const int il = tid/8; // 0...3
const int ib = tid%8; // 0...7
dst_t * y = yy + i*QK_K + 32*ib + 8*il;
- const float d = (float)x[i].d * (2*((x[i].qh[ib] >> 12) & 0xf) + 1);
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
- int grid32[2]; const int8_t * q = (const int8_t *)grid32;
- grid32[0] = *((const int *)(iq1s_grid_gpu + (x[i].qs[4*ib+il] | (((x[i].qh[ib] >> 3*il) & 7) << 8))));
- grid32[1] = __vsub4((grid32[0] >> 4) & 0x0f0f0f0f, 0x01010101);
- grid32[0] = __vsub4(grid32[0] & 0x0f0f0f0f, 0x01010101);
+ const float delta = x[i].qh[ib] & 0x8000 ? -1 - IQ1S_DELTA : -1 + IQ1S_DELTA;
+ const float d = (float)x[i].d * (2*((x[i].qh[ib] >> 12) & 7) + 1);
+ uint32_t grid32[2]; const int8_t * q = (const int8_t *)grid32;
+ grid32[0] = iq1s_grid_gpu[x[i].qs[4*ib+il] | (((x[i].qh[ib] >> 3*il) & 7) << 8)];
+ grid32[1] = (grid32[0] >> 4) & 0x0f0f0f0f;
+ grid32[0] &= 0x0f0f0f0f;
for (int j = 0; j < 8; ++j) {
- y[j] = d * q[j];
- }
-#else
- const uint8_t * grid = (const uint8_t *)(iq1s_grid_gpu + (x[i].qs[4*ib+il] | (((x[i].qh[ib] >> 3*il) & 7) << 8)));
- for (int j = 0; j < 4; ++j) {
- y[j+0] = d * ((grid[j] & 0xf) - 1);
- y[j+4] = d * ((grid[j] >> 4) - 1);
+ y[j] = d * (q[j] + delta);
}
-#endif
#else
assert(false);
#endif
const int * q8 = (const int *)bq8_1[ib32].qs;
for (int l = 0; l < 4; ++l) {
const int * grid = (const int *)(iq1s_grid_gpu + (bq1->qs[4*ib32+l] | (((bq1->qh[ib32] >> 3*l) & 7) << 8)));
- int grid0 = __vsub4(grid[0] & 0x0f0f0f0f, 0x01010101);
- int grid1 = __vsub4((grid[0] >> 4) & 0x0f0f0f0f, 0x01010101);
+ int grid0 = grid[0] & 0x0f0f0f0f;
+ int grid1 = (grid[0] >> 4) & 0x0f0f0f0f;
sumi = __dp4a(q8[2*l+1], grid1, __dp4a(q8[2*l+0], grid0, sumi));
}
#else
- const int8_t * q8 = bq8_1[ib32].qs;
+ const int8_t * q8 = bq8_1[ib32].qs;
for (int l = 0; l < 4; ++l) {
const uint8_t * grid = (const uint8_t *)(iq1s_grid_gpu + (bq1->qs[4*ib32+l] | (((bq1->qh[ib32] >> 3*l) & 7) << 8)));
for (int j = 0; j < 4; ++j) {
- sumi += q8[j] * ((grid[j] & 0xf) - 1) + q8[j+4] * ((grid[j] >> 4) - 1);
+ sumi += q8[j] * (grid[j] & 0xf) + q8[j+4] * (grid[j] >> 4);
}
q8 += 8;
}
#endif
- const float d = (float)bq1->d * __low2float(bq8_1[ib32].ds);
- return d * sumi * (2*(bq1->qh[ib32] >> 12) + 1);
+ const float delta = bq1->qh[ib32] & 0x8000 ? -1-IQ1S_DELTA : -1+IQ1S_DELTA;
+ const float d1q = (float)bq1->d * (2*((bq1->qh[ib32] >> 12) & 7) + 1);
+ const float d = d1q * __low2float (bq8_1[ib32].ds);
+ const float m = d1q * __high2float(bq8_1[ib32].ds);
+ return d * sumi + m * delta;
#else
assert(false);
return 0.f;
const uint16_t * qh = x[i].qh;
for (int ib = 0; ib < QK_K/32; ++ib) {
- const float dl = d * (2*(qh[ib] >> 12) + 1);
+ const float dl = d * (2*((qh[ib] >> 12) & 7) + 1);
