Q8_K_R8: Fastest quantized matrix multiplications (#141)

* q8_k_r8: fastest matrix multiplication known to human kind

We get PP-512(LLaMA-3.1-8B) = 370 t/s on a Ryzen-7950X!

* q8_k_r8: AVX2

I was worried that we don't have enough vector registrers on
AVX2, but it looks like it handles it just fine. We get
PP-512(LLaMA-3.1-8B) = 354 t/s on a Ryzen-5975WX.
Slightly slower than the Zen4 version with double the threads,
but still a huge upgrade compared to Q8_0_R4.

* q8_k_r4: NEON

We get PP-512(LLaMA-3.1-8B) = 159.2 t/s.
Compare this to the 128 t/s we have fr Q8_0_R4.

* q8_k_r4: go to signed ints

Why?
* On AVX2 _mm256_maddubs_epi16() may overflow, so we need to
  stay within the signed int range and use _mm256_sign_epi8.
  Not yet tested on the AVX2 comp, vut expect major slowdown.
* It is almost 10% faster on ARM_NEON. Somehow the veorrq_u8()
  needed tto convert from unsigned to signed seems to be extremely
  slow on the M2-Max
* We only lose ~0.5% in oerformance on Zen4 (there the exclusive
  or that we now use to convert fro signed to unsigned seems to be
  much faster than on M2-Max)

* Shutup useless compiler warnings

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>

6 files changed, 282 insertions, 5 deletions

diff --git a/ggml/src/ggml-common.h b/ggml/src/ggml-common.h
index 2cacc711..d77ba12c 100644
--- a/ggml/src/ggml-common.h
+++ b/ggml/src/ggml-common.h
@@ -382,6 +382,12 @@ typedef struct {
 } block_q8_K128;
 static_assert(sizeof(block_q8_K128) == sizeof(float) + 128, "wrong q8_K128 block size/padding");
 
