ikawrakow/ik_llama.cpp
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iq2_kt: NEON implementation

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Iwan Kawrakow
2025-05-24 18:25:24 +03:00
parent c7ecd4e23a
commit 5e684c1616
3 changed files with 154 additions and 32 deletions
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18
ggml/src/ggml.c
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@@ -1583,7 +1583,11 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
.from_float = quantize_row_iq2_kt,
.from_float_ref = (ggml_from_float_t)quantize_row_iq2_kt_ref,
.vec_dot = vec_dot_iq2_kt_q8_k,
.vec_dot_type = GGML_TYPE_Q8_K,
#ifdef __ARM_NEON
.vec_dot_type = GGML_TYPE_F16,
#else
.vec_dot_type = GGML_TYPE_F32,
#endif
.nrows = 1,
.row_meta_size = 4,
},
@@ -1596,7 +1600,11 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
.from_float = quantize_row_iq3_kt,
.from_float_ref = (ggml_from_float_t)quantize_row_iq3_kt_ref,
.vec_dot = vec_dot_iq3_kt_q8_k,
.vec_dot_type = GGML_TYPE_Q8_K,
#ifdef __ARM_NEON
.vec_dot_type = GGML_TYPE_F16,
#else
.vec_dot_type = GGML_TYPE_F32,
#endif
.nrows = 1,
.row_meta_size = 4,
},
@@ -1609,7 +1617,11 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
.from_float = quantize_row_iq4_kt,
.from_float_ref = (ggml_from_float_t)quantize_row_iq4_kt_ref,
.vec_dot = vec_dot_iq4_kt_q8_k,
.vec_dot_type = GGML_TYPE_Q8_K,
#ifdef __ARM_NEON
.vec_dot_type = GGML_TYPE_F16,
#else
.vec_dot_type = GGML_TYPE_F32,
#endif
.nrows = 1,
.row_meta_size = 8,
},

162
ggml/src/iqk/iqk_gemm_ktquants.cpp
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@@ -1,3 +1,4 @@
#include "iqk_common.h"
#include "iqk_gemm_ktquants.h"
#include "ggml.h"
@@ -316,37 +317,13 @@ bool iqk_set_kernels_ktquants(int ne00, int typeA, int typeB, std::array<mul_mat
switch (typeA) {
case GGML_TYPE_IQ2_KT:
assert (ne00 % QK_K == 0);
kernels[0] = mul_mat_iq2_kt_F32_T<1>;
kernels[1] = mul_mat_iq2_kt_F32_T<2>;
kernels[2] = mul_mat_iq2_kt_F32_T<3>;
kernels[3] = mul_mat_iq2_kt_F32_T<4>;
kernels[4] = mul_mat_iq2_kt_F32_T<5>;
kernels[5] = mul_mat_iq2_kt_F32_T<6>;
kernels[6] = mul_mat_iq2_kt_F32_T<7>;
kernels[7] = mul_mat_iq2_kt_F32_T<8>;
IQK_SET_MUL_MAT_FUNCTIONS(mul_mat_iq2_kt_F32_T, kernels);
break;
case GGML_TYPE_IQ3_KT:
assert (ne00 % QK_K == 0);
kernels[0] = mul_mat_iq3_kt_F32_T<1>;
kernels[1] = mul_mat_iq3_kt_F32_T<2>;
kernels[2] = mul_mat_iq3_kt_F32_T<3>;
kernels[3] = mul_mat_iq3_kt_F32_T<4>;
kernels[4] = mul_mat_iq3_kt_F32_T<5>;
kernels[5] = mul_mat_iq3_kt_F32_T<6>;
kernels[6] = mul_mat_iq3_kt_F32_T<7>;
kernels[7] = mul_mat_iq3_kt_F32_T<8>;
IQK_SET_MUL_MAT_FUNCTIONS(mul_mat_iq3_kt_F32_T, kernels);
break;
case GGML_TYPE_IQ4_KT:
assert (ne00 % QK_K == 0);
kernels[0] = mul_mat_iq4_kt_F32_T<1>;
kernels[1] = mul_mat_iq4_kt_F32_T<2>;
