shared float temp[64];
+layout(std430, binding = 9) buffer layoutName
+{
+ uint dist[4][256];
+};
+
+#define MAPPING(s0, s1, s2, s3, s4, s5, s6, s7) ((s0) | (s1 << 2) | (s2 << 4) | (s3 << 6) | (s4 << 8) | (s5 << 10) | (s6 << 12) | (s7 << 14))
+
+const uint luma_mapping[8] = {
+ MAPPING(0, 0, 1, 1, 2, 2, 3, 3),
+ MAPPING(0, 0, 1, 2, 2, 2, 3, 3),
+ MAPPING(1, 1, 2, 2, 2, 3, 3, 3),
+ MAPPING(1, 1, 2, 2, 2, 3, 3, 3),
+ MAPPING(1, 2, 2, 2, 2, 3, 3, 3),
+ MAPPING(2, 2, 2, 2, 3, 3, 3, 3),
+ MAPPING(2, 2, 3, 3, 3, 3, 3, 3),
+ MAPPING(3, 3, 3, 3, 3, 3, 3, 3),
+};
+
+// Scale factors; 1.0 / (sqrt(2.0) * cos(k * M_PI / 16.0)), except for the first which is 1.
+const float sf[8] = {
+ 1.0, 0.7209598220069479, 0.765366864730180, 0.8504300947672564,
+ 1.0, 1.2727585805728336, 1.847759065022573, 3.6245097854115502
+};
+
const float W[64] = {
8, 16, 19, 22, 26, 27, 29, 34,
16, 16, 22, 24, 27, 29, 34, 37,
26, 27, 29, 34, 38, 46, 56, 69,
27, 29, 35, 38, 46, 56, 69, 83
};
-const float S = 4.0; // whatever?
+const float S = 4.0 * 0.5; // whatever?
// NOTE: Contains factors to counteract the scaling in the DCT implementation.
+#define QM(x, y) (sf[x] * sf[y] / (W[y*8 + x] * S))
const float quant_matrix[64] = {
- 1.0 / 64.0, 1.0 / (W[ 1] * S), 1.0 / (W[ 2] * S), 1.0 / (W[ 3] * S), 1.0 / (W[ 4] * S), 1.0 / (W[ 5] * S), 1.0 / (W[ 6] * S), 1.0 / (W[ 7] * S),
- 1.0 / (W[ 8] * S), 2.0 / (W[ 9] * S), 2.0 / (W[10] * S), 2.0 / (W[11] * S), 2.0 / (W[12] * S), 2.0 / (W[13] * S), 2.0 / (W[14] * S), 2.0 / (W[15] * S),
- 1.0 / (W[16] * S), 2.0 / (W[17] * S), 2.0 / (W[18] * S), 2.0 / (W[19] * S), 2.0 / (W[20] * S), 2.0 / (W[21] * S), 2.0 / (W[22] * S), 2.0 / (W[23] * S),
- 1.0 / (W[24] * S), 2.0 / (W[25] * S), 2.0 / (W[26] * S), 2.0 / (W[27] * S), 2.0 / (W[28] * S), 2.0 / (W[29] * S), 2.0 / (W[30] * S), 2.0 / (W[31] * S),
- 1.0 / (W[32] * S), 2.0 / (W[33] * S), 2.0 / (W[34] * S), 2.0 / (W[35] * S), 2.0 / (W[36] * S), 2.0 / (W[37] * S), 2.0 / (W[38] * S), 2.0 / (W[39] * S),
- 1.0 / (W[40] * S), 2.0 / (W[41] * S), 2.0 / (W[42] * S), 2.0 / (W[43] * S), 2.0 / (W[44] * S), 2.0 / (W[45] * S), 2.0 / (W[46] * S), 2.0 / (W[47] * S),
- 1.0 / (W[48] * S), 2.0 / (W[49] * S), 2.0 / (W[50] * S), 2.0 / (W[51] * S), 2.0 / (W[52] * S), 2.0 / (W[53] * S), 2.0 / (W[54] * S), 2.0 / (W[55] * S),
- 1.0 / (W[56] * S), 2.0 / (W[57] * S), 2.0 / (W[58] * S), 2.0 / (W[59] * S), 2.0 / (W[60] * S), 2.0 / (W[61] * S), 2.0 / (W[62] * S), 2.0 / (W[63] * S)
+ 1.0 / 64.0, QM(1, 0), QM(2, 0), QM(3, 0), QM(4, 0), QM(5, 0), QM(6, 0), QM(7, 0),
+ QM(0, 1), QM(1, 1), QM(2, 1), QM(3, 1), QM(4, 1), QM(5, 1), QM(6, 1), QM(7, 1),
+ QM(0, 2), QM(1, 2), QM(2, 2), QM(3, 2), QM(4, 2), QM(5, 2), QM(6, 2), QM(7, 2),
+ QM(0, 3), QM(1, 3), QM(2, 3), QM(3, 3), QM(4, 3), QM(5, 3), QM(6, 3), QM(7, 3),
+ QM(0, 4), QM(1, 4), QM(2, 4), QM(3, 4), QM(4, 4), QM(5, 4), QM(6, 4), QM(7, 4),
+ QM(0, 5), QM(1, 5), QM(2, 5), QM(3, 5), QM(4, 5), QM(5, 5), QM(6, 5), QM(7, 5),
+ QM(0, 6), QM(1, 6), QM(2, 6), QM(3, 6), QM(4, 6), QM(5, 6), QM(6, 6), QM(7, 6),
+ QM(0, 7), QM(1, 7), QM(2, 7), QM(3, 7), QM(4, 7), QM(5, 7), QM(6, 7), QM(7, 7)
};
// Clamp and pack a 9-bit and a 7-bit signed value into a 16-bit word.
