TdAI / llama.cpp /ggml /src /ggml-cpu /spacemit /repack.cpp
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#define GGML_COMMON_IMPL_CPP
#define GGML_COMMON_DECL_CPP
#include "repack.h"
#include "ggml-common.h"
#include "ggml-cpu.h"
#include "ggml-impl.h"
#include "ime_kernels.h"
#include <algorithm>
#include <cassert>
#include <cmath>
#include <cstring>
// clang-format off
#if defined(__riscv)
#if !defined(__riscv_v) || !defined(__riscv_v_intrinsic)
#error "riscv v extension or v_intrinsic not enabled"
#else
#include <riscv_vector.h>
#endif
#if !defined(__riscv_zfh)
#error "riscv zfh extension not enabled"
#endif
#else
#error "riscv not enabled in this build"
#endif
#if defined(__GNUC__)
#pragma GCC diagnostic ignored "-Wcast-qual"
#pragma GCC diagnostic ignored "-Wunused-parameter"
#endif
// clang-format on
template <int K> constexpr int QK_0() {
if constexpr (K == 4) {
return QK4_0;
}
if constexpr (K == 8) {
return QK8_0;
}
return -1;
}
template <int K, int N> struct block {
ggml_half d[N]; // deltas for N qK_0 blocks
uint8_t qs[(QK_0<K>() * N * K) / 8]; // quants for N qK_0 blocks
};
template <int K, int N> struct block_with_zp {
ggml_half d[N]; // deltas for N qK_1 blocks
uint8_t zp[N]; // zero points for N qK_1 blocks
uint8_t qs[(QK_0<K>() * N * K) / 8]; // quants for N qK_1 blocks
};
// control size
static_assert(sizeof(block<4, 16>) == 16 * sizeof(ggml_half) + QK4_0 * 8, "wrong block<4,16> size/padding");
static_assert(sizeof(block_with_zp<4, 16>) == 16 * sizeof(ggml_half) + QK4_0 * 8 + 16 * sizeof(uint8_t),
"wrong block_with_zp<4,16> size/padding");
static_assert(sizeof(block<8, 16>) == 16 * sizeof(ggml_half) + QK4_0 * 16, "wrong block<8,16> size/padding");
static_assert(sizeof(block<4, 32>) == 32 * sizeof(ggml_half) + QK4_0 * 16, "wrong block<4,32> size/padding");
static_assert(sizeof(block_with_zp<4, 32>) == 32 * sizeof(ggml_half) + QK4_0 * 16 + 32 * sizeof(uint8_t),
"wrong block_with_zp<4,32> size/padding");
using block_q4_0x16 = block<4, 16>;
using block_q4_1x16 = block_with_zp<4, 16>;
using block_q8_0x16 = block<8, 16>;
using block_q4_0x32 = block<4, 32>;
using block_q4_1x32 = block_with_zp<4, 32>;
using block_q8_0x32 = block<8, 32>;
struct block_q4_0x32x256 {
block_q4_0x32 blocks[8]; // [f16 * 32 | i4 * 32 * 32] * 8
};
struct block_q4_1x32x256 {
block_q4_0x32 blocks[8];
uint8_t zps[32 * 8];
};
static block_q4_0x16 make_block_q4_0x16(block_q4_0 * in, unsigned int blck_size_interleave) {
block_q4_0x16 out;
GGML_ASSERT(QK4_0 / blck_size_interleave == 2);
for (int i = 0; i < 16; i++) {
out.d[i] = in[i].d;
}
for (int i = 0; i < 16; i++) {
// [0, 15], in.d & 0x0F
for (int j = 0; j < QK4_0 / 4; j++) {
//src [b0 b16] ......... [b8 b24] ......... [b15 b31]
//dst [b0 b8] ......... [b7 b15]
out.qs[i * QK4_0 / 4 + j] = (in[i].qs[j] & 0x0F) | ((in[i].qs[j + QK4_0 / 4] & 0x0F) << 4);
}
}
for (int i = 0; i < 16; i++) {
// [16, 31], in.d & 0xF0
for (int j = 0; j < QK4_0 / 4; j++) {
//src [b0 b16] ......... [b8 b24] ......... [b15 b31]
//dst [b16 b24] ......... [b23 b31]
out.qs[4 * QK4_0 + i * QK4_0 / 4 + j] = ((in[i].qs[j] & 0xF0) >> 4) | (in[i].qs[j + QK4_0 / 4] & 0xF0);
}
}
return out;
}
static block_q4_1x16 make_block_q4_1x16(block_q4_1 * in, unsigned int blck_size_interleave) {
block_q4_1x16 out;
GGML_ASSERT(QK4_1 / blck_size_interleave == 2);
for (int i = 0; i < 16; i++) {
float d = GGML_FP16_TO_FP32(in[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d);
float m = GGML_FP16_TO_FP32(in[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.m);
float mid = -std::nearbyintf(m / d);
mid = std::min(15.0f, std::max(0.0f, mid));
out.d[i] = GGML_FP32_TO_FP16(d);
out.zp[i] = static_cast<uint8_t>(mid);
}
for (int i = 0; i < 16; i++) {
// [0, 15], in.d & 0x0F
for (int j = 0; j < QK4_1 / 4; j++) {
//src [b0 b16] ......... [b8 b24] ......... [b15 b31]
//dst [b0 b8] ......... [b7 b15]
out.qs[i * QK4_1 / 4 + j] = (in[i].qs[j] & 0x0F) | ((in[i].qs[j + QK4_1 / 4] & 0x0F) << 4);
}
}
for (int i = 0; i < 16; i++) {
// [16, 31], in.d & 0xF0
for (int j = 0; j < QK4_1 / 4; j++) {
//src [b0 b16] ......... [b8 b24] ......... [b15 b31]
//dst [b16 b24] ......... [b23 b31]
out.qs[4 * QK4_1 + i * QK4_1 / 4 + j] = ((in[i].qs[j] & 0xF0) >> 4) | (in[i].qs[j + QK4_1 / 4] & 0xF0);
}
}
return out;
}
static int repack_q4_0_to_q4_0_16_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q4_0);
GGML_ASSERT(interleave_block == 16);
constexpr int nrows_interleaved = 16;
block_q4_0x16 * dst = (block_q4_0x16 *) t->data;
const block_q4_0 * src = (const block_q4_0 *) data;
block_q4_0 dst_tmp[16];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK4_0;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_0));
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_0 != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int i = 0; i < nrows_interleaved; i++) {
dst_tmp[i] = src[x + i * nblocks];
}
*dst++ = make_block_q4_0x16(dst_tmp, interleave_block);
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
static int repack_q4_1_to_q4_1_16_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q4_1);
GGML_ASSERT(interleave_block == 16);
constexpr int nrows_interleaved = 16;
block_q4_1x16 * dst = (block_q4_1x16 *) t->data;
const block_q4_1 * src = (const block_q4_1 *) data;
block_q4_1 dst_tmp[16];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK4_1;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_1));
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_1 != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int i = 0; i < nrows_interleaved; i++) {
dst_tmp[i] = src[x + i * nblocks];
}
*dst++ = make_block_q4_1x16(dst_tmp, interleave_block);
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
static inline void get_scale_min_k4(int j,
const uint8_t * GGML_RESTRICT q,
uint8_t * GGML_RESTRICT d,
uint8_t * GGML_RESTRICT m) {
if (j < 4) {
*d = q[j] & 63;
*m = q[j + 4] & 63;
} else {
*d = (q[j + 4] & 0xF) | ((q[j - 4] >> 6) << 4);
*m = (q[j + 4] >> 4) | ((q[j - 0] >> 6) << 4);
}
}
static int repack_q4_k_to_q4_1_16_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q4_K);
GGML_ASSERT(interleave_block == 16);
GGML_ASSERT(QK_K / QK4_1 == 8);
constexpr int nrows_interleaved = 16;
block_q4_1x16 * dst = (block_q4_1x16 *) t->data;
const block_q4_K * src = (const block_q4_K *) data;
block_q4_1 dst_tmp[16];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK_K;
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_K != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int j = 0; j < 8; j++) {
for (int i = 0; i < nrows_interleaved; i++) {
uint8_t sc, m;
const float d = GGML_FP16_TO_FP32(src[x + i * nblocks].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d);
const float min =
GGML_FP16_TO_FP32(src[x + i * nblocks].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.dmin);
get_scale_min_k4(j, src[x + i * nblocks].scales, &sc, &m);
const float d1 = d * sc;
const float m1 = min * m;
dst_tmp[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d = GGML_FP32_TO_FP16(d1);
dst_tmp[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.m = GGML_FP32_TO_FP16(-m1);
// src -> [b0, b32] [b1, b33] ... [b31, b63]