kernels[2] = mul_mat_iq4_kt_F32_T<3>;
kernels[3] = mul_mat_iq4_kt_F32_T<4>;
kernels[4] = mul_mat_iq4_kt_F32_T<5>;
kernels[5] = mul_mat_iq4_kt_F32_T<6>;
kernels[6] = mul_mat_iq4_kt_F32_T<7>;
kernels[7] = mul_mat_iq4_kt_F32_T<8>;
IQK_SET_MUL_MAT_FUNCTIONS(mul_mat_iq4_kt_F32_T, kernels);
break;
default:
return false;
@@ -358,8 +335,137 @@ bool iqk_set_kernels_ktquants(int ne00, int typeA, int typeB, std::array<mul_mat
#else // !__x86_64__
namespace {
struct Trellis1 {
constexpr static uint32_t kmask = 0x8fff8fff;
constexpr static uint32_t km32 = 0x3b603b60;
constexpr static uint32_t ka = 89226354;
constexpr static uint32_t kb = 64248484;
constexpr static uint32_t ka1 = ka*ka;
constexpr static uint32_t kb1 = kb*ka+kb;
constexpr static uint32_t ka2 = ka1*ka;
constexpr static uint32_t kb2 = kb1*ka+kb;
constexpr static uint32_t ka3 = ka2*ka;
constexpr static uint32_t kb3 = kb2*ka+kb;
constexpr static uint32_t ka4 = ka3*ka;
constexpr static uint32_t kb4 = kb3*ka+kb;
constexpr static uint32_t ka5 = ka4*ka;
constexpr static uint32_t kb5 = kb4*ka+kb;
constexpr static uint32_t ka6 = ka5*ka;
constexpr static uint32_t kb6 = kb5*ka+kb;
constexpr static uint32_t ka7 = ka6*ka;
constexpr static uint32_t kb7 = kb6*ka+kb;
const uint32x4x2_t mka = {uint32x4_t{ka, ka1, ka2, ka3}, uint32x4_t{ka4, ka5, ka6, ka7}};
const uint32x4x2_t mkb = {uint32x4_t{kb, kb1, kb2, kb3}, uint32x4_t{kb4, kb5, kb6, kb7}};
const uint32x4_t mask1 = vdupq_n_u32(kmask);
const uint32x4_t mask2 = vdupq_n_u32(km32);
inline uint32x4x2_t next8(uint32_t val) const {
auto mval = vdupq_n_u32(val);
uint32x4x2_t mres;
mres.val[0] = vaddq_u32(vmulq_u32(mval, mka.val[0]), mkb.val[0]);
mres.val[1] = vaddq_u32(vmulq_u32(mval, mka.val[1]), mkb.val[1]);
mres.val[0] = veorq_u32(vandq_u32(mres.val[0], mask1), mask2);
mres.val[1] = veorq_u32(vandq_u32(mres.val[1], mask1), mask2);
return mres;
}
static inline float16x8_t gen8(const uint32x4x2_t& i8) {
auto fv1 = vreinterpretq_f16_u32(i8.val[0]);
auto fv2 = vreinterpretq_f16_u32(i8.val[1]);
return vpaddq_f16(fv1, fv2);
}
inline float16x8_t gen8(uint32_t val) const { return gen8(next8(val)); }
};
template <int nrc_y>
static void mul_mat_iq2_kt_F16_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
assert(n%QK_K == 0);
const int nb = n/QK_K;
Trellis1 trellis;
auto values = vld1q_s8(iq4k_values);
union { float16x8_t vec; float16_t val[8]; } s_helper;
constexpr int k_acc = nrc_y == 1 ? 2 : nrc_y;
float16x8_t accd[k_acc];
const float16_t * y[nrc_y];
for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const float16_t *)info.src1_row(iy);
for (int ix = 0; ix < nrc_x; ++ix) {
const float * dptr = (const float *)((const char*)vx + ix*bx);
const float d = *dptr * 31.75f * 1.05f;