+typedef struct {
+    ggml_half d[8];         // delta
+    int8_t    qs[8*QK_K];   // quants, stored as unsigned ints
+} block_q8_k_r8;
+static_assert(sizeof(block_q8_k_r8) == 8*sizeof(ggml_half) + 8*QK_K, "wrong q8_k_r8 block size/padding");
+
 // (Almost) "true" 2-bit quantization.
 // Due to the need to use blocks as per ggml design, it ends up using
 // 2.0625 bpw because of the 16-bit scale for each block of 256.
diff --git a/ggml/src/ggml-quants.c b/ggml/src/ggml-quants.c
index 64bd9459..f12c9fe8 100644
--- a/ggml/src/ggml-quants.c
+++ b/ggml/src/ggml-quants.c
@@ -15208,6 +15208,7 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte
         case GGML_TYPE_Q5_K_R4: break;
         case GGML_TYPE_Q6_K_R4: break;
         case GGML_TYPE_IQ4_K_R4: break;
+        case GGML_TYPE_Q8_K_R8: break;
         case GGML_TYPE_Q4_0_4_4:
         case GGML_TYPE_Q4_0_4_8:
             {
diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c
index 26ca7991..772c70c4 100644
--- a/ggml/src/ggml.c
+++ b/ggml/src/ggml.c
@@ -979,6 +979,19 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .nrows                    = 1,
         .row_meta_size            = 0,
     },
+    [GGML_TYPE_Q8_K_R8] = {
+        .type_name                = "q8_k_r8",
+        .blck_size                = QK_K,
+        .type_size                = sizeof(block_q8_k_r8)/8,
+        .is_quantized             = true,
+        .to_float                 = (ggml_to_float_t) dequantize_row_q8_k_r8,
+        .from_float               = quantize_row_q8_k_r8,
+        .from_float_ref           = (ggml_from_float_t) quantize_row_q8_k_r8_ref,
+        .vec_dot                  = vec_dot_q8_k_r8_q8_k,
+        .vec_dot_type             = GGML_TYPE_Q8_KR8,
+        .nrows                    = 1,
+        .row_meta_size            = 0,
+    },
     [GGML_TYPE_IQ2_XXS] = {
         .type_name                = "iq2_xxs",
         .blck_size                = QK_K,
@@ -1197,6 +1210,14 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .from_float               = quantize_row_q8_K32,
         .row_meta_size            = 0,
     },
+    [GGML_TYPE_Q8_KR8] = {
+        .type_name                = "q8_KR8",
+        .blck_size                = QK_K,
+        .type_size                = sizeof(block_q8_K),
+        .is_quantized             = true,
+        .from_float               = quantize_row_q8_KR8,
+        .row_meta_size            = 0,
+    },
     [GGML_TYPE_BF16] = {
         .type_name                = "bf16",
         .blck_size                = 1,
@@ -4105,6 +4126,7 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) {
         case GGML_FTYPE_MOSTLY_Q5_K_R4:       wtype = GGML_TYPE_Q5_K_R4;  break;
         case GGML_FTYPE_MOSTLY_Q6_K:          wtype = GGML_TYPE_Q6_K;     break;
         case GGML_FTYPE_MOSTLY_Q6_K_R4:       wtype = GGML_TYPE_Q6_K_R4;  break;
+        case GGML_FTYPE_MOSTLY_Q8_K_R8:       wtype = GGML_TYPE_Q8_K_R8;  break;
         case GGML_FTYPE_MOSTLY_IQ2_XXS:       wtype = GGML_TYPE_IQ2_XXS;  break;
         case GGML_FTYPE_MOSTLY_IQ2_XS:        wtype = GGML_TYPE_IQ2_XS;   break;
         case GGML_FTYPE_MOSTLY_IQ3_XXS:       wtype = GGML_TYPE_IQ3_XXS;  break;
@@ -10641,6 +10663,7 @@ static void ggml_compute_forward_add(
         case GGML_TYPE_Q5_K_R4:
         case GGML_TYPE_Q6_K:
         case GGML_TYPE_Q6_K_R4:
+        case GGML_TYPE_Q8_K_R8:
         case GGML_TYPE_IQ2_XXS:
         case GGML_TYPE_IQ2_XS:
         case GGML_TYPE_IQ3_XXS:
@@ -11096,6 +11119,7 @@ static void ggml_compute_forward_add1(
         case GGML_TYPE_Q5_K_R4:
         case GGML_TYPE_Q6_K:
         case GGML_TYPE_Q6_K_R4:
+        case GGML_TYPE_Q8_K_R8:
         case GGML_TYPE_IQ2_XXS:
         case GGML_TYPE_IQ2_XS:
         case GGML_TYPE_IQ3_XXS:
@@ -11248,6 +11272,7 @@ static void ggml_compute_forward_acc(
         case GGML_TYPE_Q5_K_R4:
         case GGML_TYPE_Q6_K:
         case GGML_TYPE_Q6_K_R4:
+        case GGML_TYPE_Q8_K_R8:
         case GGML_TYPE_IQ2_XXS:
         case GGML_TYPE_IQ2_XS:
         case GGML_TYPE_IQ3_XXS:
@@ -14446,6 +14471,7 @@ static void ggml_compute_forward_out_prod(
         case GGML_TYPE_Q5_K_R4:
         case GGML_TYPE_Q6_K:
         case GGML_TYPE_Q6_K_R4:
+        case GGML_TYPE_Q8_K_R8:
         case GGML_TYPE_IQ2_XXS:
         case GGML_TYPE_IQ2_XS:
         case GGML_TYPE_IQ3_XXS:
@@ -14838,6 +14864,7 @@ static void ggml_compute_forward_set(
         case GGML_TYPE_Q5_K_R4:
         case GGML_TYPE_Q6_K:
         case GGML_TYPE_Q6_K_R4:
+        case GGML_TYPE_Q8_K_R8:
         case GGML_TYPE_IQ2_XXS:
         case GGML_TYPE_IQ2_XS:
         case GGML_TYPE_IQ3_XXS:
@@ -15124,6 +15151,7 @@ static void ggml_compute_forward_get_rows(
         case GGML_TYPE_Q5_K_R4:
         case GGML_TYPE_Q6_K:
         case GGML_TYPE_Q6_K_R4:
+        case GGML_TYPE_Q8_K_R8:
         case GGML_TYPE_IQ2_XXS:
         case GGML_TYPE_IQ2_XS:
         case GGML_TYPE_IQ3_XXS:
@@ -15737,6 +15765,8 @@ static void ggml_compute_forward_clamp(
         case GGML_TYPE_Q5_K_R4:
         case GGML_TYPE_Q6_K:
         case GGML_TYPE_Q6_K_R4:
+        case GGML_TYPE_Q8_K_R8:
+        case GGML_TYPE_Q8_KR8:
         case GGML_TYPE_IQ2_XXS:
         case GGML_TYPE_IQ2_XS:
         case GGML_TYPE_IQ3_XXS:
@@ -22578,6 +22608,7 @@ size_t ggml_quantize_chunk(
         case GGML_TYPE_Q5_K_R4: result = quantize_q5_k_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_Q6_K:    result = quantize_q6_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_Q6_K_R4: result = quantize_q6_k_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q8_K_R8: result = quantize_q8_k_r8(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_IQ2_XXS: result = quantize_iq2_xxs(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_IQ2_XS:  result = quantize_iq2_xs (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_IQ3_XXS: result = quantize_iq3_xxs(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
diff --git a/ggml/src/iqk/iqk_mul_mat.cpp b/ggml/src/iqk/iqk_mul_mat.cpp
index 3f448275..75e5c3c1 100644
--- a/ggml/src/iqk/iqk_mul_mat.cpp
+++ b/ggml/src/iqk/iqk_mul_mat.cpp
@@ -92,6 +92,9 @@ struct DataInfo {
     inline void store(int ix, int iy, __m128 result) const {
         _mm_storeu_ps(dst_row(iy) + ix, result);
     }
+    inline void store(int ix, int iy, __m256 result) const {
+        _mm256_storeu_ps(dst_row(iy) + ix, result);
+    }
 #endif
 #ifdef __ARM_NEON
     inline void store(int ix, int iy, float32x4_t result) const {
@@ -175,6 +178,7 @@ struct MulMat {
             case GGML_TYPE_IQ4_NL_R4:
             case GGML_TYPE_IQ4_XS_R4:
             case GGML_TYPE_IQ2_BN_R4: return 4;
+            case GGML_TYPE_Q8_K_R8: return 8;
             default: return 1;
         }
     }
@@ -3802,6 +3806,76 @@ static void mul_mat_q6_k_r4_q8_k(int n, const void * vx, size_t bx, const DataIn
     }
 }
 
