#define ggml_gemv_q2_K_8x8_q8_K_generic ggml_gemv_q2_K_8x8_q8_K
#define ggml_gemv_q4_K_8x4_q8_K_generic ggml_gemv_q4_K_8x4_q8_K
#define ggml_gemv_q4_K_8x8_q8_K_generic ggml_gemv_q4_K_8x8_q8_K
+#define ggml_gemv_q5_K_8x4_q8_K_generic ggml_gemv_q5_K_8x4_q8_K
#define ggml_gemv_q5_K_8x8_q8_K_generic ggml_gemv_q5_K_8x8_q8_K
#define ggml_gemv_q6_K_8x4_q8_K_generic ggml_gemv_q6_K_8x4_q8_K
#define ggml_gemv_q6_K_8x8_q8_K_generic ggml_gemv_q6_K_8x8_q8_K
#define ggml_gemm_q2_K_8x8_q8_K_generic ggml_gemm_q2_K_8x8_q8_K
#define ggml_gemm_q4_K_8x4_q8_K_generic ggml_gemm_q4_K_8x4_q8_K
#define ggml_gemm_q4_K_8x8_q8_K_generic ggml_gemm_q4_K_8x8_q8_K
+#define ggml_gemm_q5_K_8x4_q8_K_generic ggml_gemm_q5_K_8x4_q8_K
#define ggml_gemm_q5_K_8x8_q8_K_generic ggml_gemm_q5_K_8x8_q8_K
#define ggml_gemm_q6_K_8x4_q8_K_generic ggml_gemm_q6_K_8x4_q8_K
-#define ggml_gemm_q6_K_8x8_q8_K_generic ggml_gemm_q6_K_8x8_q8_K
+#define ggml_gemm_q6_K_8x8_q8_K_generic ggml_gemm_q6_K_8x8_q8_K
#define ggml_gemm_iq4_nl_4x4_q8_0_generic ggml_gemm_iq4_nl_4x4_q8_0
#define ggml_gemm_iq4_nl_8x8_q8_0_generic ggml_gemm_iq4_nl_8x8_q8_0
#define ggml_gemm_q8_0_4x4_q8_0_generic ggml_gemm_q8_0_4x4_q8_0
#define ggml_gemv_q4_0_4x4_q8_0_generic ggml_gemv_q4_0_4x4_q8_0
#define ggml_gemv_q4_0_4x8_q8_0_generic ggml_gemv_q4_0_4x8_q8_0
#define ggml_gemv_q4_K_8x4_q8_K_generic ggml_gemv_q4_K_8x4_q8_K
+#define ggml_gemv_q5_K_8x4_q8_K_generic ggml_gemv_q5_K_8x4_q8_K
#define ggml_gemv_q5_K_8x8_q8_K_generic ggml_gemv_q5_K_8x8_q8_K
#define ggml_gemv_q6_K_8x4_q8_K_generic ggml_gemv_q6_K_8x4_q8_K
#define ggml_gemv_q6_K_8x8_q8_K_generic ggml_gemv_q6_K_8x8_q8_K
#define ggml_gemm_q4_0_4x4_q8_0_generic ggml_gemm_q4_0_4x4_q8_0
#define ggml_gemm_q4_0_4x8_q8_0_generic ggml_gemm_q4_0_4x8_q8_0
#define ggml_gemm_q4_K_8x4_q8_K_generic ggml_gemm_q4_K_8x4_q8_K
+#define ggml_gemm_q5_K_8x4_q8_K_generic ggml_gemm_q5_K_8x4_q8_K
#define ggml_gemm_q5_K_8x8_q8_K_generic ggml_gemm_q5_K_8x8_q8_K
#define ggml_gemm_q6_K_8x4_q8_K_generic ggml_gemm_q6_K_8x4_q8_K
#define ggml_gemm_q6_K_8x8_q8_K_generic ggml_gemm_q6_K_8x8_q8_K
#define ggml_gemv_q2_K_8x8_q8_K_generic ggml_gemv_q2_K_8x8_q8_K
#define ggml_gemv_q4_K_8x4_q8_K_generic ggml_gemv_q4_K_8x4_q8_K
#define ggml_gemv_q4_K_8x8_q8_K_generic ggml_gemv_q4_K_8x8_q8_K
+#define ggml_gemv_q5_K_8x4_q8_K_generic ggml_gemv_q5_K_8x4_q8_K
#define ggml_gemv_q5_K_8x8_q8_K_generic ggml_gemv_q5_K_8x8_q8_K
#define ggml_gemv_q6_K_8x4_q8_K_generic ggml_gemv_q6_K_8x4_q8_K
#define ggml_gemv_q6_K_8x8_q8_K_generic ggml_gemv_q6_K_8x8_q8_K
#define ggml_gemm_q2_K_8x8_q8_K_generic ggml_gemm_q2_K_8x8_q8_K
#define ggml_gemm_q4_K_8x4_q8_K_generic ggml_gemm_q4_K_8x4_q8_K
#define ggml_gemm_q4_K_8x8_q8_K_generic ggml_gemm_q4_K_8x8_q8_K
+#define ggml_gemm_q5_K_8x4_q8_K_generic ggml_gemm_q5_K_8x4_q8_K
#define ggml_gemm_q5_K_8x8_q8_K_generic ggml_gemm_q5_K_8x8_q8_K
#define ggml_gemm_q6_K_8x4_q8_K_generic ggml_gemm_q6_K_8x4_q8_K
#define ggml_gemm_q6_K_8x8_q8_K_generic ggml_gemm_q6_K_8x8_q8_K
#define ggml_gemv_q2_K_8x8_q8_K_generic ggml_gemv_q2_K_8x8_q8_K
#define ggml_gemv_q4_K_8x4_q8_K_generic ggml_gemv_q4_K_8x4_q8_K
#define ggml_gemv_q4_K_8x8_q8_K_generic ggml_gemv_q4_K_8x8_q8_K
+#define ggml_gemv_q5_K_8x4_q8_K_generic ggml_gemv_q5_K_8x4_q8_K
#define ggml_gemv_q5_K_8x8_q8_K_generic ggml_gemv_q5_K_8x8_q8_K
#define ggml_gemv_q6_K_8x4_q8_K_generic ggml_gemv_q6_K_8x4_q8_K
#define ggml_gemv_q6_K_8x8_q8_K_generic ggml_gemv_q6_K_8x8_q8_K
#define ggml_gemm_q2_K_8x8_q8_K_generic ggml_gemm_q2_K_8x8_q8_K
#define ggml_gemm_q4_K_8x4_q8_K_generic ggml_gemm_q4_K_8x4_q8_K
#define ggml_gemm_q4_K_8x8_q8_K_generic ggml_gemm_q4_K_8x8_q8_K
+#define ggml_gemm_q5_K_8x4_q8_K_generic ggml_gemm_q5_K_8x4_q8_K
#define ggml_gemm_q5_K_8x8_q8_K_generic ggml_gemm_q5_K_8x8_q8_K
#define ggml_gemm_q6_K_8x4_q8_K_generic ggml_gemm_q6_K_8x4_q8_K
#define ggml_gemm_q6_K_8x8_q8_K_generic ggml_gemm_q6_K_8x8_q8_K
#define ggml_gemv_q2_K_8x8_q8_K_generic ggml_gemv_q2_K_8x8_q8_K
#define ggml_gemv_q4_K_8x4_q8_K_generic ggml_gemv_q4_K_8x4_q8_K
#define ggml_gemv_q4_K_8x8_q8_K_generic ggml_gemv_q4_K_8x8_q8_K
+#define ggml_gemv_q5_K_8x4_q8_K_generic ggml_gemv_q5_K_8x4_q8_K
#define ggml_gemv_q5_K_8x8_q8_K_generic ggml_gemv_q5_K_8x8_q8_K
#define ggml_gemv_q6_K_8x4_q8_K_generic ggml_gemv_q6_K_8x4_q8_K
#define ggml_gemv_q6_K_8x8_q8_K_generic ggml_gemv_q6_K_8x8_q8_K
#define ggml_gemm_q2_K_8x8_q8_K_generic ggml_gemm_q2_K_8x8_q8_K
#define ggml_gemm_q4_K_8x4_q8_K_generic ggml_gemm_q4_K_8x4_q8_K
#define ggml_gemm_q4_K_8x8_q8_K_generic ggml_gemm_q4_K_8x8_q8_K
+#define ggml_gemm_q5_K_8x4_q8_K_generic ggml_gemm_q5_K_8x4_q8_K
#define ggml_gemm_q5_K_8x8_q8_K_generic ggml_gemm_q5_K_8x8_q8_K
#define ggml_gemm_q6_K_8x4_q8_K_generic ggml_gemm_q6_K_8x4_q8_K
#define ggml_gemm_q6_K_8x8_q8_K_generic ggml_gemm_q6_K_8x8_q8_K
#define ggml_gemv_q2_K_8x8_q8_K_generic ggml_gemv_q2_K_8x8_q8_K
#define ggml_gemv_q4_K_8x4_q8_K_generic ggml_gemv_q4_K_8x4_q8_K
#define ggml_gemv_q4_K_8x8_q8_K_generic ggml_gemv_q4_K_8x8_q8_K
+#define ggml_gemv_q5_K_8x4_q8_K_generic ggml_gemv_q5_K_8x4_q8_K
#define ggml_gemv_q5_K_8x8_q8_K_generic ggml_gemv_q5_K_8x8_q8_K
#define ggml_gemv_q6_K_8x4_q8_K_generic ggml_gemv_q6_K_8x4_q8_K
#define ggml_gemv_q6_K_8x8_q8_K_generic ggml_gemv_q6_K_8x8_q8_K
