Add native ARM64 popcount for sizeof(T) above 1 to TensorPrimitives

[neon-sunset]

I validated that the codegen before and after the change for sizeof(T) is 1 in InvokeSpanIntoSpan.Vectorized128 is identical so whatever difference there is, it is likely the noise (from non-temporal stores? I found the numbers unstable even at 256KiB of data).

For sizeof(T) is 8 I also tested Vector128 into Vector64x2 with vaddvq_u32and back into V128 but it was slower than continuing to bruteforce.

Environment:

BenchmarkDotNet v0.13.12, macOS Sonoma 14.5 (23F79) [Darwin 23.5.0]
Apple M1 Pro, 1 CPU, 8 logical and 8 physical cores
.NET SDK 9.0.100-preview.6.24307.18
  [Host]     : .NET 9.0.0 (9.0.24.30702), Arm64 RyuJIT AdvSIMD
  DefaultJob : .NET 9.0.0 (9.0.24.30702), Arm64 RyuJIT AdvSIMD

Benchmark:

public class TensorPopCount
{
    const int Length = 262_144;
    static readonly byte[] sink = new byte[Length];
    static readonly byte[] bytes = Enumerable.Repeat((byte)0b10101010, Length).ToArray();
    static readonly ushort[] shorts = MemoryMarshal.Cast<byte, ushort>(bytes).ToArray();
    static readonly uint[] ints = MemoryMarshal.Cast<byte, uint>(bytes).ToArray();
    static readonly ulong[] longs = MemoryMarshal.Cast<byte, ulong>(bytes).ToArray();

    [Benchmark]
    public void Bytes() => TensorPrimitives.PopCount<byte>(bytes, sink);

    [Benchmark]
    public void Shorts() => TensorPrimitives.PopCount(shorts, MemoryMarshal.Cast<byte, ushort>(sink));

    [Benchmark]
    public void Ints() => TensorPrimitives.PopCount(ints, MemoryMarshal.Cast<byte, uint>(sink));

    [Benchmark]
    public void Longs() => TensorPrimitives.PopCount(longs, MemoryMarshal.Cast<byte, ulong>(sink));
}

Current:

Method	Mean	Error	StdDev
Bytes	5.689 us	0.0738 us	0.0690 us
Shorts	19.246 us	0.0215 us	0.0190 us
Ints	19.368 us	0.0264 us	0.0221 us
Longs	71.893 us	0.1026 us	0.0960 us

PR:

Method	Mean	Error	StdDev
Bytes	5.809 us	0.1144 us	0.1447 us
Shorts	3.660 us	0.0237 us	0.0185 us
Ints	4.297 us	0.0463 us	0.0387 us
Longs	5.360 us	0.0150 us	0.0117 us

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[stephentoub]

LGTM. Thanks. @tannergooding ?