+// The HAVE_FANCY_SIMD should only be #if defined(__AVX512_VNNI__ && defined(__AVX512VL__)
+template <int nrc_y>
+static void mul_mat_q8_k_r8_q8_k(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+    GGML_ASSERT(nrc_x%4 == 0);
+    Q8<nrc_y, block_q8_K> q8(info);
+#ifndef HAVE_FANCY_SIMD
+    auto m1 = _mm256_set1_epi16(1);
+#endif
+    int nbl = n / QK_K;
+    __m256  acc[nrc_y] = {};
+    __m256i isum[nrc_y] = {};
+    __m256i qx[4];
+    for (int ix = 0; ix < nrc_x; ix += 8) {
+        const block_q8_k_r8 * iq8 = (const block_q8_k_r8 *)((const char *)vx + (ix+0)*bx);
+        for (int ibl = 0; ibl < nbl; ++ibl) { // Block of 256
+            auto d4 = _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)iq8[ibl].d));
+            for (int ib = 0; ib < QK_K/16; ++ib) {
+                qx[0] = _mm256_loadu_si256((const __m256i *)iq8[ibl].qs+4*ib+0);
+                qx[1] = _mm256_loadu_si256((const __m256i *)iq8[ibl].qs+4*ib+1);
+                qx[2] = _mm256_loadu_si256((const __m256i *)iq8[ibl].qs+4*ib+2);
+                qx[3] = _mm256_loadu_si256((const __m256i *)iq8[ibl].qs+4*ib+3);
+#ifdef HAVE_FANCY_SIMD
+                qx[0] = _mm256_xor_si256(_mm256_loadu_si256((const __m256i *)iq8[ibl].qs+4*ib+0), _mm256_set1_epi8(-128));
+                qx[1] = _mm256_xor_si256(_mm256_loadu_si256((const __m256i *)iq8[ibl].qs+4*ib+1), _mm256_set1_epi8(-128));
+                qx[2] = _mm256_xor_si256(_mm256_loadu_si256((const __m256i *)iq8[ibl].qs+4*ib+2), _mm256_set1_epi8(-128));
+                qx[3] = _mm256_xor_si256(_mm256_loadu_si256((const __m256i *)iq8[ibl].qs+4*ib+3), _mm256_set1_epi8(-128));
+#else
+                auto s0 = _mm256_sign_epi8(qx[0], qx[0]);
+                auto s1 = _mm256_sign_epi8(qx[1], qx[1]);
+                auto s2 = _mm256_sign_epi8(qx[2], qx[2]);
+                auto s3 = _mm256_sign_epi8(qx[3], qx[3]);
+#endif
+                for (int iy = 0; iy < nrc_y; ++iy) {
+                    auto y128 = _mm_loadu_si128((const __m128i*)q8.y[iy][ibl].qs+ib);
+                    auto y = MM256_SET_M128I(y128, y128);
+#ifdef HAVE_FANCY_SIMD
+                    isum[iy] = _mm256_dpbusd_epi32(isum[iy], qx[0], _mm256_shuffle_epi32(y, 0x00));
+                    isum[iy] = _mm256_dpbusd_epi32(isum[iy], qx[1], _mm256_shuffle_epi32(y, 0x55));
+                    isum[iy] = _mm256_dpbusd_epi32(isum[iy], qx[2], _mm256_shuffle_epi32(y, 0xaa));
+                    isum[iy] = _mm256_dpbusd_epi32(isum[iy], qx[3], _mm256_shuffle_epi32(y, 0xff));
+#else