#define ggml_gemm_q2_K_8x8_q8_K_generic ggml_gemm_q2_K_8x8_q8_K
#define ggml_gemm_q4_K_8x4_q8_K_generic ggml_gemm_q4_K_8x4_q8_K
#define ggml_gemm_q4_K_8x8_q8_K_generic ggml_gemm_q4_K_8x8_q8_K
+#define ggml_gemm_q5_K_8x4_q8_K_generic ggml_gemm_q5_K_8x4_q8_K
#define ggml_gemm_q5_K_8x8_q8_K_generic ggml_gemm_q5_K_8x8_q8_K
#define ggml_gemm_q6_K_8x4_q8_K_generic ggml_gemm_q6_K_8x4_q8_K
#define ggml_gemm_q6_K_8x8_q8_K_generic ggml_gemm_q6_K_8x8_q8_K
#define ggml_gemv_q2_K_8x8_q8_K_generic ggml_gemv_q2_K_8x8_q8_K
#define ggml_gemv_q4_K_8x4_q8_K_generic ggml_gemv_q4_K_8x4_q8_K
#define ggml_gemv_q4_K_8x8_q8_K_generic ggml_gemv_q4_K_8x8_q8_K
+#define ggml_gemv_q5_K_8x4_q8_K_generic ggml_gemv_q5_K_8x4_q8_K
#define ggml_gemv_q5_K_8x8_q8_K_generic ggml_gemv_q5_K_8x8_q8_K
#define ggml_gemv_q6_K_8x4_q8_K_generic ggml_gemv_q6_K_8x4_q8_K
#define ggml_gemv_q6_K_8x8_q8_K_generic ggml_gemv_q6_K_8x8_q8_K
#define ggml_gemm_q2_K_8x8_q8_K_generic ggml_gemm_q2_K_8x8_q8_K
#define ggml_gemm_q4_K_8x4_q8_K_generic ggml_gemm_q4_K_8x4_q8_K
#define ggml_gemm_q4_K_8x8_q8_K_generic ggml_gemm_q4_K_8x8_q8_K
+#define ggml_gemm_q5_K_8x4_q8_K_generic ggml_gemm_q5_K_8x4_q8_K
#define ggml_gemm_q5_K_8x8_q8_K_generic ggml_gemm_q5_K_8x8_q8_K
#define ggml_gemm_q6_K_8x4_q8_K_generic ggml_gemm_q6_K_8x4_q8_K
#define ggml_gemm_q6_K_8x8_q8_K_generic ggml_gemm_q6_K_8x8_q8_K
ggml_gemv_q4_K_8x8_q8_K_generic(n, s, bs, vx, vy, nr, nc);
}
+void ggml_gemv_q5_K_8x4_q8_K(int n,
+ float * GGML_RESTRICT s,
+ size_t bs,
+ const void * GGML_RESTRICT vx,
+ const void * GGML_RESTRICT vy,
+ int nr,
+ int nc) {
+ constexpr int qk = QK_K;
+ const int nb = n / qk;
+
+ constexpr int ncols_interleaved = 8;
+ constexpr int blocklen = 4;
+
+ assert(n % qk == 0);
+ assert(nc % ncols_interleaved == 0);
+
+ UNUSED(nb);
+ UNUSED(ncols_interleaved);
+ UNUSED(blocklen);
+
+#if defined(__aarch64__) && defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
+ constexpr int col_groups = ncols_interleaved / 4; // 0123 and 4567
+ const uint8x16_t m4b = vdupq_n_u8(0x0f);
+ const uint8x16_t mone = vdupq_n_u8(1);
+ const uint8x16_t mtwo = vdupq_n_u8(2);
+
+ // 1x8 tile = 2 x 4
+ float32x4_t acc_f32[col_groups];
+
+ const block_q8_K * GGML_RESTRICT q8_ptr = (const block_q8_K *) vy;
+
+ for (int x = 0; x < nc / ncols_interleaved; x++) {
+ const block_q5_Kx8 * GGML_RESTRICT q5_ptr = (const block_q5_Kx8 *) vx + (x * nb);
+
+ for (int i = 0; i < col_groups; i++) {
+ acc_f32[i] = vdupq_n_f32(0);
+ }
+
+ for (int b = 0; b < nb; b++) {
+ float32x4_t q5_d_0 = vcvt_f32_f16(vld1_f16((const __fp16 *) q5_ptr[b].d)); // d0 d1 d2 d3
+ float32x4_t q5_d_1 = vcvt_f32_f16(vld1_f16((const __fp16 *) q5_ptr[b].d + 4)); // d4 d5 d6 d7
+ float32x4_t q8_d = vdupq_n_f32(q8_ptr[b].d);
+ float32x4_t sb_scale_0123 = vmulq_f32(q5_d_0, q8_d);
+ float32x4_t sb_scale_4567 = vmulq_f32(q5_d_1, q8_d);
+ float32x4_t q5_dmin_0 = vcvt_f32_f16(vld1_f16((const __fp16 *) q5_ptr[b].dmin)); // dmin 0..3
+ float32x4_t q5_dmin_1 = vcvt_f32_f16(vld1_f16((const __fp16 *) q5_ptr[b].dmin + 4)); // dmin 4..7
+ float32x4_t sb_min_0123 = vmulq_f32(q5_dmin_0, q8_d);
+ float32x4_t sb_min_4567 = vmulq_f32(q5_dmin_1, q8_d);
+
+ // interleaved bias_acc: [0]->r0 0123, [1]->r0 4567
+ int32x4_t bias_acc[2] = { vdupq_n_s32(0), vdupq_n_s32(0) };
+ int32x4_t acc_lo[col_groups];
+ int32x4_t acc_hi[col_groups];
+
+ // Each bsum is 16 elements, pairwise add leaves us with the 8 bsums of the entire block
+ const int16x8_t bsums = vpaddq_s16(vld1q_s16(q8_ptr[b].bsums), vld1q_s16(q8_ptr[b].bsums + 8));
+ int16_t bsums_arr[8];
+ vst1q_s16(bsums_arr, bsums);
+
+ uint8x16_t qh[col_groups][8];
+ for (int c = 0; c < col_groups; c++) {
+ for (int i = 0; i < 8; i++) {
+ qh[c][i] = vld1q_u8(q5_ptr[b].qh + i * 32 + 16 * c);
+ }
+ }
+
+ for (int sb = 0; sb < QK_K / 64; sb++) {
+ for (int i = 0; i < col_groups; i++) {
+ acc_lo[i] = vdupq_n_s32(0);
+ acc_hi[i] = vdupq_n_s32(0);
+ }
+ // Need scales for the low and high nibbles
+ // 2 * 12 = 24 bytes per subblock, 4 sbs -> 4 * 24 = 96 bytes total
+ int16x8_t q5sb_mins[2];
+ int16x8_t q5sb_scales[2];
+ for (int i = 0; i < 2; i++) {
+ int8_t aux_q5sb[8];
+ const int offset = sb * 24 + i * 12;
+ decode_q_Kx8_6bit_scales(&q5_ptr[b].scales[offset], &q5sb_mins[i], aux_q5sb);
+ q5sb_scales[i] = vmovl_s8(vld1_s8(aux_q5sb));
+ }
+
+ int8x16_t q8_qs[4];
+ for (int i = 0; i < 4; i++) {
+ q8_qs[i] = vld1q_s8(q8_ptr[b].qs + sb * 64 + i * 16);
+ }
+
+ for (int c = 0; c < col_groups; c++) {
+ uint8x16_t q5_cols[8];
+ uint8x16_t hbit_lo[8];
+ uint8x16_t hbit_hi[8];
+ int8x16_t q5_lo[8];
+ int8x16_t q5_hi[8];
+
+ for (int i = 0; i < 8; i++) {
+ q5_cols[i] = vld1q_u8(q5_ptr[b].qs + sb * QK_K + i * 32 + 16 * c);
+ hbit_lo[i] = vandq_u8(qh[c][i], mone);
+ hbit_hi[i] = vshlq_n_u8(vandq_u8(qh[c][i], mtwo), 3);
+ qh[c][i] = vshrq_n_u8(qh[c][i], 2);
+ q5_lo[i] = vreinterpretq_s8_u8(vsliq_n_u8(vandq_u8(q5_cols[i], m4b), hbit_lo[i], 4));
+ q5_hi[i] = vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q5_cols[i], 4), hbit_hi[i]));
+ }
+
+ acc_lo[c] = vdotq_laneq_s32(acc_lo[c], q5_lo[0], q8_qs[0], 0);
+ acc_lo[c] = vdotq_laneq_s32(acc_lo[c], q5_lo[1], q8_qs[0], 1);
+ acc_lo[c] = vdotq_laneq_s32(acc_lo[c], q5_lo[2], q8_qs[0], 2);
