I have a problem with converting the image data stored in byte[] array
to grayscale. I want to use vector SIMD operations because in future a need to write ASM and C++ DLL files to measure operations time.
When I read about SIMD I found that SSE command is operation on 128-bit registers so there is a problem because I need to convert my byte[] array
into few Vector<T>
stored into List<T>.
Image is four channels RGBA JPEG so I need also to know how to create vectors with R, G, B data based on single 128-bit Vector<T>
. After that, I can use the Grayscale algorithm
fY(R, G, B) = R x 0.29891 + G x 0.58661 + B x 0.11448
All in all the questions are:
byte[] array
into 128-bit registers Vector<T>
.Vector<T>
the R, G, B value to multiply it and copy to source Vector.It requires System.Runtime.Intrinsics.Experimental.dll and unsafe, but it’s relatively straightforward, and probably fast enough for many practical applications.
/// <summary>Load 4 pixels of RGB</summary>
static unsafe Vector128<int> load4( byte* src )
{
return Sse2.LoadVector128( (int*)src );
}
/// <summary>Pack red channel of 8 pixels into ushort values in [ 0xFF00 .. 0 ] interval</summary>
static Vector128<ushort> packRed( Vector128<int> a, Vector128<int> b )
{
Vector128<int> mask = Vector128.Create( 0xFF );
a = Sse2.And( a, mask );
b = Sse2.And( b, mask );
return Sse2.ShiftLeftLogical128BitLane( Sse41.PackUnsignedSaturate( a, b ), 1 );
}
/// <summary>Pack green channel of 8 pixels into ushort values in [ 0xFF00 .. 0 ] interval</summary>
static Vector128<ushort> packGreen( Vector128<int> a, Vector128<int> b )
{
Vector128<int> mask = Vector128.Create( 0xFF00 );
a = Sse2.And( a, mask );
b = Sse2.And( b, mask );
return Sse41.PackUnsignedSaturate( a, b );
}
/// <summary>Pack blue channel of 8 pixels into ushort values in [ 0xFF00 .. 0 ] interval</summary>
static Vector128<ushort> packBlue( Vector128<int> a, Vector128<int> b )
{
a = Sse2.ShiftRightLogical128BitLane( a, 1 );
b = Sse2.ShiftRightLogical128BitLane( b, 1 );
Vector128<int> mask = Vector128.Create( 0xFF00 );
a = Sse2.And( a, mask );
b = Sse2.And( b, mask );
return Sse41.PackUnsignedSaturate( a, b );
}
/// <summary>Load 8 pixels, split into RGB channels.</summary>
static unsafe void loadRgb( byte* src, out Vector128<ushort> red, out Vector128<ushort> green, out Vector128<ushort> blue )
{
var a = load4( src );
var b = load4( src + 16 );
red = packRed( a, b );
green = packGreen( a, b );
blue = packBlue( a, b );
}
const ushort mulRed = (ushort)( 0.29891 * 0x10000 );
const ushort mulGreen = (ushort)( 0.58661 * 0x10000 );
const ushort mulBlue = (ushort)( 0.11448 * 0x10000 );
/// <summary>Compute brightness of 8 pixels</summary>
static Vector128<short> brightness( Vector128<ushort> r, Vector128<ushort> g, Vector128<ushort> b )
{
r = Sse2.MultiplyHigh( r, Vector128.Create( mulRed ) );
g = Sse2.MultiplyHigh( g, Vector128.Create( mulGreen ) );
b = Sse2.MultiplyHigh( b, Vector128.Create( mulBlue ) );
var result = Sse2.AddSaturate( Sse2.AddSaturate( r, g ), b );
return Vector128.AsInt16( Sse2.ShiftRightLogical( result, 8 ) );
}
/// <summary>Convert buffer from RGBA to grayscale.</summary>
/// <remarks>
/// <para>If your image has line paddings, you'll want to call this once per line, not for the complete image.</para>
/// <para>If width of the image is not multiple of 16 pixels, you'll need to do more work to handle the last few pixels of every line.</para>
/// </remarks>
static unsafe void convertToGrayscale( byte* src, byte* dst, int count )
{
byte* srcEnd = src + count * 4;
while( src < srcEnd )
{
loadRgb( src, out var r, out var g, out var b );
var low = brightness( r, g, b );
loadRgb( src + 32, out r, out g, out b );
var hi = brightness( r, g, b );
var bytes = Sse2.PackUnsignedSaturate( low, hi );
Sse2.Store( dst, bytes );
src += 64;
dst += 16;
}
}
However, equivalent C++ implementation would be faster. C# did a decent job inlining these functions i.e. convertToGrayscale
contains no function calls.