return (uint(clamp(v9, -256, 255)) & 0x1ffu) | ((uint(clamp(v7, -64, 63)) & 0x7fu) << 9);
}
-// Scaled 1D DCT. y0 output is scaled by 8, everything else is scaled by 16.
+// Scaled 1D DCT (AA&N). y0 is correctly scaled, all other y_k are scaled by sqrt(2) cos(k * Pi / 16).
void dct_1d(inout float y0, inout float y1, inout float y2, inout float y3, inout float y4, inout float y5, inout float y6, inout float y7)
{
const float a1 = 0.7071067811865474; // sqrt(2)
y7 = p5_5 - p4_6;
y3 = p5_7 - p4_4;
}
+
void main()
{
uint x = 8 * gl_WorkGroupID.x;
imageStore(ac2_ac5_tex, ivec2(sx, y + n), uvec4(pack_9_7(c2, c5), 0, 0, 0));
imageStore(ac3_tex, ivec2(sx, y + n), ivec4(c3, 0, 0, 0));
imageStore(ac4_tex, ivec2(sx, y + n), ivec4(c4, 0, 0, 0));
+
+ // Count frequencies, but only for every 8th block or so, randomly selected.
+ uint wg_index = gl_WorkGroupID.y * gl_WorkGroupSize.x + gl_WorkGroupID.x;
+ if ((wg_index * 0x9E3779B9u) >> 29 == 0) { // Fibonacci hashing, essentially a PRNG in this context.
+ c0 = min(abs(c0), 255);
+ c1 = min(abs(c1), 255);
+ c2 = min(abs(c2), 255);
+ c3 = min(abs(c3), 255);
+ c4 = min(abs(c4), 255);
+ c5 = min(abs(c5), 255);
+ c6 = min(abs(c6), 255);
+ c7 = min(abs(c7), 255);
+
+ // Spread out the most popular elements among the cache lines by reversing the bits
+ // of the index, reducing false sharing.
+ c0 = bitfieldReverse(c0) >> 24;
+ c1 = bitfieldReverse(c1) >> 24;
+ c2 = bitfieldReverse(c2) >> 24;
+ c3 = bitfieldReverse(c3) >> 24;
+ c4 = bitfieldReverse(c4) >> 24;
+ c5 = bitfieldReverse(c5) >> 24;
+ c6 = bitfieldReverse(c6) >> 24;
+ c7 = bitfieldReverse(c7) >> 24;
+
+ uint m = luma_mapping[n];
+ atomicAdd(dist[bitfieldExtract(m, 0, 2)][c0], 1);
+ atomicAdd(dist[bitfieldExtract(m, 2, 2)][c1], 1);
+ atomicAdd(dist[bitfieldExtract(m, 4, 2)][c2], 1);
+ atomicAdd(dist[bitfieldExtract(m, 6, 2)][c3], 1);
+ atomicAdd(dist[bitfieldExtract(m, 8, 2)][c4], 1);
+ atomicAdd(dist[bitfieldExtract(m, 10, 2)][c5], 1);
+ atomicAdd(dist[bitfieldExtract(m, 12, 2)][c6], 1);
+ atomicAdd(dist[bitfieldExtract(m, 14, 2)][c7], 1);
+ }
}
projects / narabu / blobdiff