+ acc_lo[c] = vdotq_laneq_s32(acc_lo[c], q5_lo[3], q8_qs[0], 3);
+ acc_lo[c] = vdotq_laneq_s32(acc_lo[c], q5_lo[4], q8_qs[1], 0);
+ acc_lo[c] = vdotq_laneq_s32(acc_lo[c], q5_lo[5], q8_qs[1], 1);
+ acc_lo[c] = vdotq_laneq_s32(acc_lo[c], q5_lo[6], q8_qs[1], 2);
+ acc_lo[c] = vdotq_laneq_s32(acc_lo[c], q5_lo[7], q8_qs[1], 3);
+
+ acc_hi[c] = vdotq_laneq_s32(acc_hi[c], q5_hi[0], q8_qs[2], 0);
+ acc_hi[c] = vdotq_laneq_s32(acc_hi[c], q5_hi[1], q8_qs[2], 1);
+ acc_hi[c] = vdotq_laneq_s32(acc_hi[c], q5_hi[2], q8_qs[2], 2);
+ acc_hi[c] = vdotq_laneq_s32(acc_hi[c], q5_hi[3], q8_qs[2], 3);
+ acc_hi[c] = vdotq_laneq_s32(acc_hi[c], q5_hi[4], q8_qs[3], 0);
+ acc_hi[c] = vdotq_laneq_s32(acc_hi[c], q5_hi[5], q8_qs[3], 1);
+ acc_hi[c] = vdotq_laneq_s32(acc_hi[c], q5_hi[6], q8_qs[3], 2);
+ acc_hi[c] = vdotq_laneq_s32(acc_hi[c], q5_hi[7], q8_qs[3], 3);
+ }
+
+ // Scales
+ // row c0123 blk0 and blk1
+ const int16x4_t sc_0123_lo = vget_low_s16(q5sb_scales[0]);
+ const int16x4_t sc_0123_hi = vget_low_s16(q5sb_scales[1]);
+ const float32x4_t sumf_0123 = vcvtq_f32_s32(vaddq_s32(vmulq_s32(vmovl_s16(sc_0123_lo), acc_lo[0]),
+ vmulq_s32(vmovl_s16(sc_0123_hi), acc_hi[0])));
+ acc_f32[0] = vfmaq_f32(acc_f32[0], sb_scale_0123, sumf_0123);
+ // row c4567 blk0 and blk1
+ const int16x4_t sc_4567_lo = vget_high_s16(q5sb_scales[0]);
+ const int16x4_t sc_4567_hi = vget_high_s16(q5sb_scales[1]);
+ const float32x4_t sumf_4567 = vcvtq_f32_s32(vaddq_s32(vmulq_s32(vmovl_s16(sc_4567_lo), acc_lo[1]),
+ vmulq_s32(vmovl_s16(sc_4567_hi), acc_hi[1])));
+ acc_f32[1] = vfmaq_f32(acc_f32[1], sb_scale_4567, sumf_4567);
+
+ // Bias Correction
+ const int16x4_t bsums_vec_lo = vdup_n_s16(bsums_arr[2 * sb + 0]);
+ const int16x4_t bsums_vec_hi = vdup_n_s16(bsums_arr[2 * sb + 1]);
+
+ bias_acc[0] = vmlal_s16(bias_acc[0], bsums_vec_lo, vget_low_s16(q5sb_mins[0]));
+ bias_acc[0] = vmlal_s16(bias_acc[0], bsums_vec_hi, vget_low_s16(q5sb_mins[1]));
+ bias_acc[1] = vmlal_s16(bias_acc[1], bsums_vec_lo, vget_high_s16(q5sb_mins[0]));
+ bias_acc[1] = vmlal_s16(bias_acc[1], bsums_vec_hi, vget_high_s16(q5sb_mins[1]));
+ } // for sb
+
+ acc_f32[0] = vmlsq_f32(acc_f32[0], vcvtq_f32_s32(bias_acc[0]), sb_min_0123);
+ acc_f32[1] = vmlsq_f32(acc_f32[1], vcvtq_f32_s32(bias_acc[1]), sb_min_4567);
+ } // for b
+
+ int base = x * ncols_interleaved;
+ vst1q_f32(s + base, acc_f32[0]);
+ vst1q_f32(s + base + 4, acc_f32[1]);
+ } // for x
+ return;
+#endif // defined(__aarch64__) && defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
+ ggml_gemv_q5_K_8x4_q8_K_generic(n, s, bs, vx, vy, nr, nc);
+}
+
void ggml_gemv_q5_K_8x8_q8_K(int n,
float * GGML_RESTRICT s,
size_t bs,
ggml_gemm_q4_K_8x4_q8_K_generic(n, s, bs, vx, vy, nr, nc);
}
+void ggml_gemm_q5_K_8x4_q8_K(int n,
+ float * GGML_RESTRICT s,
+ size_t bs,
+ const void * GGML_RESTRICT vx,
+ const void * GGML_RESTRICT vy,
+ int nr,
+ int nc) {
+ constexpr int qk = QK_K;
+ const int nb = n / qk;
+
+ constexpr int ncols_interleaved = 8;
+ constexpr int blocklen = 4;
+
+ assert(n % qk == 0);
+ assert(nr % 4 == 0);
+ assert(nc % ncols_interleaved == 0);
+
+ UNUSED(nb);
+ UNUSED(ncols_interleaved);
+ UNUSED(blocklen);
+
+#if defined(__aarch64__) && defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
+ constexpr int q8_k_blocklen = 4;
+ constexpr int acc_size = 2 * 4; // 2 row pairs, 4 col pairs
+ constexpr int col_groups = ncols_interleaved / 4;
+ const uint8x16_t m4b = vdupq_n_u8(0x0f);
+ const uint8x16_t mone = vdupq_n_u8(1);
+ const uint8x16_t mtwo = vdupq_n_u8(2);
+
+ // 8 accumulators: 2 row pairs, 4 col pairs
+ float32x4_t acc_f32[acc_size];
+
+ for (int y = 0; y < nr / q8_k_blocklen; y++) {
+ const block_q8_Kx4 * GGML_RESTRICT q8_ptr = (const block_q8_Kx4 *) vy + (y * nb);
+
+ for (int x = 0; x < nc / ncols_interleaved; x++) {
+ const block_q5_Kx8 * GGML_RESTRICT q5_ptr = (const block_q5_Kx8 *) vx + (x * nb);
+
+ for (int i = 0; i < acc_size; i++) {
+ acc_f32[i] = vdupq_n_f32(0);
+ }
+
+ for (int b = 0; b < nb; b++) {
+ // d5 0 1 2 3, 4 5 6 7
+ float32x4_t q5_d_0123 = vcvt_f32_f16(vld1_f16((const __fp16 *) q5_ptr[b].d));
+ float32x4_t q5_d_4567 = vcvt_f32_f16(vld1_f16((const __fp16 *) q5_ptr[b].d + 4));
+ // d8 0 1 2 3
+ float32x4_t q8_d_0123 = vld1q_f32(q8_ptr[b].d);
+ // mins
+ float32x4_t q5_dmin_0123 = vcvt_f32_f16(vld1_f16((const __fp16 *) q5_ptr[b].dmin));
+ float32x4_t q5_dmin_4567 = vcvt_f32_f16(vld1_f16((const __fp16 *) q5_ptr[b].dmin + 4));
+
+ // Precomputation of scales and mins
+ float32x4_t sbd_scale_0123[q8_k_blocklen];
+ float32x4_t sbd_scale_4567[q8_k_blocklen];
+ float32x4_t sbd_min_0123[q8_k_blocklen];
+ float32x4_t sbd_min_4567[q8_k_blocklen];
+
+ sbd_scale_0123[0] = vmulq_laneq_f32(q5_d_0123, q8_d_0123, 0);
+ sbd_scale_4567[0] = vmulq_laneq_f32(q5_d_4567, q8_d_0123, 0);
+ sbd_min_0123[0] = vmulq_laneq_f32(q5_dmin_0123, q8_d_0123, 0);
+ sbd_min_4567[0] = vmulq_laneq_f32(q5_dmin_4567, q8_d_0123, 0);
+
+ sbd_scale_0123[1] = vmulq_laneq_f32(q5_d_0123, q8_d_0123, 1);
+ sbd_scale_4567[1] = vmulq_laneq_f32(q5_d_4567, q8_d_0123, 1);
+ sbd_min_0123[1] = vmulq_laneq_f32(q5_dmin_0123, q8_d_0123, 1);
+ sbd_min_4567[1] = vmulq_laneq_f32(q5_dmin_4567, q8_d_0123, 1);
+
+ sbd_scale_0123[2] = vmulq_laneq_f32(q5_d_0123, q8_d_0123, 2);
