This is follow up of D107082, which enable vector support according to psABI.
Reviewed By: skan
Differential Revision: https://reviews.llvm.org/D127982
During the reordering transformation we should try to avoid reordering bundles
like fadd,fsub because this may block them being matched into a single vector
instruction in x86.
We do this by checking if a TreeEntry is such a pattern and adding it to the
list of TreeEntries with orders that need to be considered.
Differential Revision: https://reviews.llvm.org/D125712
We were using the default getScalarizationOverhead expansion for extraction costs, which adds up all the individual element extraction costs.
This is fine for 128-bit vectors, but for 256/512-bit vectors each element extraction also has to account for extracting the upper 128-bit subvector extraction before it can handle the element. For scalarization costs we only need to extract each demanded subvector once.
Differential Revision: https://reviews.llvm.org/D125527
Most clients only used these methods because they wanted to be able to
extend or truncate to the same bit width (which is a no-op). Now that
the standard zext, sext and trunc allow this, there is no reason to use
the OrSelf versions.
The OrSelf versions additionally have the strange behaviour of allowing
extending to a *smaller* width, or truncating to a *larger* width, which
are also treated as no-ops. A small amount of client code relied on this
(ConstantRange::castOp and MicrosoftCXXNameMangler::mangleNumber) and
needed rewriting.
Differential Revision: https://reviews.llvm.org/D125557
Based off the script from D103695, on AVX1, Jaguar/Bulldozer both have low throughput for ymm select patterns (BLENDV + OR(AND,ANDN))), and even on AVX2 Haswell still struggles with BLENDV ops
We can quickly extract multiple elements of a bool vector using MOVMSK ops - since we don't know what generated the vXi1, I've been optimistic and assumed we can use PMOVMSKB to extract the maximum number of bools with a single op.
The MOVMSK pattern isn't great for extract+insert round trips as vXi1 type legalization can interfere with this a lot - so this relies on us remaining good at using getScalarizationOverhead properly (and tagging both Insert and Extract modes) for those round trip cases.
The AVX512 KMOV codegen for bool extraction is a bit of a mess so for now I've not included that - the per-element cost is a lot more accurate for current codegen.
If the legalized src/dst types are the same, assume the "truncation" is free.
This fixes some edge cases such as mul lo/hi ops and bool vectors which will get legalized back to legal vector widths
Based off the script from D103695, we were exaggerating the cost of the OR(AND(X,M),AND(Y,~M)) expansion using instruction count instead of effective throughput
Need to normalizize the mask to avoid possible crashes during attempts
to estimate cost of the very long shuffles with non-power-2 number of
elements in masks.
Introduced masks where they are not added and improved target dependent
cost models to avoid returning of the incorrect cost results after
adding masks.
Differential Revision: https://reviews.llvm.org/D100486
Introduced masks where they are not added and improved target dependent
cost models to avoid returning of the incorrect cost results after
adding masks.
Differential Revision: https://reviews.llvm.org/D100486
Before this patch `Args` was used to pass a broadcat's arguments by SLP.
This patch changes this. `Args` is now used for passing the operands of
the shuffle.
Differential Revision: https://reviews.llvm.org/D124202
Based off the script from D103695, we were exaggerating the cost of the v2i64 comparison expansion using instruction count instead of effective throughput
Splat loads are inexpensive in X86. For a 2-lane vector we need just one
instruction: `movddup (%reg), xmm0`. Using the standard Splat score leads
to worse code. This patch adds a new score dedicated for splat loads.
Please note that a splat is usually three IR instructions:
- It is usually a load and 2 inserts:
%ld = load double, double* %gep
%ins1 = insertelement <2 x double> poison, double %ld, i32 0
%ins2 = insertelement <2 x double> %ins1, double %ld, i32 1
- But it can also be a load, an insert and a shuffle:
%ld = load double, double* %gep
%ins = insertelement <2 x double> poison, double %ld, i32 0
%shf = shufflevector <2 x double> %ins, <2 x double> poison, <2 x i32> zeroinitializer
Because of this some of the lit tests contain more IR instructions.
Differential Revision: https://reviews.llvm.org/D121354
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
Phoebe Wang