// dst -> [b0, b16] [b1, b17] ... [b15, b31] [b32, b48] [b33, b49] ... [b47, b63]
const uint8_t * q = src[x + i * nblocks].qs + (j / 2) * QK4_1;
if (j % 2 == 0) {
for (int ii = 0; ii < 16; ii++) {
dst_tmp[i].qs[ii] = (q[ii] & 0x0F) | ((q[ii + 16] & 0x0F) << 4);
}
} else {
for (int ii = 0; ii < 16; ii++) {
dst_tmp[i].qs[ii] = ((q[ii] & 0xF0) >> 4) | (q[ii + 16] & 0xF0);
}
}
}
*dst++ = make_block_q4_1x16(dst_tmp, interleave_block);
}
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
static block_q4_0x32 make_block_q4_0x32(block_q4_0 * in, unsigned int blck_size_interleave) {
block_q4_0x32 out;
assert(QK4_0 / blck_size_interleave == 1);
GGML_UNUSED(blck_size_interleave);
for (int i = 0; i < 32; i++) {
out.d[i] = in[i].d;
}
for (int i = 0; i < 32; i++) {
// [0, 15], in.d & 0x0F
for (int j = 0; j < QK4_0 / 4; j++) {
//src [b0 b16] ......... [b8 b24] ......... [b15 b31]
//dst [b0 b1] ......... [b14 b15]
out.qs[i * QK4_0 / 2 + j] = (in[i].qs[j * 2] & 0x0F) | ((in[i].qs[j * 2 + 1] & 0x0F) << 4);
}
}
for (int i = 0; i < 32; i++) {
// [16, 31], in.d & 0xF0
for (int j = 0; j < QK4_0 / 4; j++) {
//src [b0 b16] ......... [b8 b24] ......... [b15 b31]
//dst [b16 b17] ......... [b30 b31]
out.qs[i * QK4_0 / 2 + QK4_0 / 4 + j] = ((in[i].qs[j * 2] & 0xF0) >> 4) | (in[i].qs[j * 2 + 1] & 0xF0);
}
}
return out;
}
static block_q4_1x32 make_block_q4_1x32(block_q4_1 * in, unsigned int blck_size_interleave) {
block_q4_1x32 out;
GGML_ASSERT(QK4_1 / blck_size_interleave == 1);
GGML_UNUSED(blck_size_interleave);
for (int i = 0; i < 32; i++) {
float d = GGML_FP16_TO_FP32(in[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d);
float m = GGML_FP16_TO_FP32(in[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.m);
float mid = -std::nearbyintf(m / d);
mid = std::min(15.0f, std::max(0.0f, mid));
out.d[i] = GGML_FP32_TO_FP16(d);
out.zp[i] = static_cast<uint8_t>(mid);
}
for (int i = 0; i < 32; i++) {
// [0, 15], in.d & 0x0F
for (int j = 0; j < QK4_1 / 4; j++) {
//src [b0 b16] ......... [b8 b24] ......... [b15 b31]
//dst [b0 b1] ......... [b14 b15]
out.qs[i * QK4_1 / 2 + j] = (in[i].qs[j * 2] & 0x0F) | ((in[i].qs[j * 2 + 1] & 0x0F) << 4);
}
}
for (int i = 0; i < 32; i++) {
// [16, 31], in.d & 0xF0
for (int j = 0; j < QK4_1 / 4; j++) {
//src [b0 b16] ......... [b8 b24] ......... [b15 b31]
//dst [b16 b24] ......... [b23 b31]
out.qs[i * QK4_1 / 2 + QK4_1 / 4 + j] = ((in[i].qs[j * 2] & 0xF0) >> 4) | (in[i].qs[j * 2 + 1] & 0xF0);
}
}
return out;
}
static block_q8_0x32 make_block_q8_0x32(block_q8_0 * in, unsigned int blck_size_interleave) {
block_q8_0x32 out;
GGML_ASSERT(QK8_0 / blck_size_interleave == 1);
GGML_UNUSED(blck_size_interleave);
for (int i = 0; i < 32; i++) {
out.d[i] = in[i].d;
}
for (int i = 0; i < 32; i++) {
memcpy(out.qs + i * QK8_0, in[i].qs, QK8_0);
}
return out;
}
static int repack_q2_k_to_q2_k_32_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q2_K);
GGML_ASSERT(interleave_block == 32);
GGML_ASSERT(QK_K == 256);
constexpr int nrows_interleaved = 32;
const block_q2_K * src = (const block_q2_K *) data;
auto * dst = (spacemit_kernels::nrow_block_q2_k<32> *) t->data;
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK_K;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q2_K));
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_K != 0) {
return -1;
}
uint8_t qs_aux[256] = { 0 };
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int i = 0; i < nrows_interleaved; i++) {
const block_q2_K * src_block = &src[(b + i) * nblocks + x];
// scale for [16, N]
for (int j = 0; j < 16; j++) {
auto zp_aux = (dst->scales[j * nrows_interleaved + i]) & 0xF0;
dst->scales[j * nrows_interleaved + i] = (src_block->scales[j] & 0x0F) | zp_aux;
}
// zp for [N, 16]
for (int j = 0; j < 16; j++) {
auto scale_aux = (dst->scales[16 * i + j]) & 0x0F;
dst->scales[16 * i + j] = (src_block->scales[j] & 0xF0) | scale_aux;
}
for (int k = 0; k < 4; k++) {
for (int j = 0; j < 32; j++) {
qs_aux[k * 32 + j] = (src_block->qs[j] >> (2 * k)) & 0x03;
}
}
for (int k = 0; k < 4; k++) {
for (int j = 0; j < 32; j++) {
qs_aux[k * 32 + j + 128] = (src_block->qs[j + 32] >> (2 * k)) & 0x03;
}
}
// from nrows_interleaved * [2 * 32byte]
// to 4 * [nrows_interleaved * 16byte]
for (int k = 0; k < 4; k++) {
for (int j = 0; j < 16; j++) {
uint8_t qs0 = qs_aux[j + k * 64];
uint8_t qs16 = qs_aux[j + 16 + k * 64];
uint8_t qs32 = qs_aux[j + 32 + k * 64];
uint8_t qs48 = qs_aux[j + 48 + k * 64];
dst->qs[(k * nrows_interleaved + i) * 16 + j] =
(qs0 & 0x03) | ((qs16 & 0x03) << 2) | ((qs32 & 0x03) << 4) | ((qs48 & 0x03) << 6);
}
}
dst->scales16[i] = src_block->GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d;
dst->zeros16[i] = src_block->GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.dmin;
}
dst++;
}
}
return 0;
}
static int repack_q3_k_to_q3_k_32_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q3_K);
GGML_ASSERT(interleave_block == 32);
GGML_ASSERT(QK_K == 256);
constexpr int nrows_interleaved = 32;
const uint32_t kmask1 = 0x03030303;
const uint32_t kmask2 = 0x0f0f0f0f;
const block_q3_K * src = (const block_q3_K *) data;
auto * dst = (spacemit_kernels::nrow_block_q3_k<32> *) t->data;
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK_K;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q3_K));
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_K != 0) {
return -1;
}
uint32_t b_scale_aux[4] = { 0 };
uint8_t qs_aux[256] = { 0 };
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int i = 0; i < nrows_interleaved; i++) {
const block_q3_K * src_block = &src[(b + i) * nblocks + x];
uint32_t * auxs = b_scale_aux;
int8_t * scale = (int8_t *) auxs;
memcpy(auxs, src_block->scales, 12);
uint32_t tmp = auxs[2];
auxs[2] = ((auxs[0] >> 4) & kmask2) | (((tmp >> 4) & kmask1) << 4);
auxs[3] = ((auxs[1] >> 4) & kmask2) | (((tmp >> 6) & kmask1) << 4);
auxs[0] = (auxs[0] & kmask2) | (((tmp >> 0) & kmask1) << 4);
auxs[1] = (auxs[1] & kmask2) | (((tmp >> 2) & kmask1) << 4);
for (int j = 0; j < 16; j++) {
dst->scales[j * nrows_interleaved + i] = scale[j] - 32;
}
for (int k = 0; k < 4; k++) {
for (int j = 0; j < 32; j++) {
qs_aux[k * 32 + j] = (src_block->qs[j] >> (2 * k)) & 0x03;
}
}
for (int k = 0; k < 4; k++) {
for (int j = 0; j < 32; j++) {
qs_aux[k * 32 + j + 128] = (src_block->qs[j + 32] >> (2 * k)) & 0x03;
}
}
// from nrows_interleaved * [2 * 32byte]
// to 4 * [nrows_interleaved * 16byte]
for (int k = 0; k < 4; k++) {
for (int j = 0; j < 16; j++) {
uint8_t qs0 = qs_aux[j + k * 64];
uint8_t qs16 = qs_aux[j + 16 + k * 64];
uint8_t qs32 = qs_aux[j + 32 + k * 64];
uint8_t qs48 = qs_aux[j + 48 + k * 64];
dst->qs[(k * nrows_interleaved + i) * 16 + j] =
(qs0 & 0x03) | ((qs16 & 0x03) << 2) | ((qs32 & 0x03) << 4) | ((qs48 & 0x03) << 6);
}
}
//memcpy(dst->hmask + i * 32, src_block->hmask, 32);
// from nrows_interleaved * [32byte]
// to 16 * [nrows_interleaved * uint16_t]
uint16_t * dst_mask = ((uint16_t *) dst->hmask) + i;
for (int j = 0; j < 16; j++, dst_mask += nrows_interleaved) {
uint8_t b_shift = j / 2;
uint8_t * b_mask_col = (uint8_t *) (src_block->hmask + (j % 2) * 16);
// b0 - b15
uint16_t msk_out_0 = 0;