+ sbd_scale_4567[2] = vmulq_laneq_f32(q5_d_4567, q8_d_0123, 2);
+ sbd_min_0123[2] = vmulq_laneq_f32(q5_dmin_0123, q8_d_0123, 2);
+ sbd_min_4567[2] = vmulq_laneq_f32(q5_dmin_4567, q8_d_0123, 2);
+
+ sbd_scale_0123[3] = vmulq_laneq_f32(q5_d_0123, q8_d_0123, 3);
+ sbd_scale_4567[3] = vmulq_laneq_f32(q5_d_4567, q8_d_0123, 3);
+ sbd_min_0123[3] = vmulq_laneq_f32(q5_dmin_0123, q8_d_0123, 3);
+ sbd_min_4567[3] = vmulq_laneq_f32(q5_dmin_4567, q8_d_0123, 3);
+
+ // Precomputation of bsums, each vpaddq calcs all the bsums for each row
+ const int16x8_t bsums[q8_k_blocklen] = {
+ vpaddq_s16(vld1q_s16(q8_ptr[b].bsums + 16 * 0), vld1q_s16(q8_ptr[b].bsums + 16 * 0 + 8)),
+ vpaddq_s16(vld1q_s16(q8_ptr[b].bsums + 16 * 1), vld1q_s16(q8_ptr[b].bsums + 16 * 1 + 8)),
+ vpaddq_s16(vld1q_s16(q8_ptr[b].bsums + 16 * 2), vld1q_s16(q8_ptr[b].bsums + 16 * 2 + 8)),
+ vpaddq_s16(vld1q_s16(q8_ptr[b].bsums + 16 * 3), vld1q_s16(q8_ptr[b].bsums + 16 * 3 + 8)),
+ };
+ int16_t bsums_arr[QK_K / 64][8];
+ for (int q8_row = 0; q8_row < 4; q8_row++) {
+ vst1q_s16(bsums_arr[q8_row], bsums[q8_row]);
+ }
+
+ // interleaved bias_acc: [0]->r0 0123, [1]->r1 0123, .., [4]->r0 4567, [5]->r1 4567 ..
+ int32x4_t bias_acc[acc_size];
+ for (int i = 0; i < acc_size; i++) {
+ bias_acc[i] = vdupq_n_s32(0);
+ }
+
+ uint8x16_t qh[col_groups][8];
+ for (int c = 0; c < col_groups; c++) {
+ for (int i = 0; i < 8; i++) {
+ qh[c][i] = vld1q_u8(q5_ptr[b].qh + i * 32 + 16 * c);
+ }
+ }
+
+ for (int sb = 0; sb < QK_K / 64; sb++) {
+ // Int accumulators for qs vecdot (4 row * 2 col quartets)
+ int32x4_t acc_lo[acc_size];
+ int32x4_t acc_hi[acc_size];
+ for (int i = 0; i < acc_size; i++) {
+ acc_lo[i] = vdupq_n_s32(0);
+ acc_hi[i] = vdupq_n_s32(0);
+ }
+ // Need scales for the low and high nibbles
+ // 2 * 12 = 24 bytes per subblock, 4 sbs -> 4 * 24 = 96 bytes total
+ int16x8_t q5sb_scales[2];
+ int16x8_t q5sb_mins[2];
+ for (int i = 0; i < 2; i++) {
+ int8_t aux_q5sb[8];
+ const int offset = sb * 24 + i * 12;
+ decode_q_Kx8_6bit_scales(&q5_ptr[b].scales[offset], &q5sb_mins[i], aux_q5sb);
+ q5sb_scales[i] = vmovl_s8(vld1_s8(aux_q5sb));
+ }
+
+ constexpr int reads_per_sb = 8; // 8 * 16 bytes each => 32 qs * 4 rows
+ for (int k = 0; k < reads_per_sb; k++) {
+ const int8x16_t q8_blk0 = vld1q_s8(q8_ptr[b].qs + sb * 256 + 16 * k);
+ const int8x16_t q8_blk1 = vld1q_s8(q8_ptr[b].qs + sb * 256 + 16 * k + 128);
+
+ // 0..3 & 32..35
+ const uint8x16_t q5_0123 = vld1q_u8(q5_ptr[b].qs + sb * QK_K + 32 * k);
+ const uint8x16_t q5_4567 = vld1q_u8(q5_ptr[b].qs + sb * QK_K + 32 * k + 16);
+
+ // NOTE: This is the only difference with q4_K
+ const uint8x16_t hbit_lo_0123 = vandq_u8(qh[0][k], mone);
+ const uint8x16_t hbit_hi_0123 = vshlq_n_u8(vandq_u8(qh[0][k], mtwo), 3);
+ qh[0][k] = vshrq_n_u8(qh[0][k], 2);
+ const uint8x16_t hbit_lo_4567 = vandq_u8(qh[1][k], mone);
+ const uint8x16_t hbit_hi_4567 = vshlq_n_u8(vandq_u8(qh[1][k], mtwo), 3);
+ qh[1][k] = vshrq_n_u8(qh[1][k], 2);
+ // From here, same as q4_K
+
+ const int8x16_t q5_0123_lo =
+ vreinterpretq_s8_u8(vsliq_n_u8(vandq_u8(q5_0123, m4b), hbit_lo_0123, 4));
+ const int8x16_t q5_0123_hi =
+ vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q5_0123, 4), hbit_hi_0123));
+
+ acc_lo[0] = vdotq_laneq_s32(acc_lo[0], q5_0123_lo, q8_blk0, 0); // 0..3 r0 c0123
+ acc_lo[1] = vdotq_laneq_s32(acc_lo[1], q5_0123_lo, q8_blk0, 1); // 0..3 r1 c0123
+ acc_lo[2] = vdotq_laneq_s32(acc_lo[2], q5_0123_lo, q8_blk0, 2); // 0..3 r2 c0123
+ acc_lo[3] = vdotq_laneq_s32(acc_lo[3], q5_0123_lo, q8_blk0, 3); // 0..3 r3 c0123
+
+ acc_hi[0] = vdotq_laneq_s32(acc_hi[0], q5_0123_hi, q8_blk1, 0); // 32..35 r0 c0123
+ acc_hi[1] = vdotq_laneq_s32(acc_hi[1], q5_0123_hi, q8_blk1, 1); // 32..35 r1 c0123
+ acc_hi[2] = vdotq_laneq_s32(acc_hi[2], q5_0123_hi, q8_blk1, 2); // 32..35 r2 c0123
+ acc_hi[3] = vdotq_laneq_s32(acc_hi[3], q5_0123_hi, q8_blk1, 3); // 32..35 r3 c0123
+
+ const int8x16_t q5_4567_lo =
+ vreinterpretq_s8_u8(vsliq_n_u8(vandq_u8(q5_4567, m4b), hbit_lo_4567, 4));
+ const int8x16_t q5_4567_hi =
+ vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q5_4567, 4), hbit_hi_4567));
+
+ acc_lo[4] = vdotq_laneq_s32(acc_lo[4], q5_4567_lo, q8_blk0, 0); // 0..3 r0 c4567
+ acc_lo[5] = vdotq_laneq_s32(acc_lo[5], q5_4567_lo, q8_blk0, 1); // 0..3 r1 c4567
+ acc_lo[6] = vdotq_laneq_s32(acc_lo[6], q5_4567_lo, q8_blk0, 2); // 0..3 r2 c4567
+ acc_lo[7] = vdotq_laneq_s32(acc_lo[7], q5_4567_lo, q8_blk0, 3); // 0..3 r3 c4567
+
+ acc_hi[4] = vdotq_laneq_s32(acc_hi[4], q5_4567_hi, q8_blk1, 0); // 32..35 r0 c4567
+ acc_hi[5] = vdotq_laneq_s32(acc_hi[5], q5_4567_hi, q8_blk1, 1); // 32..35 r1 c4567
+ acc_hi[6] = vdotq_laneq_s32(acc_hi[6], q5_4567_hi, q8_blk1, 2); // 32..35 r2 c4567
+ acc_hi[7] = vdotq_laneq_s32(acc_hi[7], q5_4567_hi, q8_blk1, 3); // 32..35 r3 c4567
+ }
+
+ // Scale and bias application
+ // acc is stored interleaved to match output layout
+ const int16x4_t sc_0123_lo = vget_low_s16(q5sb_scales[0]);
+ const int16x4_t sc_4567_lo = vget_high_s16(q5sb_scales[0]);
+ const int16x4_t sc_0123_hi = vget_low_s16(q5sb_scales[1]);
+ const int16x4_t sc_4567_hi = vget_high_s16(q5sb_scales[1]);
+ for (int row = 0; row < q8_k_blocklen; row++) {
