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pospop's Introduction

High-performance vectorised positional popcount routines for Go
===============================================================

This repository contains implementations of the positional population
count functions for Go.  Details on the algorithms used will be
published in a future research paper.

To use this library, import it as follows:

    import "github.com/clausecker/pospop"

You can then count populations using the Count8, Count16, Count32,
and Count64 functions:

    var counts [8]int
    pospop.Count8(&counts, buf)

The positional population count for buf is added to the contents of
counts.

Supported Platforms
-------------------

The kernels works on a block size of 240 or 480 bytes (depending on
whether AVX2 is available or not).  A buffer size that is a multiple
of 480 bytes and at least 10 kB in size is recommended.

Implementations are provided for the following SIMD extensions:

 * AVX-512 F/BW (amd64)
 * AVX2 (amd64, 386)
 * SSE2 (amd64, 386)
 * NEON (arm64)
 * generic kernel (all architectures)

The three kernels for amd64 correspond to the v4, v3, and v1 values
of the upcoming GOAMD64 environment variable.

Due to some required improvements in the assembler, the NEON kernel will
only be available on Go 1.16 or newer.  When building with earlier
versions of the tool chain, only the generic kernel is available.

The library automatically chooses the fastest available kernel for
the system it is running on.

Performance
-----------

As all functions
(Count8, Count16, Count32, Count64) of one set are based on the
same kernel with a different accumulation function, they all perform
equally well.  This does not apply to the generic implementations
whose performance is therefore given for every function individually.

The following performance table is grouped by the instruction set used
and the architecture it runs on.  A buffer size of 100 kB was used to
find these results.


		amd64		386		arm64		arm
avx512		82.1 GB/s	---		---		---
avx2		34.8 GB/s	31.6 GB/s	---		---
sse2		16.0 GB/s	15.6 GB/s	---		---
neon		---		---		36.9 GB/s	---
generic8	1.02 GB/s	297 MB/s	1.68 GB/s	49.0 MB/s
generic16	1.71 GB/s	1.36 GB/s	3.03 GB/s	67.1 MB/s
generic32	2.66 GB/s	2.21 GB/s	3.83 GB/s	105 MB/s
generic64	3.43 GB/s	1.89 GB/s	6.56 GB/s	82.9 MB/s

The following systems were used for benchmarks, all using Go 1.16:

 * amd64, 386: Intel(R) Xeon(R) Gold 6138 CPU @ 2.00GHz
 * arm64: Apple M1
 * arm: ARM Cortex-A72 r0p3 (Raspberry Pi 4B)

Remaining Work
--------------

 * provide assembly kernels for arm, ppcle, and others
   (hardware donations appreciated for further targets)
 * provide variants of Count16, Count32, and Count64 working on byte
   arrays

(c) 2020--2024 Robert Clausecker <[email protected]>.  All Rights Reserved.

This code is published under a 2-clause BSD license.  See the file
COPYING for details.

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pospop's Issues

bit matrix transpositions slows down counting

Hi Robert,

Thanks for persisting optimizing this great package.

I found that bit matrix transpositions slows down counting (100K buffer and others) since d24d616b (Add new count8 variant using bit matrix transpositions). I know you're creating a general framework to port to other platform, a little performance reduction may be tolerated.

I add some tests with few bytes, which I use in my cases.

Current version: d6e39e5

BenchmarkCount8/avx2/32-16              74935256                15.5 ns/op      2066.51 MB/s
BenchmarkCount8/avx2/64-16              55956423                20.3 ns/op      3153.58 MB/s
BenchmarkCount8/avx2/128-16             37906530                29.8 ns/op      4302.12 MB/s
BenchmarkCount8/avx2/256-16             24502731                50.8 ns/op      5038.58 MB/s
BenchmarkCount8/avx2/512-16             31988312                37.8 ns/op      13560.77 MB/s
BenchmarkCount8/avx2/1000-16            20510130                61.9 ns/op      16148.71 MB/s
BenchmarkCount8/avx2/10000-16            2245747               524 ns/op        19087.36 MB/s
BenchmarkCount8/avx2/100000-16            248845              4595 ns/op        21761.87 MB/s

Starting using bit matrix transpositions: 41dbbc5 (speedup after d24d616b)

BenchmarkCount8/avx2/32-16              100472971               13.2 ns/op      2431.84 MB/s
BenchmarkCount8/avx2/64-16              66744648                17.9 ns/op      3568.20 MB/s
BenchmarkCount8/avx2/128-16             42810946                28.3 ns/op      4530.39 MB/s
BenchmarkCount8/avx2/256-16             20535319                56.7 ns/op      4516.74 MB/s
BenchmarkCount8/avx2/512-16             33010789                37.1 ns/op      13811.14 MB/s
BenchmarkCount8/avx2/1000-16            21271256                56.3 ns/op      17774.12 MB/s
BenchmarkCount8/avx2/10000-16            2517070               447 ns/op        22377.79 MB/s
BenchmarkCount8/avx2/100000-16            296733              4059 ns/op        24637.18 MB/s

Old but fast way:
677120e

BenchmarkCount8/avx2/32-16              181525946                7.16 ns/op     4466.72 MB/s
BenchmarkCount8/avx2/64-16              112528216               10.5 ns/op      6069.95 MB/s
BenchmarkCount8/avx2/128-16             63801217                18.7 ns/op      6836.36 MB/s
BenchmarkCount8/avx2/256-16             40247318                29.1 ns/op      8795.27 MB/s
BenchmarkCount8/avx2/512-16             38962676                28.7 ns/op      17869.65 MB/s
BenchmarkCount8/avx2/1000-16            20517376                57.8 ns/op      17289.99 MB/s
BenchmarkCount8/avx2/10000-16            2644093               432 ns/op        23135.55 MB/s
BenchmarkCount8/avx2/100000-16            295675              3913 ns/op        25554.00 MB/s

Eliminate temporary variables from the CSA operation

Consider:

// B:A = A+B+C
#define CSA(A, B, C, D) \
	MOVOA A, D \
	PAND B, D \
	PXOR B, A \
	MOVOA A, B \
	PAND C, B \
	PXOR C, A \
	POR D, B

vs

// B:A = A+B+C
#define CSA(A, B, C) \
	PXOR C, B \ 
	PXOR A, C \
	PXOR B, A \
	POR  C, B \
	PXOR A, B

The C input must be ready 1 cycle earlier.

This is mainly for SSE2 platforms. AVX2/NEON instructions have non-destructive 3-operand forms.

Some architectures have "free" "mov elimination" which makes this change hard to benchmark.

IIRC, a problem I was having before was about how the compiler was merging a load with an xor instruction...

xor r1, [mem]

vs

load r2, [mem]
xor r1, r2

Not sure if this would be an issue with GoLang Assembly.

======

This issue is not important, feel free to close this out, just one of my pet projects.

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