for (int k = 0; k < 8; k++) {
msk_out_0 |= (uint16_t) ((b_mask_col[k] >> b_shift) & 0x01) << k;
}
for (int k = 8; k < 16; k++) {
msk_out_0 |= (uint16_t) ((b_mask_col[k] >> b_shift) & 0x01) << k;
}
dst_mask[0] = msk_out_0;
}
dst->scales16[i] = src_block->d;
}
dst++;
}
}
return 0;
}
static int repack_q4_0_to_q4_0_32_bl_ref(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q4_0);
GGML_ASSERT(interleave_block == 32); // unused
constexpr int nrows_interleaved = 32;
block_q4_0x32 * dst = (block_q4_0x32 *) t->data;
const block_q4_0 * src = (const block_q4_0 *) data;
block_q4_0 dst_tmp[32];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK4_0;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_0));
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_0 != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int i = 0; i < nrows_interleaved; i++) {
dst_tmp[i] = src[x + i * nblocks];
}
*dst++ = make_block_q4_0x32(dst_tmp, interleave_block);
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
static int repack_q4_0_to_q4_0_256_32_bl_ref(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q4_0);
GGML_ASSERT(interleave_block == 32); // unused
constexpr int nrows_interleaved = 32;
block_q4_0x32x256 * dst = (block_q4_0x32x256 *) t->data;
const block_q4_0 * src = (const block_q4_0 *) data;
block_q4_0 dst_tmp[32];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK4_0;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_0));
GGML_ASSERT(nblocks % 8 == 0); // for 256-block interleaving
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_0 != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x += 8) {
for (int j = 0; j < 8; j++) {
for (int i = 0; i < nrows_interleaved; i++) {
dst_tmp[i] = src[x + j + i * nblocks];
}
dst->blocks[j] = make_block_q4_0x32(dst_tmp, interleave_block);
}
dst++;
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
static int repack_q4_0_to_q4_1_256_32_bl_ref(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q4_1);
GGML_ASSERT(interleave_block == 32); // unused
constexpr int nrows_interleaved = 32;
block_q4_1x32x256 * dst = (block_q4_1x32x256 *) t->data;
const block_q4_1 * src = (const block_q4_1 *) data;
block_q4_1 dst_tmp[32];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK4_0;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_1));
GGML_ASSERT(nblocks % 8 == 0); // for 256-block interleaving
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_0 != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x += 8) {
for (int j = 0; j < 8; j++) {
for (int i = 0; i < nrows_interleaved; i++) {
dst_tmp[i] = src[x + j + i * nblocks];
}
block_q4_0x32 * dst_block = &dst->blocks[j];
uint8_t * dst_zp = dst->zps + j * nrows_interleaved;
for (int i = 0; i < nrows_interleaved; i++) {
float d = GGML_FP16_TO_FP32(dst_tmp[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d);
float m = GGML_FP16_TO_FP32(dst_tmp[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.m);
float mid = -std::nearbyintf(m / d);
mid = std::min(15.0f, std::max(0.0f, mid));
dst_block->d[i] = GGML_FP32_TO_FP16(d);
dst_zp[i] = static_cast<uint8_t>(mid);
}
for (int i = 0; i < nrows_interleaved; i++) {
for (int k = 0; k < QK4_1 / 4; k++) {
dst_block->qs[i * QK4_1 / 2 + k] =
(dst_tmp[i].qs[k * 2] & 0x0F) | ((dst_tmp[i].qs[k * 2 + 1] & 0x0F) << 4);
}
}
for (int i = 0; i < nrows_interleaved; i++) {
for (int k = 0; k < QK4_1 / 4; k++) {
dst_block->qs[i * QK4_1 / 2 + QK4_1 / 4 + k] =
((dst_tmp[i].qs[k * 2] & 0xF0) >> 4) | (dst_tmp[i].qs[k * 2 + 1] & 0xF0);
}
}
}
dst++;
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
// RVV optimized version of repack_q4_0_to_q4_0_32_bl
// Eliminates the intermediate dst_tmp buffer and vectorizes nibble repack.
static int repack_q4_0_to_q4_0_32_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q4_0);
GGML_ASSERT(interleave_block == 32);
constexpr int nrows_interleaved = 32;
constexpr int qs_bytes = QK4_0 / 2; // 16
block_q4_0x32 * dst = (block_q4_0x32 *) t->data;
const block_q4_0 * src = (const block_q4_0 *) data;
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK4_0;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_0));
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_0 != 0) {
return -1;
}
const ptrdiff_t row_stride = (ptrdiff_t) nblocks * sizeof(block_q4_0);
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
const block_q4_0 * col_src = src + x;
// --- 1) Gather 32 scale values (ggml_half d) with stride load ---
// d is at offset 0 of each block_q4_0, stride between rows = row_stride
{
const uint8_t * d_base = (const uint8_t *) &col_src->d;
ggml_half * d_dst = dst->d;
size_t remaining = 32;
size_t offset = 0;
while (remaining > 0) {
size_t vl = __riscv_vsetvl_e16m1(remaining);
vuint16m1_t vd =
__riscv_vlse16_v_u16m1((const uint16_t *) (d_base + offset * row_stride), row_stride, vl);
__riscv_vse16_v_u16m1((uint16_t *) (d_dst + offset), vd, vl);
offset += vl;
remaining -= vl;
}
}
// --- 2) Nibble repack qs for each of the 32 rows ---
// For each row i:
// src qs[16]: [b0|b16] [b1|b17] ... [b15|b31] (lo nibble = b_j, hi nibble = b_{j+16})
// dst qs low 8B: (qs[2j] & 0x0F) | ((qs[2j+1] & 0x0F) << 4) for j=0..7
// dst qs high 8B: ((qs[2j] >> 4)) | (qs[2j+1] & 0xF0) for j=0..7
{
const size_t vl8 = __riscv_vsetvl_e8m1(8);
for (int i = 0; i < 32; i++) {
const uint8_t * sq = col_src[i * nblocks].qs;
uint8_t * dq = dst->qs + i * qs_bytes;
// stride-2 load to separate even/odd bytes
vuint8m1_t v_even = __riscv_vlse8_v_u8m1(sq, 2, vl8); // qs[0], qs[2], ..., qs[14]
vuint8m1_t v_odd = __riscv_vlse8_v_u8m1(sq + 1, 2, vl8); // qs[1], qs[3], ..., qs[15]
// low nibble part: (even & 0x0F) | ((odd & 0x0F) << 4)
vuint8m1_t v_even_lo = __riscv_vand_vx_u8m1(v_even, 0x0F, vl8);
vuint8m1_t v_odd_lo = __riscv_vand_vx_u8m1(v_odd, 0x0F, vl8);
vuint8m1_t v_lo = __riscv_vor_vv_u8m1(v_even_lo, __riscv_vsll_vx_u8m1(v_odd_lo, 4, vl8), vl8);
// high nibble part: (even >> 4) | (odd & 0xF0)
vuint8m1_t v_even_hi = __riscv_vsrl_vx_u8m1(v_even, 4, vl8);
vuint8m1_t v_odd_hi = __riscv_vand_vx_u8m1(v_odd, 0xF0, vl8);
vuint8m1_t v_hi = __riscv_vor_vv_u8m1(v_even_hi, v_odd_hi, vl8);
__riscv_vse8_v_u8m1(dq, v_lo, vl8);
__riscv_vse8_v_u8m1(dq + 8, v_hi, vl8);
}
}
dst++;
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
static int repack_q4_1_to_q4_1_32_bl_ref(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q4_1);
GGML_ASSERT(interleave_block == 32); // unused
constexpr int nrows_interleaved = 32;
block_q4_1x32 * dst = (block_q4_1x32 *) t->data;
const block_q4_1 * src = (const block_q4_1 *) data;
block_q4_1 dst_tmp[32];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK4_1;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_1));
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_1 != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int i = 0; i < nrows_interleaved; i++) {
dst_tmp[i] = src[x + i * nblocks];
}
*dst++ = make_block_q4_1x32(dst_tmp, interleave_block);
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
// RVV optimized version of repack_q4_1_to_q4_1_32_bl
// Eliminates the intermediate dst_tmp buffer and vectorizes nibble repack + zp computation.
