This patch adds an initial ShuffleVectorInst::isInsertSubvectorMask helper to recognize 2-op shuffles where the lowest elements of one of the sources are being inserted into the "in-place" other operand, this includes "concat_vectors" patterns as can be seen in the Arm shuffle cost changes. This also helped fix a x86 issue with irregular/length-changing SK_InsertSubvector costs - I'm hoping this will help with D107188
This doesn't currently attempt to work with 1-op shuffles that could either be a "widening" shuffle or a self-insertion.
The self-insertion case is tricky, but we currently always match this with the existing SK_PermuteSingleSrc logic.
The widening case will be addressed in a follow up patch that treats the cost as 0.
Masks with a high number of undef elts will still struggle to match optimal subvector widths - its currently bounded by minimum-width possible insertion, whilst some cases would benefit from wider (pow2?) subvectors.
Differential Revision: https://reviews.llvm.org/D107228
I have added a new FastMathFlags parameter to getArithmeticReductionCost
to indicate what type of reduction we are performing:
1. Tree-wise. This is the typical fast-math reduction that involves
continually splitting a vector up into halves and adding each
half together until we get a scalar result. This is the default
behaviour for integers, whereas for floating point we only do this
if reassociation is allowed.
2. Ordered. This now allows us to estimate the cost of performing
a strict vector reduction by treating it as a series of scalar
operations in lane order. This is the case when FP reassociation
is not permitted. For scalable vectors this is more difficult
because at compile time we do not know how many lanes there are,
and so we use the worst case maximum vscale value.
I have also fixed getTypeBasedIntrinsicInstrCost to pass in the
FastMathFlags, which meant fixing up some X86 tests where we always
assumed the vector.reduce.fadd/mul intrinsics were 'fast'.
New tests have been added here:
Analysis/CostModel/AArch64/reduce-fadd.ll
Analysis/CostModel/AArch64/sve-intrinsics.ll
Transforms/LoopVectorize/AArch64/strict-fadd-cost.ll
Transforms/LoopVectorize/AArch64/sve-strict-fadd-cost.ll
Differential Revision: https://reviews.llvm.org/D105432
Update shl/lshr/ashr costs based on the worst case costs from the script in D103695 - many of the 128-bit shifts (usually where integer multiplies aren't used) have similar behaviour to AVX1 so we can merge them.
We know that "CVTTPS2SI" returns 0x80000000 for out of range inputs (and for FP_TO_UINT, negative float values are undefined). We can use this to make unsigned conversions from vXf32 to vXi32 more efficient, particularly on targets without blend using the following logic:
small := CVTTPS2SI(x);
fp_to_ui(x) := small | (CVTTPS2SI(x - 2^31) & ARITHMETIC_RIGHT_SHIFT(small, 31))
Even on targets where "PBLENDVPS"/"PBLENDVB" exists, it is often a latency 2, low throughput instruction so this logic is applied there too (in particular for AVX2 also). It furthermore gets rid of one high latency floating point comparison in the previous lowering.
@TomHender checked the correctness of this for all possible floats between -1 and 2^32 (both ends excluded).
Original Patch by @TomHender (Tom Hender)
Differential Revision: https://reviews.llvm.org/D89697
Update (mainly) vXf32/vXf64 -> vXi8/vXi16 fptosi/fptoui costs based on the worst case costs from the script in D103695.
Move to using legalized types wherever possible, which allows us to prune the cost tables.
Update truncation costs based on the worst case costs from the script in D103695.
Move to using legalized types wherever possible, which allows us to prune the cost tables.
This patch removes the IsPairwiseForm flag from the Reduction Cost TTI
hooks, along with some accompanying code for pattern matching reductions
from trees starting at extract elements. IsPairWise is now assumed to be
false, which was the predominant way that the value was used from both
the Loop and SLP vectorizers. Since the adjustments such as D93860, the
SLP vectorizer has not relied upon this distinction between paiwise and
non-pairwise reductions.