+ // Bias correction
+ // row c0123 blk0 and blk1
+ const float32x4_t sumf_0123 =
+ vcvtq_f32_s32(vaddq_s32(vmulq_s32(vmovl_s16(sc_0123_lo), acc_lo[row]),
+ vmulq_s32(vmovl_s16(sc_0123_hi), acc_hi[row])));
+ acc_f32[2 * row] = vfmaq_f32(acc_f32[2 * row], sbd_scale_0123[row], sumf_0123);
+
+ // row c4567 blk0 and blk1
+ const float32x4_t sumf_4567 =
+ vcvtq_f32_s32(vaddq_s32(vmulq_s32(vmovl_s16(sc_4567_lo), acc_lo[row + 4]),
+ vmulq_s32(vmovl_s16(sc_4567_hi), acc_hi[row + 4])));
+ acc_f32[2 * row + 1] = vfmaq_f32(acc_f32[2 * row + 1], sbd_scale_4567[row], sumf_4567);
+
+ // Bias
+ const int16x4_t bsums_vec_lo = vdup_n_s16(bsums_arr[sb][row * 2]);
+ const int16x4_t bsums_vec_hi = vdup_n_s16(bsums_arr[sb][row * 2 + 1]);
+
+ // row c0123 blk0 and blk1
+ bias_acc[2 * row] = vmlal_s16(bias_acc[2 * row], bsums_vec_lo, vget_low_s16(q5sb_mins[0]));
+ bias_acc[2 * row] = vmlal_s16(bias_acc[2 * row], bsums_vec_hi, vget_low_s16(q5sb_mins[1]));
+
+ // row c4567 blk0 and blk1
+ bias_acc[2 * row + 1] =
+ vmlal_s16(bias_acc[2 * row + 1], bsums_vec_lo, vget_high_s16(q5sb_mins[0]));
+ bias_acc[2 * row + 1] =
+ vmlal_s16(bias_acc[2 * row + 1], bsums_vec_hi, vget_high_s16(q5sb_mins[1]));
+ }
+ } // for sb
+
+ for (int row = 0; row < q8_k_blocklen; row++) {
+ acc_f32[2 * row] = vmlsq_f32(acc_f32[2 * row], vcvtq_f32_s32(bias_acc[2 * row]), sbd_min_0123[row]);
+ acc_f32[2 * row + 1] =
+ vmlsq_f32(acc_f32[2 * row + 1], vcvtq_f32_s32(bias_acc[2 * row + 1]), sbd_min_4567[row]);
+ }
+ } // for b
+
+ for (int i = 0; i < q8_k_blocklen; i++) {
+ int row = y * q8_k_blocklen + i;
+ for (int j = 0; j < 2; j++) {
+ int col = x * ncols_interleaved + j * 4;
+ int offset = row * bs + col;
+ vst1q_f32(s + offset, acc_f32[2 * i + j]);
+ }
+ }
+ } // for x
+ } // for y
+ return;
+#endif // defined(__aarch64__) && defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
+ ggml_gemm_q5_K_8x4_q8_K_generic(n, s, bs, vx, vy, nr, nc);
+}
+
void ggml_gemm_q4_K_8x8_q8_K(int n,
float * GGML_RESTRICT s,
size_t bs,
}
}
+template <int M, int N>
+static void ggml_gemv_q5_K_NxM_q8_K_generic_impl(int n,
+ float * GGML_RESTRICT s,
+ size_t bs,
+ const void * GGML_RESTRICT vx,
+ const void * GGML_RESTRICT vy,
+ int nr,
+ int nc) {
+ constexpr int blocklen = M;
+ constexpr int ncols_interleaved = N;
+ const int qk = QK_K;
+ const int nb = n / qk;
+ static const uint32_t kmask1 = 0x3f3f3f3f;
+ static const uint32_t kmask2 = 0x0f0f0f0f;
+ static const uint32_t kmask3 = 0x03030303;
+
+ assert(n % qk == 0);
+ assert(nc % ncols_interleaved == 0);
+
+ UNUSED(bs);
+ UNUSED(nr);
+
+ float sumf[ncols_interleaved];
+ float sum_minf[ncols_interleaved];
+ uint32_t utmp[32];
+ int sumi1;
+ int sumi2;
+ int sumi;
+
+ const block_q8_K * a_ptr = (const block_q8_K *) vy;
+ for (int x = 0; x < nc / ncols_interleaved; x++) {
+ const block_q5_Kx8 * b_ptr = (const block_q5_Kx8 *) vx + (x * nb);
+
+ for (int j = 0; j < ncols_interleaved; j++) {
+ sumf[j] = 0.0;
+ sum_minf[j] = 0.0;
+ }
+ for (int l = 0; l < nb; l++) {
+ for (int sb = 0; sb < 8; sb++) {
+ memcpy(utmp + sb * 4, b_ptr[l].scales + sb * K_SCALE_SIZE, K_SCALE_SIZE);
+ utmp[sb * 4 + 3] = ((utmp[sb * 4 + 2] >> 4) & kmask2) | (((utmp[sb * 4 + 1] >> 6) & kmask3) << 4);
+ const uint32_t uaux_0 = utmp[sb * 4 + 1] & kmask1;
+ utmp[sb * 4 + 1] = (utmp[sb * 4 + 2] & kmask2) | (((utmp[sb * 4 + 0] >> 6) & kmask3) << 4);
+ utmp[sb * 4 + 2] = uaux_0;
+ utmp[sb * 4 + 0] &= kmask1;
+ }
+ for (int k = 0; k < (qk / (2 * blocklen)); k++) {
+ constexpr int scale_stride = 32;
+ uint8_t * scales_0 = (uint8_t *) utmp + (k / (32 / blocklen)) * scale_stride;
+ uint8_t * scales_1 = (uint8_t *) utmp + (k / (32 / blocklen)) * scale_stride + 16;
+
+ const int qh_shift = (k / (32 / blocklen)) * 2;
+ for (int j = 0; j < ncols_interleaved; j++) {
+ sumi1 = 0;
+ sumi2 = 0;
+ sumi = 0;
+ for (int i = 0; i < blocklen; ++i) {
+ const int b_qs_offset = k * ncols_interleaved * blocklen + j * blocklen + i;
+
+ const int qh_idx = (k * blocklen + i) % 32;
+ const int qh_chunk = qh_idx / blocklen;
+ const int qh_pos = qh_idx % blocklen;
+ const int b_qh_offset = qh_chunk * (blocklen * ncols_interleaved) + j * blocklen + qh_pos;
+
+ const uint8_t qh_val = b_ptr[l].qh[b_qh_offset];
+ const uint8_t h0 = (qh_val >> qh_shift) & 1;
+ const uint8_t h1 = (qh_val >> (qh_shift + 1)) & 1;
+
+ const int v0 = (int8_t) ((b_ptr[l].qs[b_qs_offset] & 0xF) | (h0 << 4));
+ const int v1 = (int8_t) ((b_ptr[l].qs[b_qs_offset] >> 4) | (h1 << 4));
+
+ const int q8_offset = (k / (32 / blocklen)) * 64 + (k % (32 / blocklen)) * blocklen + i;
+
+ sumi1 = (v0 * a_ptr[l].qs[q8_offset]);
+ sumi2 = (v1 * a_ptr[l].qs[q8_offset + 32]);
+ sumi1 = sumi1 * scales_0[j];
+ sumi2 = sumi2 * scales_1[j];
+ sumi += sumi1 + sumi2;
+ }
+ sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * a_ptr[l].d;
+ }
+ }
+ for (int sb = 0; sb < 8; sb++) {
+ uint8_t * mins = (uint8_t *) utmp + 8 + sb * 16;
+ for (int j = 0; j < ncols_interleaved; j++) {
+ sum_minf[j] += mins[j] * (a_ptr[l].bsums[sb * 2] + a_ptr[l].bsums[sb * 2 + 1]) *
+ GGML_CPU_FP16_TO_FP32(b_ptr[l].dmin[j]) * a_ptr[l].d;
+ }
+ }
+ }
+ for (int j = 0; j < ncols_interleaved; j++) {
+ s[x * ncols_interleaved + j] = sumf[j] - sum_minf[j];
+ }
+ }
+}
+