+                    auto sumi1 = _mm256_madd_epi16(m1, _mm256_maddubs_epi16(s0, _mm256_sign_epi8(_mm256_shuffle_epi32(y, 0x00), qx[0])));
+                    auto sumi2 = _mm256_madd_epi16(m1, _mm256_maddubs_epi16(s1, _mm256_sign_epi8(_mm256_shuffle_epi32(y, 0x55), qx[1])));
+                    auto sumi3 = _mm256_madd_epi16(m1, _mm256_maddubs_epi16(s2, _mm256_sign_epi8(_mm256_shuffle_epi32(y, 0xaa), qx[2])));
+                    auto sumi4 = _mm256_madd_epi16(m1, _mm256_maddubs_epi16(s3, _mm256_sign_epi8(_mm256_shuffle_epi32(y, 0xff), qx[3])));
+                    isum[iy] = _mm256_add_epi32(isum[iy], _mm256_add_epi32(sumi1, sumi2));
+                    isum[iy] = _mm256_add_epi32(isum[iy], _mm256_add_epi32(sumi3, sumi4));
+#endif
+                }
+            }
+#ifdef HAVE_FANCY_SIMD
+            auto m4 = _mm256_mul_ps(d4, _mm256_set1_ps(-128.f));
+#endif
+            for (int iy = 0; iy < nrc_y; ++iy) {
+                auto d4y = _mm256_mul_ps(d4, _mm256_set1_ps(q8.scale(iy, ibl)));
+                acc[iy] = _mm256_fmadd_ps(d4y, _mm256_cvtepi32_ps(isum[iy]), acc[iy]);
+#ifdef HAVE_FANCY_SIMD
+                auto bsums = (const float *)q8.y[iy][ibl].bsums;
+                acc[iy] = _mm256_fmadd_ps(m4, _mm256_set1_ps(bsums[0]), acc[iy]);
+#endif
+                isum[iy] = _mm256_setzero_si256();
+            }
+        }
+        for (int iy = 0; iy < nrc_y; ++iy) {
+            info.store(ix, iy, acc[iy]);
+            acc[iy] = _mm256_setzero_ps();
+        }
+    }
+}
+
 template <int nrc_y>
 static void mul_mat_iq4_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
     GGML_ASSERT(nrc_x%4 == 0);
@@ -5976,6 +6050,18 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& mm, int Ny) {
             mm.funcs[7] = mul_mat_q6_k_r4_q8_k<8>;
             expected_typeB = GGML_TYPE_Q8_K;
             break;
+        case GGML_TYPE_Q8_K_R8:
+            assert (ne00 % QK_K == 0);
+            mm.funcs[0] = mul_mat_q8_k_r8_q8_k<1>;
+            mm.funcs[1] = mul_mat_q8_k_r8_q8_k<2>;
+            mm.funcs[2] = mul_mat_q8_k_r8_q8_k<3>;
+            mm.funcs[3] = mul_mat_q8_k_r8_q8_k<4>;
+            mm.funcs[4] = mul_mat_q8_k_r8_q8_k<5>;
+            mm.funcs[5] = mul_mat_q8_k_r8_q8_k<6>;
+            mm.funcs[6] = mul_mat_q8_k_r8_q8_k<7>;
+            mm.funcs[7] = mul_mat_q8_k_r8_q8_k<8>;
+            expected_typeB = GGML_TYPE_Q8_KR8;
+            break;
         case GGML_TYPE_IQ4_K_R4:
             assert (ne00 % QK_K == 0);
             mm.funcs[0] = mul_mat_iq4_k_r4_q8_k<1>;
@@ -9158,6 +9244,55 @@ void mul_mat_q6_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& inf
     }
 }
 