+ const float delta = qh[ib] & 0x8000 ? -IQ1S_DELTA : IQ1S_DELTA;
for (int l = 0; l < 4; ++l) {
const int8_t * grid = (const int8_t *)(iq1s_grid + (qs[l] | (((qh[ib] >> 3*l) & 7) << 8)));
for (int j = 0; j < 8; ++j) {
- y[j] = dl * grid[j];
+ y[j] = dl * (grid[j] + delta);
}
y += 8;
}
const uint8_t * qs = x[i].qs;
const uint16_t * qh = x[i].qh;
- int sumi1 = 0, sumi2 = 0;
+ int sumi1 = 0, sumi2 = 0, sumi3 = 0;
for (int ib = 0; ib < QK_K/32; ib += 2) {
const int32x4_t p1 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), q1b.val[0], q8b.val[0]), q1b.val[1], q8b.val[1]);
const int32x4_t p2 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), q1b.val[2], q8b.val[2]), q1b.val[3], q8b.val[3]);
- sumi1 += vaddvq_s32(p1) * (2*(qh[ib+0] >> 12) + 1);
- sumi2 += vaddvq_s32(p2) * (2*(qh[ib+1] >> 12) + 1);
+ const int ls1 = 2*((qh[ib+0] >> 12) & 7) + 1;
+ const int ls2 = 2*((qh[ib+1] >> 12) & 7) + 1;
+ sumi1 += vaddvq_s32(p1) * ls1;
+ sumi2 += vaddvq_s32(p2) * ls2;
+ sumi3 += (y[i].bsums[2*ib+0] + y[i].bsums[2*ib+1]) * ls1 * (qh[ib+0] & 0x8000 ? -1 : 1)
+ + (y[i].bsums[2*ib+2] + y[i].bsums[2*ib+3]) * ls2 * (qh[ib+1] & 0x8000 ? -1 : 1);
}
- sumf += y[i].d * GGML_FP16_TO_FP32(x[i].d) * (sumi1 + sumi2);
+ sumf += y[i].d * GGML_FP16_TO_FP32(x[i].d) * (sumi1 + sumi2 + IQ1S_DELTA * sumi3);
}
*s = sumf;
#elif defined __AVX2__
__m256 accum = _mm256_setzero_ps();
+ float accum1 = 0;
for (int i = 0; i < nb; ++i) {
const int8_t * q8 = y[i].qs;
const uint16_t * qh = x[i].qh;
__m256i sumi = _mm256_setzero_si256();
+ int sumi1 = 0;
for (int ib = 0; ib < QK_K/32; ib += 2) {
const __m256i q1b_1 = _mm256_set_epi64x(iq1s_grid[qs[3] | ((qh[ib+0] >> 1) & 0x700)], iq1s_grid[qs[2] | ((qh[ib+0] << 2) & 0x700)],
iq1s_grid[qs[1] | ((qh[ib+0] << 5) & 0x700)], iq1s_grid[qs[0] | ((qh[ib+0] << 8) & 0x700)]);
const __m256i dot1 = mul_add_epi8(q1b_1, q8b_1);
const __m256i dot2 = mul_add_epi8(q1b_2, q8b_2);
- const __m256i p1 = _mm256_madd_epi16(dot1, _mm256_set1_epi16(2*(qh[ib+0] >> 12) + 1));
- const __m256i p2 = _mm256_madd_epi16(dot2, _mm256_set1_epi16(2*(qh[ib+1] >> 12) + 1));
+ const int16_t ls1 = 2*((qh[ib+0] >> 12) & 7) + 1;
+ const int16_t ls2 = 2*((qh[ib+1] >> 12) & 7) + 1;
+ const __m256i p1 = _mm256_madd_epi16(dot1, _mm256_set1_epi16(ls1));
+ const __m256i p2 = _mm256_madd_epi16(dot2, _mm256_set1_epi16(ls2));
sumi = _mm256_add_epi32(sumi, _mm256_add_epi32(p1, p2));
+ sumi1 += (y[i].bsums[2*ib+0] + y[i].bsums[2*ib+1]) * (qh[ib+0] & 0x8000 ? -1 : 1) * ls1
+ + (y[i].bsums[2*ib+2] + y[i].bsums[2*ib+3]) * (qh[ib+1] & 0x8000 ? -1 : 1) * ls2;
}
- accum = _mm256_fmadd_ps(_mm256_set1_ps(y[i].d * GGML_FP16_TO_FP32(x[i].d)), _mm256_cvtepi32_ps(sumi), accum);
