/D112079
A few more tuples are being queried after D111546. Might be good to model them,
They all require a lot of manual assembly surgery.
The only sched models that for cpu's that support avx2
but not avx512 are: haswell, broadwell, skylake, zen1-3
For load we have:
https://godbolt.org/z/9bnKrefcG - for intels `Block RThroughput: =40.0`; for ryzens, `Block RThroughput: =16.0`
So could pick cost of `40`
For store we have:
https://godbolt.org/z/5s3s14dEY - for intels `Block RThroughput: =40.0`; for ryzens, `Block RThroughput: =16.0`
So we could pick cost of `40`.
I'm directly using the shuffling asm the llc produced,
without any manual fixups that may be needed
to ensure sequential execution.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D111945
A few more tuples are being queried after D111546. Might be good to model them,
They all require a lot of manual assembly surgery.
The only sched models that for cpu's that support avx2
but not avx512 are: haswell, broadwell, skylake, zen1-3
For load we have:
https://godbolt.org/z/MTaKboejM - for intels `Block RThroughput: =32.0`; for ryzens, `Block RThroughput: <=16.0`
So could pick cost of `32`
For store we have:
https://godbolt.org/z/v7xPj3Wd4 - for intels `Block RThroughput: =32.0`; for ryzens, `Block RThroughput: <=32.0`
So we could pick cost of `32`.
I'm directly using the shuffling asm the llc produced,
without any manual fixups that may be needed
to ensure sequential execution.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D111944
A few more tuples are being queried after D111546. Might be good to model them,
They all require a lot of manual assembly surgery.
The only sched models that for cpu's that support avx2
but not avx512 are: haswell, broadwell, skylake, zen1-3
For load we have:
https://godbolt.org/z/11rcvdreP - for intels `Block RThroughput: <=68.0`; for ryzens, `Block RThroughput: <=48.0`
So could pick cost of `68`
For store we have:
https://godbolt.org/z/6aM11fWcP - for intels `Block RThroughput: <=64.0`; for ryzens, `Block RThroughput: <=32.0`
So we could pick cost of `64`.
I'm directly using the shuffling asm the llc produced,
without any manual fixups that may be needed
to ensure sequential execution.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D111943
A few more tuples are being queried after D111546. Might be good to model them,
They all require a lot of manual assembly surgery.
The only sched models that for cpu's that support avx2
but not avx512 are: haswell, broadwell, skylake, zen1-3
For load we have:
https://godbolt.org/z/s5b6E6jsP - for intels `Block RThroughput: <=32.0`; for ryzens, `Block RThroughput: <=24.0`
So could pick cost of `32`
For store we have:
https://godbolt.org/z/efh99d93b - for intels `Block RThroughput: <=48.0`; for ryzens, `Block RThroughput: <=32.0`
So we could pick cost of `48`.
I'm directly using the shuffling asm the llc produced,
without any manual fixups that may be needed
to ensure sequential execution.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D111942
A few more tuples are being queried after D111546. Might be good to model them,
They all require a lot of manual assembly surgery.
The only sched models that for cpu's that support avx2
but not avx512 are: haswell, broadwell, skylake, zen1-3
For load we have:
https://godbolt.org/z/YTeT9M7fW - for intels `Block RThroughput: <=212.0`; for ryzens, `Block RThroughput: <=64.0`
So could pick cost of `212`
For store we have:
https://godbolt.org/z/vc954KEGP - for intels `Block RThroughput: <=90.0`; for ryzens, `Block RThroughput: <=24.0`
So we could pick cost of `90`.
I'm directly using the shuffling asm the llc produced,
without any manual fixups that may be needed
to ensure sequential execution.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D111940
These cases use the same codegen as AVX2 (pshuflw/pshufd) for the sub-128bit vector deinterleaving, and unpcklqdq for v2i64.
It's going to take a while to add full interleaved cost coverage, but since these are the same for SSE2 -> AVX2 it should be an easy win.
Fixes PR47437
Differential Revision: https://reviews.llvm.org/D111938
And another attempt to start untangling this ball of threads around gather.
There's `TTI::prefersVectorizedAddressing()`hoop, which confusingly defaults to `true`,
which tells LV to try to vectorize the addresses that lead to loads,
but X86 generally can not deal with vectors of addresses,
the only instructions that support that are GATHER/SCATTER,
but even those aren't available until AVX2, and aren't really usable until AVX512.
This specializes the hook for X86, to return true only if we have AVX512 or AVX2 w/ fast gather.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D111546
While i've modelled most of the relevant tuples for AVX2,
that only covered fully-interleaved groups.
By definition, interleaving load of stride N means:
load N*VF elements, and shuffle them into N VF-sized vectors,
with 0'th vector containing elements `[0, VF)*stride + 0`,
and 1'th vector containing elements `[0, VF)*stride + 1`.
Example: https://godbolt.org/z/df561Me5E (i64 stride 4 vf 2 => cost 6)
Now, not fully interleaved load, is when not all of these vectors is demanded.
So at worst, we could just pretend that everything is demanded,
and discard the non-demanded vectors. What this means is that the cost
for not-fully-interleaved group should be not greater than the cost
for the same fully-interleaved group, but perhaps somewhat less.
Examples:
https://godbolt.org/z/a78dK5Geq (i64 stride 4 (indices 012u) vf 2 => cost 4)
https://godbolt.org/z/G91ceo8dM (i64 stride 4 (indices 01uu) vf 2 => cost 2)
https://godbolt.org/z/5joYob9rx (i64 stride 4 (indices 0uuu) vf 2 => cost 1)
As we have established over the course of last ~70 patches, (wow)
`BaseT::getInterleavedMemoryOpCos()` is absolutely bogus,
it is usually almost an order of magnitude overestimation,
so i would claim that we should at least use the hardcoded costs
of fully interleaved load groups.
We could go further and adjust them e.g. by the number of demanded indices,
but then i'm somewhat fearful of underestimating the cost.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D111174
This a NFC refactor patch to merge the AVX2 interleaved cost handling back into the getInterleavedMemoryOpCost base method - while getInterleavedMemoryOpCostAVX512 uses instruction and patterns very specific to AVX512+, much of the costs analysis for AVX2 can be reused for all SSE targets.
This is the first step towards improving SSE and AVX1 costs that will reuse the relevant AVX2 costs by splitting some of the tables - for instance AVX1 has very similar costs for most vXi64/vXf64 interleave patterns and many sub-128bit vector costs are the same all the way down to SSE2 (or at least SSSE3).
Differential Revision: https://reviews.llvm.org/D111822
Simon Pilgrim