+template <int nrc_y>
+void mul_mat_q8_k_r8_q8_k(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+    GGML_ASSERT(nrc_x%8 == 0);
+    Q8<nrc_y, block_q8_K> q8(info);
+    int nbl = n / QK_K;
+    float32x4_t acc[2*nrc_y] = {};
+    for (int ix = 0; ix < nrc_x; ix += 8) {
+        const block_q8_k_r8 * iq8 = (const block_q8_k_r8 *)((const char *)vx + ix*bx);
+        for (int ibl = 0; ibl < nbl; ++ibl) {
+            auto d4l = vcvt_f32_f16(vld1_f16((const float16_t *)iq8[ibl].d+0));
+            auto d4h = vcvt_f32_f16(vld1_f16((const float16_t *)iq8[ibl].d+4));
+            int32x4_t isum[2*nrc_y] = {};
+            for (int ib = 0; ib < QK_K/16; ++ib) {
+                auto q1 = vld1q_u8_x4(iq8[ibl].qs + 128*ib +  0);
+                auto q2 = vld1q_u8_x4(iq8[ibl].qs + 128*ib + 64);
+                for (int k = 0; k < 4; ++k) {
+                    q1.val[k] = veorq_u8(q1.val[k], vdupq_n_u8(0x80));
+                    q2.val[k] = veorq_u8(q2.val[k], vdupq_n_u8(0x80));
+                }
+                for (int iy = 0; iy < nrc_y; ++iy) {
+                    auto y = vld1q_s8(q8.y[iy][ibl].qs+16*ib);
+                    isum[2*iy+0] = vdotq_laneq_s32(isum[2*iy+0], q1.val[0], y, 0);
+                    isum[2*iy+1] = vdotq_laneq_s32(isum[2*iy+1], q1.val[1], y, 0);
+                    isum[2*iy+0] = vdotq_laneq_s32(isum[2*iy+0], q1.val[2], y, 1);
+                    isum[2*iy+1] = vdotq_laneq_s32(isum[2*iy+1], q1.val[3], y, 1);
+                    isum[2*iy+0] = vdotq_laneq_s32(isum[2*iy+0], q2.val[0], y, 2);
+                    isum[2*iy+1] = vdotq_laneq_s32(isum[2*iy+1], q2.val[1], y, 2);
+                    isum[2*iy+0] = vdotq_laneq_s32(isum[2*iy+0], q2.val[2], y, 3);
+                    isum[2*iy+1] = vdotq_laneq_s32(isum[2*iy+1], q2.val[3], y, 3);
+                }
+            }
+            for (int iy = 0; iy < nrc_y; ++iy) {
+                auto d8 = vdupq_n_f32(q8.scale(iy, ibl));
+                const float * bsum = (const float *)q8.y[iy][ibl].bsums;
+                auto m8 = vdupq_n_f32(-128.f*bsum[0]);
+                acc[2*iy+0] = vfmaq_f32(acc[2*iy+0], vmulq_f32(d4l, d8), vcvtq_f32_s32(isum[2*iy+0]));
+                acc[2*iy+1] = vfmaq_f32(acc[2*iy+1], vmulq_f32(d4h, d8), vcvtq_f32_s32(isum[2*iy+1]));
+                acc[2*iy+0] = vfmaq_f32(acc[2*iy+0], d4l, m8);
+                acc[2*iy+1] = vfmaq_f32(acc[2*iy+1], d4l, m8);
+            }
+        }
+        for (int iy = 0; iy < nrc_y; ++iy) {
+            info.store(ix+0, iy, acc[2*iy+0]);
+            info.store(ix+4, iy, acc[2*iy+1]);
+            acc[2*iy+0] = acc[2*iy+1] = vdupq_n_f32(0.f);
+        }
+    }
+}
+
 void mul_mat_iq4_nl_r4_q8_0_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
     GGML_ASSERT(nrc_x%4 == 0);
     Q8<1, block_q8_0_x4> q8(info);
@@ -9575,6 +9710,10 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& m, int /*Ny*/) {
             SET_MUL_MAT_FUNCTIONS(m, mul_mat_q6_k_r4_q8_k);
             expected_Btype = GGML_TYPE_Q8_K;
             break;
+        case GGML_TYPE_Q8_K_R8:
+            SET_MUL_MAT_FUNCTIONS(m, mul_mat_q8_k_r8_q8_k);
+            expected_Btype = GGML_TYPE_Q8_KR8;
+            break;
         case GGML_TYPE_IQ4_K_R4:
             SET_MUL_MAT_FUNCTIONS(m, mul_mat_iq4_k_r4_q8_k);
             expected_Btype = GGML_TYPE_Q8_K;
diff --git a/ggml/src/iqk/iqk_quantize.cpp b/ggml/src/iqk/iqk_quantize.cpp
index 438a277e..de8c0d99 100644
--- a/ggml/src/iqk/iqk_quantize.cpp
+++ b/ggml/src/iqk/iqk_quantize.cpp
@@ -2469,7 +2469,7 @@ size_t quantize_iq6_k(const float * src, void * dst, int64_t nrows, int64_t n_pe
     return nrows * nblock * sizeof(block_iq6_k);
 }
 