+template <int M, int N>
+static void ggml_gemm_q5_K_NxM_q8_K_generic_impl(int n,
+ float * GGML_RESTRICT s,
+ size_t bs,
+ const void * GGML_RESTRICT vx,
+ const void * GGML_RESTRICT vy,
+ int nr,
+ int nc) {
+ constexpr int blocklen = M;
+ constexpr int ncols_interleaved = N;
+ const int qk = QK_K;
+ const int nb = n / qk;
+ static const uint32_t kmask1 = 0x3f3f3f3f;
+ static const uint32_t kmask2 = 0x0f0f0f0f;
+ static const uint32_t kmask3 = 0x03030303;
+
+ assert(n % qk == 0);
+ assert(nr % 4 == 0);
+ assert(nc % ncols_interleaved == 0);
+
+ float sumf[4][ncols_interleaved];
+ float sum_minf[4][ncols_interleaved];
+ uint32_t utmp[32];
+ int sumi1;
+ int sumi2;
+ int sumi;
+
+ for (int y = 0; y < nr / 4; y++) {
+ const block_q8_Kx4 * a_ptr = (const block_q8_Kx4 *) vy + (y * nb);
+ for (int x = 0; x < nc / ncols_interleaved; x++) {
+ const block_q5_Kx8 * b_ptr = (const block_q5_Kx8 *) vx + (x * nb);
+ for (int m = 0; m < 4; m++) {
+ for (int j = 0; j < ncols_interleaved; j++) {
+ sumf[m][j] = 0.0;
+ sum_minf[m][j] = 0.0;
+ }
+ }
+ for (int l = 0; l < nb; l++) {
+ for (int sb = 0; sb < 8; sb++) {
+ memcpy(utmp + sb * 4, b_ptr[l].scales + sb * K_SCALE_SIZE, K_SCALE_SIZE);
+ utmp[sb * 4 + 3] = ((utmp[sb * 4 + 2] >> 4) & kmask2) | (((utmp[sb * 4 + 1] >> 6) & kmask3) << 4);
+ const uint32_t uaux_0 = utmp[sb * 4 + 1] & kmask1;
+ utmp[sb * 4 + 1] = (utmp[sb * 4 + 2] & kmask2) | (((utmp[sb * 4 + 0] >> 6) & kmask3) << 4);
+ utmp[sb * 4 + 2] = uaux_0;
+ utmp[sb * 4 + 0] &= kmask1;
+ }
+ for (int k = 0; k < (qk / (2 * blocklen)); k++) {
+ constexpr int scale_stride = 32;
+ uint8_t * scales_0 = (uint8_t *) utmp + (k / (32 / blocklen)) * scale_stride;
+ uint8_t * scales_1 = (uint8_t *) utmp + (k / (32 / blocklen)) * scale_stride + 16;
+
+ const int qh_shift = (k / (32 / blocklen)) * 2;
+ for (int m = 0; m < 4; m++) {
+ for (int j = 0; j < ncols_interleaved; j++) {
+ sumi1 = 0;
+ sumi2 = 0;
+ sumi = 0;
+ for (int i = 0; i < blocklen; ++i) {
+ const int b_qs_offset = k * ncols_interleaved * blocklen + j * blocklen + i;
+
+ const int qh_idx = (k * blocklen + i) % 32;
+ const int qh_chunk = qh_idx / blocklen;
+ const int qh_pos = qh_idx % blocklen;
+ const int b_qh_offset =
+ qh_chunk * (blocklen * ncols_interleaved) + j * blocklen + qh_pos;
+
+ const uint8_t qh_val = b_ptr[l].qh[b_qh_offset];
+ const uint8_t h0 = (qh_val >> qh_shift) & 1;
+ const uint8_t h1 = (qh_val >> (qh_shift + 1)) & 1;
+
+ const int v0 = (int8_t) ((b_ptr[l].qs[b_qs_offset] & 0xF) | (h0 << 4));
+ const int v1 = (int8_t) ((b_ptr[l].qs[b_qs_offset] >> 4) | (h1 << 4));
+
+ const int q8_offset = (k / (32 / blocklen)) * 256 +
+ (k % (32 / blocklen)) * 4 * blocklen + m * blocklen + i;
+
+ sumi1 = (v0 * a_ptr[l].qs[q8_offset]);
+ sumi2 = (v1 * a_ptr[l].qs[q8_offset + 128]);
+ sumi1 = sumi1 * scales_0[j];
+ sumi2 = sumi2 * scales_1[j];
+ sumi += sumi1 + sumi2;
+ }
+ sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * a_ptr[l].d[m];
+ }
+ }
+ }
+ for (int sb = 0; sb < 8; sb++) {
+ uint8_t * mins = (uint8_t *) utmp + 8 + sb * 16;
+ for (int m = 0; m < 4; m++) {
+ const int16_t * bsums = a_ptr[l].bsums + (sb * 8) + (m * 4) - ((sb % 2) * 6);
+ for (int j = 0; j < ncols_interleaved; j++) {
+ sum_minf[m][j] += mins[j] * (bsums[0] + bsums[1]) *
+ GGML_CPU_FP16_TO_FP32(b_ptr[l].dmin[j]) * a_ptr[l].d[m];
+ }
+ }
+ }
+ }
+ for (int m = 0; m < 4; m++) {
+ for (int j = 0; j < ncols_interleaved; j++) {
+ s[(y * 4 + m) * bs + x * ncols_interleaved + j] = sumf[m][j] - sum_minf[m][j];
+ }
+ }
+ }
+ }
+}
+
extern "C" {
void ggml_gemv_q4_0_4x4_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc) {
}
}
-void ggml_gemv_q5_K_8x8_q8_K_generic(int n,
- float * GGML_RESTRICT s,
- size_t bs,
- const void * GGML_RESTRICT vx,
- const void * GGML_RESTRICT vy,
- int nr,
- int nc) {
- const int qk = QK_K;
- const int nb = n / qk;
- const int ncols_interleaved = 8;
- const int blocklen = 8;
- static const uint32_t kmask1 = 0x3f3f3f3f;
- static const uint32_t kmask2 = 0x0f0f0f0f;
- static const uint32_t kmask3 = 0x03030303;
-
- assert(n % qk == 0);
- assert(nc % ncols_interleaved == 0);
-
- UNUSED(bs);
- UNUSED(nr);
-
- float sumf[8];
- float sum_minf[8];
- uint32_t utmp[32];
- int sumi1;
- int sumi2;
- int sumi;
-
- const block_q8_K * a_ptr = (const block_q8_K *) vy;
- for (int x = 0; x < nc / ncols_interleaved; x++) {
- const block_q5_Kx8 * b_ptr = (const block_q5_Kx8 *) vx + (x * nb);
-
- for (int j = 0; j < ncols_interleaved; j++) {
- sumf[j] = 0.0;
- sum_minf[j] = 0.0;
- }
- for (int l = 0; l < nb; l++) {
- for (int sb = 0; sb < 8; sb++) {
- memcpy(utmp + sb * 4, b_ptr[l].scales + sb * 12, 12);
- utmp[sb * 4 + 3] = ((utmp[sb * 4 + 2] >> 4) & kmask2) | (((utmp[sb * 4 + 1] >> 6) & kmask3) << 4);
- const uint32_t uaux_0 = utmp[sb * 4 + 1] & kmask1;
- utmp[sb * 4 + 1] = (utmp[sb * 4 + 2] & kmask2) | (((utmp[sb * 4 + 0] >> 6) & kmask3) << 4);
- utmp[sb * 4 + 2] = uaux_0;
- utmp[sb * 4 + 0] &= kmask1;
- }
- for (int k = 0; k < (qk / (2 * blocklen)); k++) {
- uint8_t * scales_0 = (uint8_t *) utmp + (k / 4) * 32;
- uint8_t * scales_1 = (uint8_t *) utmp + (k / 4) * 32 + 16;
-
- const int qh_shift = (k / 4) * 2;
- for (int j = 0; j < ncols_interleaved; j++) {
- sumi1 = 0;
- sumi2 = 0;