This also removes some code that was detecting reductions trees starting
from extract elements inside the costmodel. This case was
double-counting costs though, adding the individual costs on the
individual instruction _and_ the total cost of the reduction. Removing
it changes the costs in llvm/test/Analysis/CostModel/X86/reduction.ll to
not double count. The cost of reduction intrinsics is still tested
through the various tests in
llvm/test/Analysis/CostModel/X86/reduce-xyz.ll.
Differential Revision: https://reviews.llvm.org/D105484
Revived D101297 in its original form + added some changes in X86
legalization cehcking for masked gathers.
This solution is the most stable and the most correct one. We have to
check the legality before trying to build the masked gather in SLP.
Without this check we have incorrect cost (for SLP) in case if the masked gather
is not legal/slower than the gather. And we're missing some
vectorization opportunities.
This can be fixed in the cost model, but in this case we need to add
special checks for the cost of GEPs for ScatterVectorize node, add
special check for small trees, etc., i.e. there are a lot of corner
cases here and there, which insrease code base and make it harder to
maintain the code.
> Can't we rely on cost model to deal with this? This can be profitable for futher vectorization, when we can start from such gather loads as seed.
The question from D101297. Actually, no, it can't. Actually, simple
gather may give us better result, especially after we started
vectorization of insertelements. Plus, like I said before, the cost for
non-legal masked gathers leads to missed vectorization opportunities.
Differential Revision: https://reviews.llvm.org/D105042
Update costs based on the worst case costs from the script in D103695.
Move to using legalized types wherever possible, which allows us to prune the cost tables.
Update (mainly) vXi8/vXi16 -> vXf32/vXf64 sitofp/uitofp costs based on the worst case costs from the script in D103695.
Move to using legalized types wherever possible, which allows us to prune the cost tables.
Provide a generic fallback that performs the fptosi to i32 types, then truncates to sub-i32 scalars.
These numbers can be tweaked for specific sse levels, but we should get the default handling in place first.
Provide a generic fallback that extends sub-i32 scalars before using the existing sitofp instructions.
These numbers can be tweaked for specific sse levels, but we should get the default handling in place first.
We get the extension for free for non-vector loads.
Update v4i64 -> v4f32/v4f64 uitofp costs based on the worst case costs from the script in D103695.
Fixes a few regressions before we start adding AVX costs for legalized types.
Building on rG2a1ef8784ad9a, adjust the SSE cost tables to use the legalized types based on the worst case costs from the script in D103695.
To account for different numbers of src/dst legalized type registers we must scale the cost by maximum of the src/dst, not just use src
Move the (SSE-only) generic, legalized type conversion matching after the specific,custom conversion cases, allowing us to properly provide cost overrides.
The next step will be to clean up some of the weird existing costs and then to enable AVX+ legalized costs, which will let us strip out a lot of the cost tables entries.
Based off the worse case numbers generated by D103695, the AVX1/2/512 sitofp/uitofp/fptosi/fptoui costs were higher than necessary (based off instruction counts instead of actual throughput).
The SSE costs still need further fixes, but I hit an issue with the order in which SSE costs are checked - we need to check CUSTOM costs (with non-legal types) first, and then fallback to LEGALIZED types. I'm looking at this now, and this should let us start thinning out a lot of the duplicates in the costs tables.
Then we can finally start work on vXi64 / vXi16 / vXi8 / vXi1 integers, which should let us look at sub-128-bit vectorization (D103925).
Based off the worse case numbers generated by D103695, we were overestimating the cost of a number of vector truncations:
AVX2: v2i32->v2i8, v2i64->v2i16 + v4i64->v4i32
AVX1: v2i32->v2i8, v4i64->v4i16 + v16i16->v16i8
Once we have a working set of conversion costs, the intention is to cleanup the tables and use legalized types a lot more to reduce the number of entries we currently have.
Determined from llvm-mca analysis (btver2 vs bdver2 vs sandybridge), the split+extends+concat sequence on AVX1 capable targets are cheaper than the #ops that the cost was previously based on.