+ const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
+ accum = _mm256_fmadd_ps(_mm256_set1_ps(d), _mm256_cvtepi32_ps(sumi), accum);
+ accum1 += d * sumi1;
}
- *s = hsum_float_8(accum);
+ *s = hsum_float_8(accum) + IQ1S_DELTA * accum1;
#else
const uint8_t * qs = x[i].qs;
const uint16_t * qh = x[i].qh;
- int sumi = 0;
+ int sumi = 0, sumi1 = 0;
for (int ib = 0; ib < QK_K/32; ++ib) {
- const int ls = 2*(qh[ib] >> 12) + 1;
+ const int ls = 2*((qh[ib] >> 12) & 7) + 1;
+ const int delta = qh[ib] & 0x8000 ? -1 : 1;
int lsum = 0;
for (int l = 0; l < 4; ++l) {
const int8_t * grid = (const int8_t *)(iq1s_grid + (qs[l] | (((qh[ib] >> 3*l) & 7) << 8)));
}
q8 += 8;
}
- sumi += ls * lsum;
+ sumi += ls * lsum;
+ sumi1 += ls * delta * (y[i].bsums[2*ib+0] + y[i].bsums[2*ib+1]);
qs += 4;
}
- sumf += GGML_FP16_TO_FP32(x[i].d) * y[i].d * sumi;
+ sumf += GGML_FP16_TO_FP32(x[i].d) * y[i].d * (sumi + IQ1S_DELTA * sumi1);
}
*s = sumf;
}
static int iq1_find_best_neighbour2(const uint16_t * restrict neighbours, const uint64_t * restrict grid,
- const float * restrict xval, const float * restrict weight, float scale, int8_t * restrict L, int ngrid) {
+ const float * restrict xval, const float * restrict weight, float scale, const float * restrict xg, int8_t * restrict L, int ngrid) {
int num_neighbors = neighbours[0];
GGML_ASSERT(num_neighbors > 0);
float best_score = FLT_MAX;
const int8_t * pg = (const int8_t *)(grid + neighbours[j]);
float d2 = 0;
for (int i = 0; i < 8; ++i) {
- float q = (pg[i] - 3)/2;
+ float q = xg[(pg[i] - 1)/2];
float w = weight[i];
float diff = scale*q - xval[i];
d2 += w*diff*diff;
float d2 = 0;
for (int j = 0; j < 8; ++j) {
float w = weight[j];
- float q = (grid_i[j] - 3)/2;
+ float q = xg[(grid_i[j] - 1)/2];
float diff = scale*q - xval[i];
d2 += w*diff*diff;
}
const int8_t * pg = (const int8_t *)(grid + neighbours[j]);
float sumqx = 0, sumq2 = 0;
for (int i = 0; i < 8; ++i) {
- float q = (pg[i] - 3)/2;
+ float q = xg[(pg[i] - 1)/2];
float w = weight[i];
sumqx += w*q*xval[i];
sumq2 += w*q*q;
block_iq1_s * y = vy;
+ const float x_p[3] = {-1 + IQ1S_DELTA, IQ1S_DELTA, 1 + IQ1S_DELTA};
+ const float x_m[3] = {-1 - IQ1S_DELTA, -IQ1S_DELTA, 1 - IQ1S_DELTA};
+
float scales[QK_K/IQ1S_BLOCK_SIZE];
float weight[IQ1S_BLOCK_SIZE];
int8_t L[IQ1S_BLOCK_SIZE];
float pairs[2*IQ1S_BLOCK_SIZE];
int * idx = (int *)(pairs + 1);
uint16_t index[IQ1S_BLOCK_SIZE/8];
+ int8_t shifts[QK_K/IQ1S_BLOCK_SIZE];
for (int ibl = 0; ibl < nbl; ++ibl) {
}
}
float best_score = 0, scale = max;
- int besti1 = 0, besti2 = 0;
+ int besti1 = -1, besti2 = -1, best_shift = 0;
for (int i1 = 0; i1 <= IQ1S_BLOCK_SIZE; ++i1) {
for (int i2 = i1; i2 <= IQ1S_BLOCK_SIZE; ++i2) {