- sumi = 0;
- for (int i = 0; i < blocklen; ++i) {
- const int b_qs_offset = k * ncols_interleaved * blocklen + j * blocklen + i;
-
- const int qh_idx = (k * 8 + i) % 32;
- const int qh_chunk = qh_idx / 8;
- const int qh_pos = qh_idx % 8;
- const int b_qh_offset = qh_chunk * 64 + j * 8 + qh_pos;
-
- const uint8_t qh_val = b_ptr[l].qh[b_qh_offset];
- const uint8_t h0 = (qh_val >> qh_shift) & 1;
- const uint8_t h1 = (qh_val >> (qh_shift + 1)) & 1;
-
- const int v0 = (int8_t) ((b_ptr[l].qs[b_qs_offset] & 0xF) | (h0 << 4));
- const int v1 = (int8_t) ((b_ptr[l].qs[b_qs_offset] >> 4) | (h1 << 4));
-
- const int q8_offset = (k >> 2) * 64 + (k % 4) * blocklen + i;
+void ggml_gemv_q5_K_8x4_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc) {
+ ggml_gemv_q5_K_NxM_q8_K_generic_impl<4, 8>(n, s, bs, vx, vy, nr, nc);
+}
- sumi1 = (v0 * a_ptr[l].qs[q8_offset]);
- sumi2 = (v1 * a_ptr[l].qs[q8_offset + 32]);
- sumi1 = sumi1 * scales_0[j];
- sumi2 = sumi2 * scales_1[j];
- sumi += sumi1 + sumi2;
- }
- sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * a_ptr[l].d;
- }
- }
- for (int sb = 0; sb < 8; sb++) {
- uint8_t * mins = (uint8_t *) utmp + 8 + sb * 16;
- for (int j = 0; j < ncols_interleaved; j++) {
- sum_minf[j] += mins[j] * (a_ptr[l].bsums[sb * 2] + a_ptr[l].bsums[sb * 2 + 1]) *
- GGML_CPU_FP16_TO_FP32(b_ptr[l].dmin[j]) * a_ptr[l].d;
- }
- }
- }
- for (int j = 0; j < ncols_interleaved; j++) {
- s[x * ncols_interleaved + j] = sumf[j] - sum_minf[j];
- }
- }
+void ggml_gemv_q5_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc) {
+ ggml_gemv_q5_K_NxM_q8_K_generic_impl<8, 8>(n, s, bs, vx, vy, nr, nc);
}
}
}
-void ggml_gemm_q5_K_8x8_q8_K_generic(int n,
- float * GGML_RESTRICT s,
- size_t bs,
- const void * GGML_RESTRICT vx,
- const void * GGML_RESTRICT vy,
- int nr,
- int nc) {
- const int qk = QK_K;
- const int nb = n / qk;
- const int ncols_interleaved = 8;
- const int blocklen = 8;
-
- constexpr uint32_t kmask1 = 0x3f3f3f3f;
- constexpr uint32_t kmask2 = 0x0f0f0f0f;
- constexpr uint32_t kmask3 = 0x03030303;
-
- assert(n % qk == 0);
- assert(nr % 4 == 0);
- assert(nc % ncols_interleaved == 0);
-
- float sumf[4][8];
- float sum_minf[4][8];
- uint32_t utmp[32];
- int sumi1;
- int sumi2;
- int sumi;
-
- for (int y = 0; y < nr / 4; y++) {
- const block_q8_Kx4 * a_ptr = (const block_q8_Kx4 *) vy + (y * nb);
- for (int x = 0; x < nc / ncols_interleaved; x++) {
- const block_q5_Kx8 * b_ptr = (const block_q5_Kx8 *) vx + (x * nb);
- for (int m = 0; m < 4; m++) {
- for (int j = 0; j < ncols_interleaved; j++) {
- sumf[m][j] = 0.0;
- sum_minf[m][j] = 0.0;
- }
- }
- for (int l = 0; l < nb; l++) {
- for (int sb = 0; sb < 8; sb++) {
- memcpy(utmp + sb * 4, b_ptr[l].scales + sb * 12, 12);
- utmp[sb * 4 + 3] = ((utmp[sb * 4 + 2] >> 4) & kmask2) | (((utmp[sb * 4 + 1] >> 6) & kmask3) << 4);
- const uint32_t uaux_0 = utmp[sb * 4 + 1] & kmask1;
- utmp[sb * 4 + 1] = (utmp[sb * 4 + 2] & kmask2) | (((utmp[sb * 4 + 0] >> 6) & kmask3) << 4);
- utmp[sb * 4 + 2] = uaux_0;
- utmp[sb * 4 + 0] &= kmask1;
- }
- for (int k = 0; k < (qk / (2 * blocklen)); k++) {
- uint8_t * scales_0 = (uint8_t *) utmp + (k / 4) * 32;
- uint8_t * scales_1 = (uint8_t *) utmp + (k / 4) * 32 + 16;
-
- const int qh_shift = (k / 4) * 2;
- for (int m = 0; m < 4; m++) {
- for (int j = 0; j < ncols_interleaved; j++) {
- sumi1 = 0;
- sumi2 = 0;
- sumi = 0;
- for (int i = 0; i < blocklen; ++i) {
- const int b_qs_offset = k * ncols_interleaved * blocklen + j * blocklen + i;
-
- const int qh_idx = (k * 8 + i) % 32;
- const int qh_chunk = qh_idx / 8;
- const int qh_pos = qh_idx % 8;
- const int b_qh_offset = qh_chunk * 64 + j * 8 + qh_pos;
-
- const uint8_t qh_val = b_ptr[l].qh[b_qh_offset];
- const uint8_t h0 = (qh_val >> qh_shift) & 1;
- const uint8_t h1 = (qh_val >> (qh_shift + 1)) & 1;
-
- const int v0 = (int8_t) ((b_ptr[l].qs[b_qs_offset] & 0xF) | (h0 << 4));
- const int v1 = (int8_t) ((b_ptr[l].qs[b_qs_offset] >> 4) | (h1 << 4));
-
- const int q8_offset = (k >> 2) * 256 + (k % 4) * 4 * blocklen + m * blocklen + i;
+void ggml_gemm_q5_K_8x4_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc) {
+ ggml_gemm_q5_K_NxM_q8_K_generic_impl<4, 8>(n, s, bs, vx, vy, nr, nc);
+}
- sumi1 = (v0 * a_ptr[l].qs[q8_offset]);
- sumi2 = (v1 * a_ptr[l].qs[q8_offset + 128]);
- sumi1 = sumi1 * scales_0[j];
- sumi2 = sumi2 * scales_1[j];
- sumi += sumi1 + sumi2;
- }
- sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * a_ptr[l].d[m];
- }
- }
- }
- for (int sb = 0; sb < 8; sb++) {
- uint8_t * mins = (uint8_t *) utmp + 8 + sb * 16;
- for (int m = 0; m < 4; m++) {
- const int16_t * bsums = a_ptr[l].bsums + (sb * 8) + (m * 4) - ((sb % 2) * 6);
- for (int j = 0; j < ncols_interleaved; j++) {
- sum_minf[m][j] += mins[j] * (bsums[0] + bsums[1]) *
- GGML_CPU_FP16_TO_FP32(b_ptr[l].dmin[j]) * a_ptr[l].d[m];
- }
- }
- }
- }
- for (int m = 0; m < 4; m++) {
- for (int j = 0; j < ncols_interleaved; j++) {
- s[(y * 4 + m) * bs + x * ncols_interleaved + j] = sumf[m][j] - sum_minf[m][j];
- }
- }
- }
- }
+void ggml_gemm_q5_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc) {
+ ggml_gemm_q5_K_NxM_q8_K_generic_impl<8, 8>(n, s, bs, vx, vy, nr, nc);
}