static int repack_q4_1_to_q4_1_32_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q4_1);
GGML_ASSERT(interleave_block == 32);
constexpr int nrows_interleaved = 32;
constexpr int qs_bytes = QK4_1 / 2; // 16
block_q4_1x32 * dst = (block_q4_1x32 *) t->data;
const block_q4_1 * src = (const block_q4_1 *) data;
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK4_1;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_1));
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_1 != 0) {
return -1;
}
const ptrdiff_t row_stride = (ptrdiff_t) nblocks * sizeof(block_q4_1);
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
const block_q4_1 * col_src = src + x;
// --- 1) Gather d and m, compute zp = clamp(nearbyint(-m/d), 0, 15) ---
// block_q4_1 layout: [d(f16), m(f16), qs[16]]
// d is at byte offset 0, m is at byte offset 2 from each block start
{
const uint8_t * dm_base = (const uint8_t *) &col_src->GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d;
ggml_half * d_dst = dst->d;
uint8_t * zp_dst = dst->zp;
size_t remaining = 32;
size_t offset = 0;
while (remaining > 0) {
size_t vl = __riscv_vsetvl_e16m1(remaining);
// stride load d (f16) from each row
vuint16m1_t vd_raw =
__riscv_vlse16_v_u16m1((const uint16_t *) (dm_base + offset * row_stride), row_stride, vl);
__riscv_vse16_v_u16m1((uint16_t *) (d_dst + offset), vd_raw, vl);
// stride load m (f16) from each row (offset +2 bytes from d)
vuint16m1_t vm_raw =
__riscv_vlse16_v_u16m1((const uint16_t *) (dm_base + 2 + offset * row_stride), row_stride, vl);
// convert to f32 for zp computation: zp = nearbyint(-m / d)
vfloat16m1_t vd_f16 = __riscv_vreinterpret_v_u16m1_f16m1(vd_raw);
vfloat16m1_t vm_f16 = __riscv_vreinterpret_v_u16m1_f16m1(vm_raw);
// -m / d in f16 directly (SpaceMIT X60 supports f16 arithmetic)
vfloat16m1_t v_neg_m = __riscv_vfneg_v_f16m1(vm_f16, vl);
vfloat16m1_t v_ratio = __riscv_vfdiv_vv_f16m1(v_neg_m, vd_f16, vl);
// Convert to f32 for nearbyint, then clamp
vfloat32m2_t v_ratio_f32 = __riscv_vfwcvt_f_f_v_f32m2(v_ratio, vl);
// Use integer rounding: convert f32 -> int (rounds to nearest)
vint32m2_t v_zp_i32 = __riscv_vfcvt_x_f_v_i32m2(v_ratio_f32, vl);
// clamp to [0, 15]
v_zp_i32 = __riscv_vmax_vx_i32m2(v_zp_i32, 0, vl);
v_zp_i32 = __riscv_vmin_vx_i32m2(v_zp_i32, 15, vl);
// narrow i32 -> u8
vint16m1_t v_zp_i16 = __riscv_vncvt_x_x_w_i16m1(v_zp_i32, vl);
vint8mf2_t v_zp_i8 = __riscv_vncvt_x_x_w_i8mf2(v_zp_i16, vl);
vuint8mf2_t v_zp_u8 = __riscv_vreinterpret_v_i8mf2_u8mf2(v_zp_i8);
__riscv_vse8_v_u8mf2(zp_dst + offset, v_zp_u8, vl);
offset += vl;
remaining -= vl;
}
}
// --- 2) Nibble repack qs for each of the 32 rows ---
{
const size_t vl8 = __riscv_vsetvl_e8m1(8);
for (int i = 0; i < 32; i++) {
const uint8_t * sq = col_src[i * nblocks].qs;
uint8_t * dq = dst->qs + i * qs_bytes;
// stride-2 load to separate even/odd bytes
vuint8m1_t v_even = __riscv_vlse8_v_u8m1(sq, 2, vl8);
vuint8m1_t v_odd = __riscv_vlse8_v_u8m1(sq + 1, 2, vl8);
// low nibble part: (even & 0x0F) | ((odd & 0x0F) << 4)
vuint8m1_t v_even_lo = __riscv_vand_vx_u8m1(v_even, 0x0F, vl8);
vuint8m1_t v_odd_lo = __riscv_vand_vx_u8m1(v_odd, 0x0F, vl8);
vuint8m1_t v_lo = __riscv_vor_vv_u8m1(v_even_lo, __riscv_vsll_vx_u8m1(v_odd_lo, 4, vl8), vl8);
// high nibble part: (even >> 4) | (odd & 0xF0)
vuint8m1_t v_even_hi = __riscv_vsrl_vx_u8m1(v_even, 4, vl8);
vuint8m1_t v_odd_hi = __riscv_vand_vx_u8m1(v_odd, 0xF0, vl8);
vuint8m1_t v_hi = __riscv_vor_vv_u8m1(v_even_hi, v_odd_hi, vl8);
__riscv_vse8_v_u8m1(dq, v_lo, vl8);
__riscv_vse8_v_u8m1(dq + 8, v_hi, vl8);
}
}
dst++;
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
static int repack_q4_k_to_q4_1_32_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q4_K);
GGML_ASSERT(interleave_block == 32);
GGML_ASSERT(QK_K / QK4_1 == 8);
constexpr int nrows_interleaved = 32;
block_q4_1x32 * dst = (block_q4_1x32 *) t->data;
const block_q4_K * src = (const block_q4_K *) data;
block_q4_1 dst_tmp[32];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK_K;
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_K != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int j = 0; j < 8; j++) {
for (int i = 0; i < nrows_interleaved; i++) {
uint8_t sc, m;
const float d = GGML_FP16_TO_FP32(src[x + i * nblocks].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d);
const float min =
GGML_FP16_TO_FP32(src[x + i * nblocks].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.dmin);
get_scale_min_k4(j, src[x + i * nblocks].scales, &sc, &m);
const float d1 = d * sc;
const float m1 = min * m;
dst_tmp[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d = GGML_FP32_TO_FP16(d1);
dst_tmp[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.m = GGML_FP32_TO_FP16(-m1);
// src -> [b0, b32] [b1, b33] ... [b31, b63]
// dst -> [b0, b16] [b1, b17] ... [b15, b31] [b32, b48] [b33, b49] ... [b47, b63]
const uint8_t * q = src[x + i * nblocks].qs + (j / 2) * QK4_1;
if (j % 2 == 0) {
for (int ii = 0; ii < 16; ii++) {
dst_tmp[i].qs[ii] = (q[ii] & 0x0F) | ((q[ii + 16] & 0x0F) << 4);
}
} else {
for (int ii = 0; ii < 16; ii++) {
dst_tmp[i].qs[ii] = ((q[ii] & 0xF0) >> 4) | (q[ii + 16] & 0xF0);
}
}
}
*dst++ = make_block_q4_1x32(dst_tmp, interleave_block);
}
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
static int repack_q6_k_to_q8_0_32_bl_ref(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q6_K);
GGML_ASSERT(interleave_block == 32);
GGML_ASSERT(QK_K / QK4_1 == 8);
constexpr int nrows_interleaved = 32;
block_q8_0x32 * dst = (block_q8_0x32 *) t->data;