But the code of that function is far from optimal. The .NET failed to propagate constants, for the magic numbers it emitted code like this inside the loop:
mov r8d,962Ch
vmovd xmm1,r8d
vpbroadcastw xmm1,xmm1
The generated code only uses 6 out of 16 registers. There’re enough available registers for all the magic numbers involved.
Also .NET emits many redundant instructions which just shuffle data around:
vmovaps xmm2, xmm0
vmovaps xmm3, xmm1
With a little less precision than the other answer, 7 bit fixed point scales could be used instead of 16 bit fixed point scales, enabling the use of PMADDUBSW. That also does not require any shuffling before the multiply. Then PMADDWD can be abused as a pairwise horizontal addition, so there is still no shuffling after the multiplication. That has a relatively bad latency, but that would be hidden by instruction level parallelism, the CPU isn't just go to sit there and do nothing.
Since this code is supposed to write to a different buffer than it reads from, it is safe to use the "step back and do a single unaligned iteration"-trick to handle the last block of pixels if there are fewer than 16 of them left.
I changed the blue weight to 128 * 0.118 because then it comes out as 15, which is closer to 14.65344 (the unrounded scaled weight). Also, letting it round down to 14 makes the total weight 127, which would mean that later dividing by 128 loses brightness.
All combined,
static unsafe void convertToGrayscale(byte* src, byte* dst, int count)
{
int countMain = count & -16;
byte* srcEnd = src + countMain * 4;
byte* srcRealEnd = src + count * 4;
byte* dstRealEnd = dst + count;
sbyte scaleR = (sbyte)(128 * 0.29891);
sbyte scaleG = (sbyte)(128 * 0.58661);
sbyte scaleB = (sbyte)(128 * 0.118);
Vector128<sbyte> scales = Vector128.Create(scaleR, scaleG, scaleB, 0, scaleR, scaleG, scaleB, 0, scaleR, scaleG, scaleB, 0, scaleR, scaleG, scaleB, 0);
Vector128<short> ones = Vector128.Create((short)1);
do
{
while (src < srcEnd)
{
var block0 = Sse2.LoadVector128(src);
var block1 = Sse2.LoadVector128(src + 16);
var block2 = Sse2.LoadVector128(src + 32);
var block3 = Sse2.LoadVector128(src + 48);
var scaled0 = Ssse3.MultiplyAddAdjacent(block0, scales);
var scaled1 = Ssse3.MultiplyAddAdjacent(block1, scales);
var scaled2 = Ssse3.MultiplyAddAdjacent(block2, scales);
var scaled3 = Ssse3.MultiplyAddAdjacent(block3, scales);
var t0 = Sse2.MultiplyAddAdjacent(scaled0, ones);
var t1 = Sse2.MultiplyAddAdjacent(scaled1, ones);
var t2 = Sse2.MultiplyAddAdjacent(scaled2, ones);
var t3 = Sse2.MultiplyAddAdjacent(scaled3, ones);
var c01 = Sse2.PackSignedSaturate(t0, t1);
c01 = Sse2.ShiftRightLogical(c01, 7);
var c23 = Sse2.PackSignedSaturate(t2, t3);
c23 = Sse2.ShiftRightLogical(c23, 7);
var c0123 = Sse2.PackUnsignedSaturate(c01, c23);
Sse2.Store(dst, c0123);
src += 64;
dst += 16;
}
// hack to re-use the main loop for the "tail"
if (src == srcRealEnd)
break;
srcEnd = srcRealEnd;
src = srcRealEnd - 64;
dst = dstRealEnd - 16;
} while (true);
}
On my PC, this is about twice as fast as the solution based on PMULHUW.
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