-template <bool is_K32>
+template <int q8_type>
 void iqk_quantize_row_q8_K_T(const float * x, void * vy, int64_t k) {
     assert(k % QK_K == 0);
     const int nb = k / QK_K;
@@ -2505,7 +2505,7 @@ void iqk_quantize_row_q8_K_T(const float * x, void * vy, int64_t k) {
             __m256i i1 = _mm256_cvtps_epi32(v1);
             __m256i i2 = _mm256_cvtps_epi32(v2);
             __m256i i3 = _mm256_cvtps_epi32(v3);
-            if constexpr (is_K32) {
+            if constexpr (q8_type > 0) {
                 int bsum = hsum_i32_8(_mm256_add_epi32(_mm256_add_epi32(i0, i1), _mm256_add_epi32(i2, i3)));
                 auto bs = (float *)y[i].bsums;
                 bs[ib] = d*bsum;
@@ -2520,6 +2520,12 @@ void iqk_quantize_row_q8_K_T(const float * x, void * vy, int64_t k) {
             _mm256_storeu_si256((__m256i *)q8, i0);
             q8 += 32;
         }
+        if constexpr (q8_type == 2) {
+            auto bs = (float *)y[i].bsums;
+            float sum = 0;
+            for (int ib = 0; ib < QK_K/32; ++ib) sum += bs[ib];
+            bs[0] = sum;
+        }
     }
 #else
     for (int i = 0; i < nb; i++) {
@@ -2545,15 +2551,20 @@ void iqk_quantize_row_q8_K_T(const float * x, void * vy, int64_t k) {
             int v = nearest_int(iscale*x[j]);
             y[i].qs[j] = MIN(127, v);
         }
-        if constexpr (is_K32) {
+        if constexpr (q8_type > 0) {
             auto bs = (float *)y[i].bsums;
             float d = 1/iscale;
+            float sum = 0;
             for (int j = 0; j < QK_K/32; ++j) {
                 int sum = 0;
                 for (int ii = 0; ii < 32; ++ii) {
                     sum += y[i].qs[j*32 + ii];
                 }
                 bs[j] = d*sum;
+                sum += bs[j];
+            }
+            if constexpr (q8_type == 2) {
+                bs[0] = sum;
             }
         } else {
             for (int j = 0; j < QK_K/16; ++j) {
@@ -2572,11 +2583,15 @@ void iqk_quantize_row_q8_K_T(const float * x, void * vy, int64_t k) {
 }
 