const block_q6_K * src = (const block_q6_K *) data;
block_q8_0 dst_tmp[32];
int8_t aux8[QK4_1];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK_K;
if (t->ne[0] % QK_K != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
int64_t nrow_real = std::min((int64_t) nrow - b, (int64_t) nrows_interleaved);
for (int64_t x = 0; x < nblocks; x++) {
for (int bi = 0; bi < 8; bi++) {
int i = 0;
for (; i < nrow_real; i++) {
const uint8_t * q4 = src[x + i * nblocks].ql;
const uint8_t * qh = src[x + i * nblocks].qh;
const int8_t * scales = src[x + i * nblocks].scales;
float d = GGML_FP16_TO_FP32(src[x + i * nblocks].d);
q4 += 64 * (bi / 4);
qh += 32 * (bi / 4);
int8_t * GGML_RESTRICT a = aux8;
int8_t bi_idx = bi % 4;
if (bi_idx == 0) {
for (int l = 0; l < 32; ++l) {
a[l] = (int8_t) ((q4[l] & 0xF) | (((qh[l] >> 0) & 3) << 4)) - 32;
}
} else if (bi_idx == 1) {
for (int l = 0; l < 32; ++l) {
a[l] = (int8_t) ((q4[l + 32] & 0xF) | (((qh[l] >> 2) & 3) << 4)) - 32;
}
} else if (bi_idx == 2) {
for (int l = 0; l < 32; ++l) {
a[l] = (int8_t) ((q4[l + 0] >> 4) | (((qh[l] >> 4) & 3) << 4)) - 32;
}
} else if (bi_idx == 3) {
for (int l = 0; l < 32; ++l) {
a[l] = (int8_t) ((q4[l + 32] >> 4) | (((qh[l] >> 6) & 3) << 4)) - 32;
}
}
a = aux8;
float a_max_abs = 0.0f;
float scale_0 = scales[bi * 2 + 0] * d;
float scale_1 = scales[bi * 2 + 1] * d;
for (int l = 0; l < 16; ++l) {
a_max_abs = std::max(a_max_abs, std::abs(a[l] * scale_0));
}
for (int l = 16; l < 32; ++l) {
a_max_abs = std::max(a_max_abs, std::abs(a[l] * scale_1));
}
float reflect_scale = a_max_abs / ((1 << 7) - 1);
float reflect_scale_0 = scale_0 / reflect_scale;
float reflect_scale_1 = scale_1 / reflect_scale;
for (int l = 0; l < 16; ++l) {
float a_temp = std::clamp(std::nearbyintf(a[l] * reflect_scale_0), -128.0f, 127.0f);
a[l] = (int8_t) (a_temp);
}
for (int l = 16; l < 32; ++l) {
float a_temp = std::clamp(std::nearbyintf(a[l] * reflect_scale_1), -128.0f, 127.0f);
a[l] = (int8_t) (a_temp);
}
dst_tmp[i].d = GGML_FP32_TO_FP16(reflect_scale);
memcpy(dst_tmp[i].qs, a, 32 * sizeof(int8_t));
}
for (; i < nrows_interleaved; i++) {
memset(&dst_tmp[i], 0, sizeof(block_q8_0));
}
*dst++ = make_block_q8_0x32(dst_tmp, interleave_block);
}
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
// RVV optimized version of repack_q6_k_to_q8_0_32_bl
// Vectorizes the Q6_K dequant -> requant pipeline using RVV intrinsics.
// For each sub-block (bi), dequant 32 Q6_K values to int6 -> apply two sub-block scales ->
// find max abs -> compute reflect_scale -> requant to int8 -> gather d with stride load.
static int repack_q6_k_to_q8_0_32_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q6_K);
GGML_ASSERT(interleave_block == 32);
GGML_ASSERT(QK_K / QK4_1 == 8);
constexpr int nrows_interleaved = 32;
block_q8_0x32 * dst = (block_q8_0x32 *) t->data;
const block_q6_K * src = (const block_q6_K *) data;
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK_K;
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_K != 0) {
return -1;
}
const ptrdiff_t row_stride = (ptrdiff_t) nblocks * sizeof(block_q6_K);
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int bi = 0; bi < 8; bi++) {
// --- 1) Gather 32 d values with stride load ---
// We need to compute reflect_scale per row first, so gather d later.
// Process each row: dequant Q6_K sub-block -> requant to Q8_0
for (int i = 0; i < nrows_interleaved; i++) {
const block_q6_K * src_blk = &src[x + i * nblocks];
const uint8_t * q4 = src_blk->ql + 64 * (bi / 4);
const uint8_t * qh = src_blk->qh + 32 * (bi / 4);
const int8_t * scales = src_blk->scales;
float d = GGML_FP16_TO_FP32(src_blk->d);
int8_t bi_idx = bi % 4;
// --- Dequant 32 Q6_K values to int6 (range [-32, 31]) using RVV ---
// vl = 32 for e8m2 (VLEN=256) or loop for smaller VLEN
const size_t vl16 = __riscv_vsetvl_e8m1(16);
vint8m1_t va_lo, va_hi; // 16 elements each
if (bi_idx == 0) {
// a[l] = (q4[l] & 0xF) | (((qh[l] >> 0) & 3) << 4) - 32
vuint8m1_t vq4_lo = __riscv_vle8_v_u8m1(q4, vl16);
vuint8m1_t vq4_hi = __riscv_vle8_v_u8m1(q4 + 16, vl16);
vuint8m1_t vqh_lo = __riscv_vle8_v_u8m1(qh, vl16);
vuint8m1_t vqh_hi = __riscv_vle8_v_u8m1(qh + 16, vl16);
vuint8m1_t vlo4_lo = __riscv_vand_vx_u8m1(vq4_lo, 0x0F, vl16);
vuint8m1_t vlo4_hi = __riscv_vand_vx_u8m1(vq4_hi, 0x0F, vl16);
vuint8m1_t vh_lo = __riscv_vsll_vx_u8m1(__riscv_vand_vx_u8m1(vqh_lo, 0x03, vl16), 4, vl16);
vuint8m1_t vh_hi = __riscv_vsll_vx_u8m1(__riscv_vand_vx_u8m1(vqh_hi, 0x03, vl16), 4, vl16);
vuint8m1_t vcomb_lo = __riscv_vor_vv_u8m1(vlo4_lo, vh_lo, vl16);
vuint8m1_t vcomb_hi = __riscv_vor_vv_u8m1(vlo4_hi, vh_hi, vl16);
va_lo = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_lo), 32, vl16);
va_hi = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_hi), 32, vl16);
} else if (bi_idx == 1) {
// a[l] = (q4[l+32] & 0xF) | (((qh[l] >> 2) & 3) << 4) - 32
vuint8m1_t vq4_lo = __riscv_vle8_v_u8m1(q4 + 32, vl16);
vuint8m1_t vq4_hi = __riscv_vle8_v_u8m1(q4 + 48, vl16);
vuint8m1_t vqh_lo = __riscv_vle8_v_u8m1(qh, vl16);
vuint8m1_t vqh_hi = __riscv_vle8_v_u8m1(qh + 16, vl16);
vuint8m1_t vlo4_lo = __riscv_vand_vx_u8m1(vq4_lo, 0x0F, vl16);
vuint8m1_t vlo4_hi = __riscv_vand_vx_u8m1(vq4_hi, 0x0F, vl16);
vuint8m1_t vh_lo = __riscv_vsll_vx_u8m1(
__riscv_vand_vx_u8m1(__riscv_vsrl_vx_u8m1(vqh_lo, 2, vl16), 0x03, vl16), 4, vl16);
vuint8m1_t vh_hi = __riscv_vsll_vx_u8m1(
__riscv_vand_vx_u8m1(__riscv_vsrl_vx_u8m1(vqh_hi, 2, vl16), 0x03, vl16), 4, vl16);
vuint8m1_t vcomb_lo = __riscv_vor_vv_u8m1(vlo4_lo, vh_lo, vl16);
vuint8m1_t vcomb_hi = __riscv_vor_vv_u8m1(vlo4_hi, vh_hi, vl16);