const block_iq2_kt * x = (const block_iq2_kt *)(dptr + 1);
for (int iy = 0; iy < k_acc; ++iy) accd[iy] = vdupq_n_f16(0);
for (int i = 0; i < nb; ++i) {
const uint16_t * ql = (const uint16_t *)x[i].ql;
auto u32 = *(const uint32_t *)x[i].scales;
auto s8_u32 = uint32x2_t{u32, u32 >> 4};
s8_u32 = vand_u8(s8_u32, vdup_n_u32(0x0f0f0f0f));
auto s8 = vqtbl1_s8(values, vreinterpret_u8_u32(s8_u32));
auto s16 = vmovl_s8(s8);
s_helper.vec = vcvtq_f16_s16(s16);
for (int ib = 0; ib < QK_K/64; ++ib) {
auto scale1 = vdupq_n_f16(s_helper.val[2*ib+0]);
auto scale2 = vdupq_n_f16(s_helper.val[2*ib+1]);
for (int j = 0; j < 4; ++j) {
auto xval1 = vmulq_f16(scale1, trellis.gen8(ql[8*ib+j+0]+4096));
auto xval2 = vmulq_f16(scale2, trellis.gen8(ql[8*ib+j+4]+4096));
if constexpr (nrc_y == 1) {
accd[0] = vfmaq_f16(accd[0], xval1, vld1q_f16(y[0] + i*QK_K + 64*ib + 8*j + 0));
accd[1] = vfmaq_f16(accd[1], xval2, vld1q_f16(y[0] + i*QK_K + 64*ib + 8*j + 32));
} else {
for (int iy = 0; iy < nrc_y; ++iy) {
accd[iy] = vfmaq_f16(accd[iy], xval1, vld1q_f16(y[iy] + i*QK_K + 64*ib + 8*j + 0));
accd[iy] = vfmaq_f16(accd[iy], xval2, vld1q_f16(y[iy] + i*QK_K + 64*ib + 8*j + 32));
}
}
}
}
}
if constexpr (nrc_y == 1) {
auto res16 = vpaddq_f16(accd[0], accd[1]);
auto res = vaddq_f32(vcvt_f32_f16(vget_low_f16(res16)), vcvt_f32_f16(vget_high_f16(res16)));
info.store(ix, 0, vaddvq_f32(res)*d);
} else {
for (int iy = 0; iy < nrc_y; ++iy) {
auto res = vaddq_f32(vcvt_f32_f16(vget_low_f16(accd[iy])), vcvt_f32_f16(vget_high_f16(accd[iy])));
info.store(ix, iy, vaddvq_f32(res)*d);
}
}
}
}
}
bool iqk_set_kernels_ktquants(int ne00, int typeA, int typeB, std::array<mul_mat_t, IQK_MAX_NY>& kernels, mul_mat_t& func16) {
return false;
if (ne00%QK_K != 0 || ggml_type(typeB) != GGML_TYPE_F16) {
return false;
}
func16 = nullptr;
switch (typeA) {
case GGML_TYPE_IQ2_KT:
IQK_SET_MUL_MAT_FUNCTIONS(mul_mat_iq2_kt_F16_T, kernels);
break;
//case GGML_TYPE_IQ3_KT:
// IQK_SET_MUL_MAT_FUNCTIONS(mul_mat_iq3_kt_F32_T, kernels);
// break;
//case GGML_TYPE_IQ4_KT:
// IQK_SET_MUL_MAT_FUNCTIONS(mul_mat_iq4_kt_F32_T, kernels);
// break;
default:
return false;
}
return true;
}
#endif

6
ggml/src/iqk/iqk_mul_mat.cpp
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@@ -651,6 +651,10 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& m, int /*Ny*/) {
case GGML_TYPE_IQ1_S_R4:
case GGML_TYPE_IQ1_M_R4:
return iqk_set_kernels_1bit(ne00, typeA, typeB, m.funcs, m.func16);
case GGML_TYPE_IQ2_KT:
case GGML_TYPE_IQ3_KT:
case GGML_TYPE_IQ4_KT:
return ggml_type(typeB) == GGML_TYPE_F16 ? iqk_set_kernels_ktquants(ne00, typeA, typeB, m.funcs, m.func16) : false;
default:
return false;
}
@@ -926,4 +930,4 @@ extern "C" IQK_API bool iqk_moe_fused_up_gate(long /*Nx*/, long /*Ny*/, long /*n
return false;
}
#endif
#endif