 void iqk_quantize_row_q8_K(const float * x, void * vy, int64_t k) {
-    iqk_quantize_row_q8_K_T<false>(x, vy, k);
+    iqk_quantize_row_q8_K_T<0>(x, vy, k);
 }
 
 void quantize_row_q8_K32(const float * x, void * vy, int64_t k) {
-    iqk_quantize_row_q8_K_T<true>(x, vy, k);
+    iqk_quantize_row_q8_K_T<1>(x, vy, k);
+}
+
+void quantize_row_q8_KR8(const float * x, void * vy, int64_t k) {
+    iqk_quantize_row_q8_K_T<2>(x, vy, k);
 }
 
 namespace {
@@ -4666,3 +4681,81 @@ void vec_dot_iq4_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t
     GGML_UNUSED(by);
 }
 
+//
+// ========================================= q8_k_r8
+//
+
+void quantize_row_q8_k_r8_ref(const float * x, block_q8_k_r8 * y, int64_t k) {
+    quantize_q8_k_r8(x, (void *)y, 8, k/8, nullptr);
+}
+
+void quantize_row_q8_k_r8(const float * x, void * y, int64_t k) {
+    quantize_q8_k_r8(x, y, 8, k/8, nullptr);
+}
+
+static void repack_q8_k(int nrows, int n_per_row, const block_q8_K * x, block_q8_k_r8 * y) {
+    GGML_ASSERT(nrows%8 == 0);
+    GGML_ASSERT(n_per_row%QK_K == 0);
+    int nblock = n_per_row/QK_K;
+    const block_q8_K * x8[8];
+    for (int row = 0; row < nrows; row += 8) {
+        for (int k = 0; k < 8; ++k) x8[k] = x + nblock*k;
+        for (int ibl = 0; ibl < nblock; ++ibl) {
+            for (int k = 0; k < 8; ++k) {
+                y[ibl].d[k] = GGML_FP32_TO_FP16(x8[k][ibl].d);
+                for (int ib = 0; ib < QK_K/4; ++ib) {
+                    for (int i = 0; i < 4; ++i) y[ibl].qs[32*ib + 4*k + i] = x8[k][ibl].qs[4*ib+i];
+                }
+            }
+        }
+        x += 4*nblock;
+        y += nblock;
+    }
+}
+
+size_t quantize_q8_k_r8(const float * src, void * dst, int64_t nrows, int64_t n_per_row, [[maybe_unused]] const float * imatrix) {
+    GGML_ASSERT(nrows%8 == 0);
+    GGML_ASSERT(n_per_row%QK_K == 0);
+    char * qcur = (char *)dst;
+    auto row_size_0 = ggml_row_size(GGML_TYPE_Q8_K, n_per_row);
+    auto row_size_1 = ggml_row_size(GGML_TYPE_Q8_K_R8, n_per_row);
+    std::vector<char> qtmp(8*row_size_0);
+    for (int row = 0; row < nrows; row += 8) {
+        quantize_row_q8_K32(src, (void *)qtmp.data(), 8*n_per_row);
+        repack_q8_k(8, n_per_row, (const block_q8_K *)qtmp.data(), (block_q8_k_r8 *)qcur);
+        qcur += 8*row_size_1;
+        src += 8*n_per_row;
+    }
+    return nrows*row_size_1;
+}
+
+void dequantize_row_q8_k_r8(const block_q8_k_r8 * x, float * y, int64_t k) {
+    auto n_per_row = k/8;
+    float * y8[8];
+    for (int k = 0; k < 8; ++k) y8[k] = y + n_per_row*k;
+    int nblock = n_per_row/QK_K;
+    for (int ibl = 0; ibl < nblock; ++ibl) {
+        for (int k = 0; k < 8; ++k) {
+            const float d = GGML_FP16_TO_FP32(x[ibl].d[k]);
+            for (int ib = 0; ib < QK_K/4; ++ib) {
+                for (int i = 0; i < 4; ++i) {
+                    y8[k][QK_K*ibl+4*ib+i] = d * x[ibl].qs[32*ib+4*k+i];
+                }
+            }
+        }
+    }
+}
+
+void vec_dot_q8_k_r8_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
+#if GGML_USE_IQK_MULMAT
+    if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q8_K_R8, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
+        return;
+    }
+#endif
+    GGML_ASSERT(n%QK4_NL == 0);
+    GGML_ASSERT(nrc == 1);
+    GGML_UNUSED(bs);
+    GGML_UNUSED(bx);
+    GGML_UNUSED(by);
+}
+
diff --git a/ggml/src/iqk/iqk_quantize.h b/ggml/src/iqk/iqk_quantize.h
index c5702d73..753bbdb5 100644
--- a/ggml/src/iqk/iqk_quantize.h
+++ b/ggml/src/iqk/iqk_quantize.h
@@ -145,11 +145,18 @@ size_t quantize_iq4_k_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT d
 void   dequantize_row_iq4_k_r4(const block_iq4_k_r4  * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
 void   vec_dot_iq4_k_r4_q8_k(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
 
+void   quantize_row_q8_k_r8_ref(const float * GGML_RESTRICT x, block_q8_k_r8  * GGML_RESTRICT y, int64_t k);
+void   quantize_row_q8_k_r8(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+size_t quantize_q8_k_r8(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+void   dequantize_row_q8_k_r8(const block_q8_k_r8  * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void   vec_dot_q8_k_r8_q8_k(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
+
 void iqk_quantize_row_q8_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, int64_t k);
 void quantize_row_q8_K64_ref(const float * GGML_RESTRICT x, block_q8_K64 * GGML_RESTRICT y, int64_t k);
 void quantize_row_q8_K64(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
 void quantize_row_q8_K16(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
 void quantize_row_q8_K32(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_q8_KR8(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
 
 #ifdef __cplusplus
 }