- float sumqx = -(sumx[i1] - sumx[0]) + (sumx[IQ1S_BLOCK_SIZE] - sumx[i2]);
- float sumq2 = (sumw[i1] - sumw[0]) + (sumw[IQ1S_BLOCK_SIZE] - sumw[i2]);
+ float sumqx = (sumx[i1] - sumx[0])*x_p[0] + (sumx[i2] - sumx[i1])*x_p[1] + (sumx[IQ1S_BLOCK_SIZE] - sumx[i2])*x_p[2];
+ float sumq2 = (sumw[i1] - sumw[0])*x_p[0]*x_p[0] + (sumw[i2] - sumw[i1])*x_p[1]*x_p[1] + (sumw[IQ1S_BLOCK_SIZE] - sumw[i2])*x_p[2]*x_p[2];
+ if (sumq2 > 0 && sumqx*sumqx > best_score*sumq2) {
+ scale = sumqx/sumq2; best_score = scale*sumqx;
+ besti1 = i1; besti2 = i2; best_shift = 1;
+ }
+ sumqx = (sumx[i1] - sumx[0])*x_m[0] + (sumx[i2] - sumx[i1])*x_m[1] + (sumx[IQ1S_BLOCK_SIZE] - sumx[i2])*x_m[2];
+ sumq2 = (sumw[i1] - sumw[0])*x_m[0]*x_m[0] + (sumw[i2] - sumw[i1])*x_m[1]*x_m[1] + (sumw[IQ1S_BLOCK_SIZE] - sumw[i2])*x_m[2]*x_m[2];
if (sumq2 > 0 && sumqx*sumqx > best_score*sumq2) {
scale = sumqx/sumq2; best_score = scale*sumqx;
- besti1 = i1; besti2 = i2;
+ besti1 = i1; besti2 = i2; best_shift = -1;
}
}
}
+ GGML_ASSERT(besti1 >= 0 && besti2 >= 0 && best_shift != 0);
for (int j = 0; j < besti1; ++j) L[idx[2*j]] = 0;
for (int j = besti1; j < besti2; ++j) L[idx[2*j]] = 1;
for (int j = besti2; j < IQ1S_BLOCK_SIZE; ++j) L[idx[2*j]] = 2;
if (scale < 0) {
for (int j = 0; j < IQ1S_BLOCK_SIZE; ++j) L[j] = 2 - L[j];
- scale = -scale;
+ scale = -scale; best_shift = -best_shift;
}
bool all_on_grid = true;
+ const float * xx = best_shift == 1 ? x_p : x_m;
for (int k = 0; k < IQ1S_BLOCK_SIZE/8; ++k) {
uint16_t u = 0;
for (int j = 0; j < 8; ++j) u |= (L[8*k+j] << 2*j);
if (grid_index < 0) {
all_on_grid = false;
const uint16_t * neighbours = kneighbors_q2xs - kmap_q2xs[u] - 1;
- grid_index = iq1_find_best_neighbour2(neighbours, kgrid_q2xs, xb + 8*k, weight + 8*k, scale, L + 8*k, NGRID_IQ1S);
+ grid_index = iq1_find_best_neighbour2(neighbours, kgrid_q2xs, xb + 8*k, weight + 8*k, scale, xx, L + 8*k, NGRID_IQ1S);
GGML_ASSERT(grid_index >= 0);
}
index[k] = grid_index;
const int8_t * pg = (const int8_t *)(kgrid_q2xs + index[k]);
for (int j = 0; j < 8; ++j) {
float w = weight[8*k + j];
- float q = (pg[j] - 3)/2;
+ float q = xx[(pg[j] - 1)/2];
sumqx += w*q*xb[8*k+j];
sumq2 += w*q*q;
}
y[ibl].qh[ib] = h;
GGML_ASSERT(scale >= 0);
scales[ib] = scale;
+ shifts[ib] = best_shift;
max_scale = MAX(max_scale, scale);
}
continue;
}
- float d = max_scale/31;
+ float d = max_scale/15;
y[ibl].d = GGML_FP32_TO_FP16(d*1.125f); // 1.085f is another fudge factor. Don't ask me why it is needed.
float id = 1/d;
for (int ib = 0; ib < QK_K/IQ1S_BLOCK_SIZE; ++ib) {
int l = nearest_int(0.5f*(id*scales[ib]-1));
- l = MAX(0, MIN(15, l));
+ l = MAX(0, MIN(7, l));
+ if (shifts[ib] == -1) l |= 8;
y[ibl].qh[ib] |= (l << 12);
}
}