void ggml_gemm_q6_K_8x4_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc) {
const int end = QK_K * 4 / blck_size_interleave;
- // Interleave Q5_K quants by taking 8 bytes at a time
+ // Interleave Q5_K quants by taking blck_size_interleave bytes at a time
for (int i = 0; i < end; ++i) {
int src_id = i % 8;
int src_offset = (i / 8) * blck_size_interleave;
int dst_offset = i * blck_size_interleave;
- uint64_t elems;
- memcpy(&elems, &in[src_id].qs[src_offset], sizeof(uint64_t));
- memcpy(&out.qs[dst_offset], &elems, sizeof(uint64_t));
+ memcpy(&out.qs[dst_offset], &in[src_id].qs[src_offset], blck_size_interleave);
}
- // Repeat for low bits 8 bytes at a time as well, since
+ // Repeat for high bits with the same chunk size, since
// the high bits are interleaved in Q5_K and the index is
// qh_idx = (qs_idx % 32);
// qh_val = qh[qh_idx] >> (qs_idx / 32);
int src_offset = (i / 8) * blck_size_interleave;
int dst_offset = i * blck_size_interleave;
- uint64_t elems;
- memcpy(&elems, &in[src_id].qh[src_offset], sizeof(uint64_t));
- memcpy(&out.qh[dst_offset], &elems, sizeof(uint64_t));
+ memcpy(&out.qh[dst_offset], &in[src_id].qh[src_offset], blck_size_interleave);
}
// The below logic is copied over from Q4_K
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q5_K);
- GGML_ASSERT(interleave_block == 8);
+ GGML_ASSERT(interleave_block == 4 || interleave_block == 8);
constexpr int nrows_interleaved = 8;
block_q5_Kx8 * dst = (block_q5_Kx8 *) t->data;
return repack_q2_K_to_q2_K_8_bl(t, 8, data, data_size);
}
+template <> int repack<block_q5_K, 4, 8>(struct ggml_tensor * t, const void * data, size_t data_size) {
+ return repack_q5_K_to_q5_K_8_bl(t, 4, data, data_size);
+}
+
template <> int repack<block_q5_K, 8, 8>(struct ggml_tensor * t, const void * data, size_t data_size) {
return repack_q5_K_to_q5_K_8_bl(t, 8, data, data_size);
}
ggml_gemv_q4_K_8x8_q8_K(n, s, bs, vx, vy, nr, nc);
}
+template <> void gemv<block_q5_K, 4, 8, GGML_TYPE_Q8_K>(int n, float * s, size_t bs, const void * vx, const void * vy, int nr, int nc) {
+ ggml_gemv_q5_K_8x4_q8_K(n, s, bs, vx, vy, nr, nc);
+}
+
template <> void gemv<block_q5_K, 8, 8, GGML_TYPE_Q8_K>(int n, float * s, size_t bs, const void * vx, const void * vy, int nr, int nc) {
ggml_gemv_q5_K_8x8_q8_K(n, s, bs, vx, vy, nr, nc);
}
ggml_gemm_q4_K_8x8_q8_K(n, s, bs, vx, vy, nr, nc);
}
+template <> void gemm<block_q5_K, 4, 8, GGML_TYPE_Q8_K>(int n, float * s, size_t bs, const void * vx, const void * vy, int nr, int nc) {
+ ggml_gemm_q5_K_8x4_q8_K(n, s, bs, vx, vy, nr, nc);
+}
+
template <> void gemm<block_q5_K, 8, 8, GGML_TYPE_Q8_K>(int n, float * s, size_t bs, const void * vx, const void * vy, int nr, int nc) {
ggml_gemm_q5_K_8x8_q8_K(n, s, bs, vx, vy, nr, nc);
}
static const ggml::cpu::repack::tensor_traits<block_q4_K, 8, 8, GGML_TYPE_Q8_K> q4_K_8x8_q8_K;
// instance for Q5_K
+ static const ggml::cpu::repack::tensor_traits<block_q5_K, 4, 8, GGML_TYPE_Q8_K> q5_K_8x4_q8_K;
static const ggml::cpu::repack::tensor_traits<block_q5_K, 8, 8, GGML_TYPE_Q8_K> q5_K_8x8_q8_K;
// instance for Q6_K
return &q5_K_8x8_q8_K;
}
}
+ if (ggml_cpu_has_neon() && ggml_cpu_has_dotprod()) {
+ if (cur->ne[1] % 8 == 0) {
+ return &q5_K_8x4_q8_K;
+ }
+ }
} else if (cur->type == GGML_TYPE_Q6_K) {
if (ggml_cpu_has_neon() && ggml_cpu_has_matmul_int8()) {
if (cur->ne[1] % 8 == 0) {
void ggml_gemv_q2_K_8x8_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemv_q4_K_8x4_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemv_q4_K_8x8_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemv_q5_K_8x4_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemv_q5_K_8x8_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemv_q6_K_8x4_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemv_q6_K_8x8_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemm_q2_K_8x8_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemm_q4_K_8x4_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemm_q4_K_8x8_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemm_q5_K_8x4_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemm_q5_K_8x8_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemm_q6_K_8x4_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemm_q6_K_8x8_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemv_q2_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemv_q4_K_8x4_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemv_q4_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemv_q5_K_8x4_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemv_q5_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemv_q6_K_8x4_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemv_q6_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemm_q2_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemm_q4_K_8x4_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemm_q4_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
+void ggml_gemm_q5_K_8x4_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemm_q5_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemm_q6_K_8x4_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
void ggml_gemm_q6_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc);
overview / pkg / ggml / sources / llama.cpp / commitdiff