va_lo = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_lo), 32, vl16);
va_hi = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_hi), 32, vl16);
} else if (bi_idx == 2) {
// a[l] = (q4[l] >> 4) | (((qh[l] >> 4) & 3) << 4) - 32
vuint8m1_t vq4_lo = __riscv_vle8_v_u8m1(q4, vl16);
vuint8m1_t vq4_hi = __riscv_vle8_v_u8m1(q4 + 16, vl16);
vuint8m1_t vqh_lo = __riscv_vle8_v_u8m1(qh, vl16);
vuint8m1_t vqh_hi = __riscv_vle8_v_u8m1(qh + 16, vl16);
vuint8m1_t vhi4_lo = __riscv_vsrl_vx_u8m1(vq4_lo, 4, vl16);
vuint8m1_t vhi4_hi = __riscv_vsrl_vx_u8m1(vq4_hi, 4, vl16);
vuint8m1_t vh_lo = __riscv_vsll_vx_u8m1(
__riscv_vand_vx_u8m1(__riscv_vsrl_vx_u8m1(vqh_lo, 4, vl16), 0x03, vl16), 4, vl16);
vuint8m1_t vh_hi = __riscv_vsll_vx_u8m1(
__riscv_vand_vx_u8m1(__riscv_vsrl_vx_u8m1(vqh_hi, 4, vl16), 0x03, vl16), 4, vl16);
vuint8m1_t vcomb_lo = __riscv_vor_vv_u8m1(vhi4_lo, vh_lo, vl16);
vuint8m1_t vcomb_hi = __riscv_vor_vv_u8m1(vhi4_hi, vh_hi, vl16);
va_lo = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_lo), 32, vl16);
va_hi = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_hi), 32, vl16);
} else { // bi_idx == 3
// a[l] = (q4[l+32] >> 4) | (((qh[l] >> 6) & 3) << 4) - 32
vuint8m1_t vq4_lo = __riscv_vle8_v_u8m1(q4 + 32, vl16);
vuint8m1_t vq4_hi = __riscv_vle8_v_u8m1(q4 + 48, vl16);
vuint8m1_t vqh_lo = __riscv_vle8_v_u8m1(qh, vl16);
vuint8m1_t vqh_hi = __riscv_vle8_v_u8m1(qh + 16, vl16);
vuint8m1_t vhi4_lo = __riscv_vsrl_vx_u8m1(vq4_lo, 4, vl16);
vuint8m1_t vhi4_hi = __riscv_vsrl_vx_u8m1(vq4_hi, 4, vl16);
vuint8m1_t vh_lo = __riscv_vsll_vx_u8m1(
__riscv_vand_vx_u8m1(__riscv_vsrl_vx_u8m1(vqh_lo, 6, vl16), 0x03, vl16), 4, vl16);
vuint8m1_t vh_hi = __riscv_vsll_vx_u8m1(
__riscv_vand_vx_u8m1(__riscv_vsrl_vx_u8m1(vqh_hi, 6, vl16), 0x03, vl16), 4, vl16);
vuint8m1_t vcomb_lo = __riscv_vor_vv_u8m1(vhi4_lo, vh_lo, vl16);
vuint8m1_t vcomb_hi = __riscv_vor_vv_u8m1(vhi4_hi, vh_hi, vl16);
va_lo = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_lo), 32, vl16);
va_hi = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_hi), 32, vl16);
}
// --- Widen to i16 for scaled abs computation ---
float scale_0 = scales[bi * 2 + 0] * d;
float scale_1 = scales[bi * 2 + 1] * d;
// Widen i8 -> i16 -> f32 for abs*scale computation
vint16m2_t va_lo_w = __riscv_vsext_vf2_i16m2(va_lo, vl16);
vint16m2_t va_hi_w = __riscv_vsext_vf2_i16m2(va_hi, vl16);
// Compute |a[l] * scale_0| for lo half, |a[l] * scale_1| for hi half
vfloat32m4_t vf_lo = __riscv_vfcvt_f_x_v_f32m4(__riscv_vsext_vf2_i32m4(va_lo_w, vl16), vl16);
vfloat32m4_t vf_hi = __riscv_vfcvt_f_x_v_f32m4(__riscv_vsext_vf2_i32m4(va_hi_w, vl16), vl16);
vfloat32m4_t vabs_lo = __riscv_vfabs_v_f32m4(__riscv_vfmul_vf_f32m4(vf_lo, scale_0, vl16), vl16);
vfloat32m4_t vabs_hi = __riscv_vfabs_v_f32m4(__riscv_vfmul_vf_f32m4(vf_hi, scale_1, vl16), vl16);
// Find max abs across both halves
vfloat32m4_t vabs_max = __riscv_vfmax_vv_f32m4(vabs_lo, vabs_hi, vl16);
// Reduce to scalar max
vfloat32m1_t vzero = __riscv_vfmv_v_f_f32m1(0.0f, 1);
vfloat32m1_t vmax_red = __riscv_vfredmax_vs_f32m4_f32m1(vabs_max, vzero, vl16);
float a_max_abs = __riscv_vfmv_f_s_f32m1_f32(vmax_red);
float reflect_scale = a_max_abs / 127.0f;
float reflect_scale_0 = scale_0 / reflect_scale;
float reflect_scale_1 = scale_1 / reflect_scale;
// --- Requant: a[l] = clamp(nearbyint(a[l] * reflect_scale_x), -128, 127) ---
vfloat32m4_t vscaled_lo = __riscv_vfmul_vf_f32m4(vf_lo, reflect_scale_0, vl16);
vfloat32m4_t vscaled_hi = __riscv_vfmul_vf_f32m4(vf_hi, reflect_scale_1, vl16);
// fcvt.x rounds to nearest (using current rounding mode)
vint32m4_t vi_lo = __riscv_vfcvt_x_f_v_i32m4(vscaled_lo, vl16);
vint32m4_t vi_hi = __riscv_vfcvt_x_f_v_i32m4(vscaled_hi, vl16);
// Clamp to [-128, 127]
vi_lo = __riscv_vmax_vx_i32m4(vi_lo, -128, vl16);
vi_lo = __riscv_vmin_vx_i32m4(vi_lo, 127, vl16);
vi_hi = __riscv_vmax_vx_i32m4(vi_hi, -128, vl16);
vi_hi = __riscv_vmin_vx_i32m4(vi_hi, 127, vl16);
// Narrow i32 -> i16 -> i8
vint16m2_t vi16_lo = __riscv_vncvt_x_x_w_i16m2(vi_lo, vl16);
vint16m2_t vi16_hi = __riscv_vncvt_x_x_w_i16m2(vi_hi, vl16);
vint8m1_t vi8_lo = __riscv_vncvt_x_x_w_i8m1(vi16_lo, vl16);
vint8m1_t vi8_hi = __riscv_vncvt_x_x_w_i8m1(vi16_hi, vl16);
// Store d and qs directly into dst block
dst->d[i] = GGML_FP32_TO_FP16(reflect_scale);
int8_t * dq = (int8_t *) dst->qs + i * QK8_0;
__riscv_vse8_v_i8m1(dq, vi8_lo, vl16);
__riscv_vse8_v_i8m1(dq + 16, vi8_hi, vl16);
}
dst++;
}
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
static int repack_q8_0_to_q8_0_32_bl_ref(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q8_0);
GGML_ASSERT(interleave_block == 32); // unused
constexpr int nrows_interleaved = 32;
block_q8_0x32 * dst = (block_q8_0x32 *) t->data;
const block_q8_0 * src = (const block_q8_0 *) data;
block_q8_0 dst_tmp[32];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK8_0;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q8_0));
if (t->ne[0] % QK8_0 != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
int64_t nrows_real = std::min((int64_t) nrow - b, (int64_t) nrows_interleaved);
for (int64_t x = 0; x < nblocks; x++) {
int i = 0;
for (; i < nrows_real; i++) {
dst_tmp[i] = src[x + i * nblocks];
}
for (; i < nrows_interleaved; i++) {
memset(&dst_tmp[i], 0, sizeof(block_q8_0));
}
*dst++ = make_block_q8_0x32(dst_tmp, interleave_block);
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
// RVV optimized version of repack_q8_0_to_q8_0_32_bl
// Eliminates the intermediate dst_tmp buffer and vectorizes scale gather + qs copy.