The SkylakeServer model (and later IceLake/TigerLake targets according to Agner) have the PMOV truncations as uops=2, rthroughput=2 instructions.
Noticed while trying to reduce the diffs between cost tables and llvm-mca analysis.
Determined from llvm-mca analysis, AVX1 capable targets have a higher throughput for VPBLENDVB and shuffle ops, making it cheaper to perform shift+shuffle/select shift patterns.
rG1ad4f887bd7692a9e63fb42586f0ece366f2fe01 incorrectly assumed that vXi64 non-uniform shifts were slow like vXi32 were - but llvm-mca (+Agner) both confirm that Haswell/Broadwell are full rate.
Determined from llvm-mca analysis, AVX2+ capable targets have a higher throughput for VPBLENDVB and VPMOVZX ops, making it cheaper to perform shift+select patterns for vXi8 shifts or extend/shift/truncate for vXi16 shifts. Similarly AVX512BW can perform vXi8 as extend/shift/truncate patterns.
This follows in steps of similar `getMemoryOpCost()` changes, D100099/D100684.
Intel SDM, `VPMASKMOV — Conditional SIMD Integer Packed Loads and Stores`:
```
Faults occur only due to mask-bit required memory accesses that caused the faults. Faults will not occur due to
referencing any memory location if the corresponding mask bit for that memory location is 0. For example, no
faults will be detected if the mask bits are all zero.
```
I.e., if mask is all-zeros, any address is fine.
Masked load/store's prime use-case is e.g. tail masking the loop remainder,
where for the last iteration, only first some few elements of a vector exist.
So much similarly, i don't see why must we scalarize non-power-of-two vectors,
iff the element type is something we can masked- store/load.
We simply need to legalize it, widen the mask, and be done with it.
And we even already count the cost of widening the mask.
Reviewed By: ABataev
Differential Revision: https://reviews.llvm.org/D102990
By llvm-mca analysis, Haswell/Broadwell has a non-uniform vector shift recip-throughput cost of the AVX2 targets at 2 for both 128 and 256-bit vectors - XOP capable targets have better 128-bit vector shifts so improve the fallback in those cases.
By llvm-mca analysis, Haswell/Broadwell has the worst v4i64 recip-throughput cost of the AVX2 targets at 6 (vs the currently used cost of 8). Similarly SkylakeServer (our only AVX512 target model) implements PMULLQ with an average cost of 1.5 (rounded up to 2.0), and the PMULUDQ-sequence (without AVX512DQ) as a cost of 6.
Based on worst case of sandybridge (vs btver2 + bdver2) llvm-mca analysis - which is a lot less than what we were predicting (I think based off total uop count).
BTVER2 has a 2 cycle throughput for v4i32 multiplies (same as SSE41 targets), which is only partially hidden by the subvector extracts/insert when splitting v8i32.
Now that getMemoryOpCost() correctly handles all the vector variants,
we should no longer hand-roll our own version of it, but use it directly.
The AVX512 variant probably needs a similar change,
but there it is less obvious.
This was initially landed in 69ed93a435,
but was reverted in 6b95fd199d
because the patch it depends on was reverted.
Instead of handling power-of-two sized vector chunks,
try handling the large vector in a stream mode,
decreasing the operational vector size
once it no longer works for the elements left to process.
Notably, this improves costs for overaligned loads - loading padding is fine.
This more directly tracks when we need to insert/extract the YMM/XMM subvector,
some costs fluctuate because of that.
This was initially landed in c02476f315,
but reverted in 5fddc3312b,
because the code made some very optimistic assumptions about invariants
that didn't hold in practice.
Reviewed By: RKSimon, ABataev
Differential Revision: https://reviews.llvm.org/D100684
BTVER2 has a weaker f64 multiplier that other AVX1-era targets, so we need to bump the worst case cost slightly - llvm-mca reports the new vectorization in simplebb is beneficial on btver2, bdver2 and sandybridge AVX1 targets
Simon Pilgrim