static int repack_q8_0_to_q8_0_32_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q8_0);
GGML_ASSERT(interleave_block == 32);
constexpr int nrows_interleaved = 32;
block_q8_0x32 * dst = (block_q8_0x32 *) t->data;
const block_q8_0 * src = (const block_q8_0 *) data;
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK8_0;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q8_0));
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK8_0 != 0) {
return -1;
}
const ptrdiff_t row_stride = (ptrdiff_t) nblocks * sizeof(block_q8_0);
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
const block_q8_0 * col_src = src + x;
// --- 1) Gather 32 scale values (ggml_half d) with stride load ---
{
const uint8_t * d_base = (const uint8_t *) &col_src->d;
ggml_half * d_dst = dst->d;
size_t remaining = 32;
size_t offset = 0;
while (remaining > 0) {
size_t vl = __riscv_vsetvl_e16m1(remaining);
vuint16m1_t vd =
__riscv_vlse16_v_u16m1((const uint16_t *) (d_base + offset * row_stride), row_stride, vl);
__riscv_vse16_v_u16m1((uint16_t *) (d_dst + offset), vd, vl);
offset += vl;
remaining -= vl;
}
}
// --- 2) Copy qs for each of the 32 rows (32 bytes per row) ---
{
for (int i = 0; i < 32; i++) {
const int8_t * sq = col_src[i * nblocks].qs;
int8_t * dq = (int8_t *) dst->qs + i * QK8_0;
size_t len = QK8_0;
size_t idx = 0;
while (len > 0) {
size_t vl = __riscv_vsetvl_e8m2(len);
vint8m2_t vs = __riscv_vle8_v_i8m2(sq + idx, vl);
__riscv_vse8_v_i8m2(dq + idx, vs, vl);
idx += vl;
len -= vl;
}
}
}
dst++;
}
src += nrows_interleaved * nblocks;
}
return 0;
GGML_UNUSED(data_size);
}
static void convert_mxfp4_to_5bit(const block_mxfp4 & src, spacemit_kernels::nrow_block_mxfp4<1> & dst) {
dst.e[0] = src.e;
// Decode all 32 mxfp4 values to signed integers via kvalues_mxfp4
int8_t vals[32];
for (int j = 0; j < QK_MXFP4 / 2; j++) {
vals[j] = kvalues_mxfp4[src.qs[j] & 0xF];
vals[j + QK_MXFP4 / 2] = kvalues_mxfp4[src.qs[j] >> 4];
}
// vals [b0, b1, b2, b3, ..., b30, b31]
// Pack abs into qs with reorder: [b0,b1]..[b14,b15]..[b30,b31]
for (int j = 0; j < QK_MXFP4 / 2; j++) {
uint8_t lo0 = static_cast<uint8_t>(std::abs(vals[j * 2]));
uint8_t lo1 = static_cast<uint8_t>(std::abs(vals[j * 2 + 1]));
dst.qs[j] = (lo0 & 0x0F) | ((lo1 & 0x0F) << 4);
}
// Pack sign bits into qh[4] (32 bits total, 1 bit per weight)
// reorder: [0,1,2,...,15,16,17,...,31] after the qs reorder above
uint32_t sign_bits = 0;
for (int j = 0; j < 32; j++) {
if (vals[j] < 0) {
sign_bits |= (1u << j);
}
}
memcpy(dst.qh, &sign_bits, 4);
}
static spacemit_kernels::nrow_block_mxfp4<32> make_block_mxfp4x32(spacemit_kernels::nrow_block_mxfp4<1> * in,
unsigned int blck_size_interleave) {
spacemit_kernels::nrow_block_mxfp4<32> out;
GGML_ASSERT(QK_MXFP4 / blck_size_interleave == 1);
GGML_UNUSED(blck_size_interleave);
for (int i = 0; i < 32; i++) {
out.e[i] = in[i].e[0];
}
// qs: copy per-row 16 bytes
for (int i = 0; i < 32; i++) {
memcpy(out.qs + i * 16, in[i].qs, 16);
}
// qh: copy per-row 4 bytes
for (int i = 0; i < 32; i++) {
memcpy(out.qh + i * 4, in[i].qh, 4);
}
return out;
}
static int repack_mxfp4_to_mxfp4_32_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_MXFP4);
GGML_ASSERT(interleave_block == 32);
constexpr int nrows_interleaved = 32;
spacemit_kernels::nrow_block_mxfp4<32> * dst = (spacemit_kernels::nrow_block_mxfp4<32> *) t->data;
const block_mxfp4 * src = (const block_mxfp4 *) data;
spacemit_kernels::nrow_block_mxfp4<1> dst_tmp[32];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK_MXFP4;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_mxfp4));
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_MXFP4 != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int i = 0; i < nrows_interleaved; i++) {
convert_mxfp4_to_5bit(src[x + i * nblocks], dst_tmp[i]);
}
*dst++ = make_block_mxfp4x32(dst_tmp, interleave_block);
}
src += nrows_interleaved * nblocks;
}
return 0;
}
static spacemit_kernels::nrow_block_q5_1<32> make_block_q5_1x32(spacemit_kernels::nrow_block_q5_1<1> * in,
unsigned int blck_size_interleave) {
spacemit_kernels::nrow_block_q5_1<32> out;
GGML_ASSERT(QK5_1 / blck_size_interleave == 1);
GGML_UNUSED(blck_size_interleave);
for (int i = 0; i < 32; i++) {
out.scales16[i] = in[i].scales16[0];
out.zp[i] = in[i].zp[0];
}
// qs: low 4 bits, reorder from [b0,b16],[b1,b17]... to [b0,b1]...[b14,b15] and [b16,b17]...[b30,b31]
for (int i = 0; i < 32; i++) {
// low half [0..15]
for (int j = 0; j < QK5_1 / 4; j++) {
out.qs[i * QK5_1 / 2 + j] = (in[i].qs[j * 2] & 0x0F) | ((in[i].qs[j * 2 + 1] & 0x0F) << 4);
}
// high half [16..31]
for (int j = 0; j < QK5_1 / 4; j++) {
out.qs[i * QK5_1 / 2 + QK5_1 / 4 + j] = ((in[i].qs[j * 2] & 0xF0) >> 4) | (in[i].qs[j * 2 + 1] & 0xF0);
}
}
// qh: 5th bit, copy directly
for (int i = 0; i < 32; i++) {
for (int j = 0; j < 4; j++) {
out.qh[i * 4 + j] = in[i].qh[j];
}
}
return out;
}
static spacemit_kernels::nrow_block_q5_0<32> make_block_q5_0x32(spacemit_kernels::nrow_block_q5_0<1> * in,
unsigned int blck_size_interleave) {
spacemit_kernels::nrow_block_q5_0<32> out;
GGML_ASSERT(QK5_0 / blck_size_interleave == 1);
GGML_UNUSED(blck_size_interleave);
for (int i = 0; i < 32; i++) {
out.scales16[i] = in[i].scales16[0];
}
// qs: low 4 bits, reorder from [b0,b16],[b1,b17]... to [b0,b1]...[b14,b15] and [b16,b17]...[b30,b31]
for (int i = 0; i < 32; i++) {
// low half [0..15]
for (int j = 0; j < QK5_0 / 4; j++) {
out.qs[i * QK5_0 / 2 + j] = (in[i].qs[j * 2] & 0x0F) | ((in[i].qs[j * 2 + 1] & 0x0F) << 4);
}
// high half [16..31]
for (int j = 0; j < QK5_0 / 4; j++) {
out.qs[i * QK5_0 / 2 + QK5_0 / 4 + j] = ((in[i].qs[j * 2] & 0xF0) >> 4) | (in[i].qs[j * 2 + 1] & 0xF0);
}
}
// qh: 5th bit, copy directly
for (int i = 0; i < 32; i++) {
for (int j = 0; j < 4; j++) {
out.qh[i * 4 + j] = in[i].qh[j];
}
}
return out;
}
static int repack_q5_0_to_q5_0_32_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q5_0);
GGML_ASSERT(interleave_block == 32); // unused
constexpr int nrows_interleaved = 32;
spacemit_kernels::nrow_block_q5_0<32> * dst = (spacemit_kernels::nrow_block_q5_0<32> *) t->data;
const block_q5_0 * src = (const block_q5_0 *) data;
spacemit_kernels::nrow_block_q5_0<1> dst_tmp[32];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK5_0;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q5_0));
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK5_0 != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int i = 0; i < nrows_interleaved; i++) {
const block_q5_0 & s = src[x + i * nblocks];
dst_tmp[i].scales16[0] = s.d;
memcpy(dst_tmp[i].qs, s.qs, sizeof(dst_tmp[i].qs));
memcpy(dst_tmp[i].qh, s.qh, sizeof(dst_tmp[i].qh));
}
*dst++ = make_block_q5_0x32(dst_tmp, interleave_block);
}
src += nrows_interleaved * nblocks;
}
return 0;
}
static int repack_q5_1_to_q5_1_32_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q5_1);
GGML_ASSERT(interleave_block == 32); // unused
constexpr int nrows_interleaved = 32;
spacemit_kernels::nrow_block_q5_1<32> * dst = (spacemit_kernels::nrow_block_q5_1<32> *) t->data;
const block_q5_1 * src = (const block_q5_1 *) data;
spacemit_kernels::nrow_block_q5_1<1> dst_tmp[32];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK5_1;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q5_1));
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK5_1 != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int i = 0; i < nrows_interleaved; i++) {
const block_q5_1 & s = src[x + i * nblocks];
float d = GGML_FP16_TO_FP32(s.GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d);
float m = GGML_FP16_TO_FP32(s.GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.m);
if (d == 0.0f) {
dst_tmp[i].scales16[0] = GGML_FP32_TO_FP16(std::fabs(m));
dst_tmp[i].zp[0] = m < 0.0f ? 1 : 0;
memset(dst_tmp[i].qh, 0, sizeof(dst_tmp[i].qh));
memset(dst_tmp[i].qs, m > 0.0f ? 0x11 : 0x00, sizeof(dst_tmp[i].qs));
continue;
}
float mid = std::nearbyintf(-m / d);
mid = std::min(31.0f, std::max(0.0f, mid));
dst_tmp[i].scales16[0] = GGML_FP32_TO_FP16(d);
dst_tmp[i].zp[0] = static_cast<uint8_t>(mid);
// qs: copy low 4 bits directly (same nibble packing)
memcpy(dst_tmp[i].qs, s.qs, QK5_1 / 2);
// qh: copy 5th bit directly
memcpy(dst_tmp[i].qh, s.qh, 4);
}
*dst++ = make_block_q5_1x32(dst_tmp, interleave_block);
}
src += nrows_interleaved * nblocks;
}
return 0;
}
static int repack_q5_k_to_q5_1_32_bl(ggml_tensor * t,
int interleave_block,
const void * GGML_RESTRICT data,
size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q5_K);
GGML_ASSERT(interleave_block == 32);
GGML_ASSERT(QK_K / QK5_1 == 8);
constexpr int nrows_interleaved = 32;
spacemit_kernels::nrow_block_q5_1<32> * dst = (spacemit_kernels::nrow_block_q5_1<32> *) t->data;
const block_q5_K * src = (const block_q5_K *) data;
spacemit_kernels::nrow_block_q5_1<1> dst_tmp[32];
int nrow = ggml_nrows(t);
int nblocks = t->ne[0] / QK_K;
if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_K != 0) {
return -1;
}
for (int b = 0; b < nrow; b += nrows_interleaved) {
for (int64_t x = 0; x < nblocks; x++) {
for (int j = 0; j < 8; j++) {
for (int i = 0; i < nrows_interleaved; i++) {
uint8_t sc, m;
const float d = GGML_FP16_TO_FP32(src[x + i * nblocks].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d);
const float min =
GGML_FP16_TO_FP32(src[x + i * nblocks].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.dmin);
get_scale_min_k4(j, src[x + i * nblocks].scales, &sc, &m);
float d1 = d * sc;
float m1 = min * m;
float mid = std::nearbyintf(m1 / d1);
mid = std::min(31.0f, std::max(0.0f, mid));
dst_tmp[i].scales16[0] = GGML_FP32_TO_FP16(d1);
dst_tmp[i].zp[0] = static_cast<uint8_t>(mid);
// src -> [b0, b32] [b1, b33] ... [b31, b63]
// dst -> [b0, b16] [b1, b17] ... [b15, b31] [b32, b48] [b33, b49] ... [b47, b63]
const uint8_t * q = src[x + i * nblocks].qs + (j / 2) * QK5_1;
if (j % 2 == 0) {
for (int ii = 0; ii < 16; ii++) {
dst_tmp[i].qs[ii] = (q[ii] & 0x0F) | ((q[ii + 16] & 0x0F) << 4);
}
} else {
for (int ii = 0; ii < 16; ii++) {
dst_tmp[i].qs[ii] = ((q[ii] & 0xF0) >> 4) | (q[ii + 16] & 0xF0);
}
}
// Extract the 5th bit (qh) for this sub-block
// block_q5_K.qh[32]: for sub-block j, the 5th bit is at bit position j in qh[l]
// qs was reordered: dst_qs maps to src weights [0,16,1,17,...,15,31]
// So qh must follow the same reorder to stay aligned with qs
// dst qh[4] = 32 bits for 32 weights in the reordered layout:
// byte 0: weights 0..7 (from src_qh[0..7])
// byte 1: weights 8..15 (from src_qh[8..15])
// byte 2: weights 16..23 (from src_qh[16..23])
// byte 3: weights 24..31 (from src_qh[24..31])
const uint8_t * src_qh = src[x + i * nblocks].qh;
for (int bi = 0; bi < 4; bi++) {
uint8_t qh_byte = 0;
for (int k = 0; k < 8; k++) {
int src_idx = bi * 8 + k;
qh_byte |= ((src_qh[src_idx] >> j) & 1) << k;
}
dst_tmp[i].qh[bi] = qh_byte;
}
}
*dst++ = make_block_q5_1x32(dst_tmp, interleave_block);
}
}
src += nrows_interleaved * nblocks;
}
return 0;
}
namespace ggml::cpu::riscv64_spacemit {
template <typename BLOC_TYPE, int64_t INTER_SIZE, int64_t NB_COLS> int repack(ggml_tensor *, const void *, size_t);
template <> int repack<block_q4_0, 32, 16>(ggml_tensor * t, const void * data, size_t data_size) {
return repack_q4_0_to_q4_0_16_bl(t, 16, data, data_size);
}
template <> int repack<block_q4_1, 32, 16>(ggml_tensor * t, const void * data, size_t data_size) {
return repack_q4_1_to_q4_1_16_bl(t, 16, data, data_size);
}
template <> int repack<block_q4_K, 32, 16>(ggml_tensor * t, const void * data, size_t data_size) {
return repack_q4_k_to_q4_1_16_bl(t, 16, data, data_size);
}
template <> int repack<block_q2_K, 256, 32>(ggml_tensor * t, const void * data, size_t data_size) {
return repack_q2_k_to_q2_k_32_bl(t, 32, data, data_size);
}
template <> int repack<block_q3_K, 256, 32>(ggml_tensor * t, const void * data, size_t data_size) {
return repack_q3_k_to_q3_k_32_bl(t, 32, data, data_size);
}
template <> int repack<block_q4_0, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) {
#if 0
return repack_q4_0_to_q4_0_32_bl_ref(t, 32, data, data_size);
#else
return repack_q4_0_to_q4_0_32_bl(t, 32, data, data_size);
#endif
}
template <> int repack<block_q4_0, 256, 32>(ggml_tensor * t, const void * data, size_t data_size) {
#if 1
return repack_q4_0_to_q4_0_256_32_bl_ref(t, 32, data, data_size);
#else
//return repack_q4_0_to_q4_0_256_32_bl(t, 32, data, data_size);
#endif
}
template <> int repack<block_q4_1, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) {
#if 0
return repack_q4_1_to_q4_1_32_bl_ref(t, 32, data, data_size);
#else
return repack_q4_1_to_q4_1_32_bl(t, 32, data, data_size);
#endif
}
template <> int repack<block_q4_1, 256, 32>(ggml_tensor * t, const void * data, size_t data_size) {
#if 1
return repack_q4_0_to_q4_1_256_32_bl_ref(t, 32, data, data_size);
#else
return repack_q4_1_to_q4_1_256_32_bl(t, 32, data, data_size);
#endif
}
template <> int repack<block_q4_K, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) {
return repack_q4_k_to_q4_1_32_bl(t, 32, data, data_size);
}
template <> int repack<block_q6_K, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) {
#if 1
return repack_q6_k_to_q8_0_32_bl_ref(t, 32, data, data_size);
#else
return repack_q6_k_to_q8_0_32_bl(t, 32, data, data_size);
#endif
}
template <> int repack<block_q8_0, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) {
#if 1
return repack_q8_0_to_q8_0_32_bl_ref(t, 32, data, data_size);
#else
return repack_q8_0_to_q8_0_32_bl(t, 32, data, data_size);
#endif
}
template <> int repack<block_mxfp4, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) {
return repack_mxfp4_to_mxfp4_32_bl(t, 32, data, data_size);
}
template <> int repack<block_q5_0, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) {
return repack_q5_0_to_q5_0_32_bl(t, 32, data, data_size);
}
template <> int repack<block_q5_1, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) {
return repack_q5_1_to_q5_1_32_bl(t, 32, data, data_size);
}
template <> int repack<block_q5_K, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) {
return repack_q5_k_to_q5_1_32_bl(t, 32, data, data_size);
}
} // namespace ggml::cpu::riscv64_spacemit