diff options
author | Kawrakow <iwankawrakow@gmail.com> | 2025-05-22 10:05:51 +0300 |
---|---|---|
committer | GitHub <noreply@github.com> | 2025-05-22 10:05:51 +0300 |
commit | b94cd3b632a78dfb46b18d52b84be66bcf26166a (patch) | |
tree | b65a5e45edad37f95301174d6971614950a8d489 /ggml/src/iqk/iqk_gemm_floats.cpp | |
parent | a2b5057a0c9a2758830b6f841bb22150d2511bb1 (diff) |
Refactor iqk_mul_mat.cpp (#435)
* Refactor iqk: WIP
* Refactor iqk: Factor out float GEMM (AVX2/AVX512)
* Refactor iqk: Factor out GEMM for legacy quants (AVX2/AVX512)
* Refactor iqk: Factor out GEMM for k-quants (AVX2/AVX512)
* Refactor iqk: fix AVX2
* Refactor iqk: Factor out GEMM for i-quants (AVX2/AVX512)
* Refactor iqk: fix AVX2
* Refactor iqk: Factor out GEMM for iqk-quants (AVX2/AVX512)
* Refactor iqk: fix AVX2
* Refactor iqk: Factor out GEMM for 1-bit quants (ABX2/AVX512)
* Refactor iqk: fix AVX2
* Refactor iqk: Factor out GEMM for iq1_bn, iq2_bn, iq2_bn_r4
* Refactor iqk: Factor out GEMM for repacked legacy quants
* Refactor iqk: Factor out GEMM for q8_K_R8, q8_KV
* Refactor iqk: Factor out GEMM for repacked i-quants
* Refactor iqk: GEMM kernels are refactored on AVX2/AVX512
* Refactor iqk: factor out 1-bit quants (NEON)
* Refactor iqk: factor out k-quants (NEON)
* Refactor iqk: factor out floats (NEON)
* Also iq4_xs belongs to k-quants
* Refactor iqk: factor out iqk quants (NEON)
* Refactor iqk: factor out legacy quants (NEON)
* Refactor iqk: factor out repacked legacy quants (NEON)
* Refactor iqk: factor out repacked k-quants (NEON)
* Refactor iqk: factor out repacked iqk quants (NEON)
* Refactor iqk: GEMM kernels are refactored on NEON
* Refactor iqk: FA compiles
If it works is a different story.
Current compile time: 107.3 sesonds on the Ryzen-7950X
* Refactor iqk: FA refactored (Zen4)
Compile time for the FA files is now ~21 seconds on my
Ryzen-7950X, so still slightly too long for my taste
but much better than the 142 seconds we had before.
* Adding forgotten file
* Most helpers don't need to be templates
Also hide Q4_0 and Q8_KV behind IQK_FA_ALL_QUANTS.
Compilation time drops to 14 second on the Ryzen-5975WX
* Fix bf16
* Refactor iqk: FA refactored (NEON)
* Forgotten MMQ ref and typo (#431)
* Adding forgotten iq5_k_r4
* Fix iq4_k_r4 on NEON
* Fix iq4_ks on NEON
It was broken before the refactoring (the shifts were not correctly
applied).
* Fix q8_0 on NEON
* Fix q6_0 K cache
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Co-authored-by: Nexes the Elder <124105151+Nexesenex@users.noreply.github.com>
Diffstat (limited to 'ggml/src/iqk/iqk_gemm_floats.cpp')
-rw-r--r-- | ggml/src/iqk/iqk_gemm_floats.cpp | 1048 |
1 files changed, 1048 insertions, 0 deletions
diff --git a/ggml/src/iqk/iqk_gemm_floats.cpp b/ggml/src/iqk/iqk_gemm_floats.cpp new file mode 100644 index 00000000..5165eb98 --- /dev/null +++ b/ggml/src/iqk/iqk_gemm_floats.cpp @@ -0,0 +1,1048 @@ +#include "iqk_gemm_floats.h" + +#ifdef IQK_IMPLEMENT + +#include "ggml-impl.h" + +#define GGML_COMMON_IMPL_C +#include "ggml-common.h" + +#ifdef __x86_64__ + +namespace { + +// float matrices - we handle f16, bf16 (if native bf16 support is available) and f32, but only to f32 result + +struct QFBase { +#ifdef __AVX512F__ + constexpr static int k_step = 16; + using Data = __m512; + using Acc = __m512; + static inline Data load(const ggml_half * x) { return _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)x)); } + static inline Data load(const float * x) { return _mm512_loadu_ps(x); } + static inline Data load(const ggml_bf16_t * x) { + return _mm512_castsi512_ps(_mm512_slli_epi32(_mm512_cvtepu16_epi32(_mm256_loadu_si256((const __m256i*)x)), 16)); + } + static inline Acc acc(Acc prev, const Data& y, const Data& x) { + return _mm512_fmadd_ps(y, x, prev); + } + static inline Acc acc_first(const Data& y, const Data& x) { + return _mm512_mul_ps(y, x); + } + static inline Acc add(Acc x, Acc y) { return _mm512_add_ps(x, y); } + static inline float hsum(Acc acc) { + return _mm512_reduce_add_ps(acc); + } + template <typename Float> + static inline Data load4Floats(const Float * x) { + return _mm512_insertf32x4(_mm512_setzero_ps(), load128(x), 0); + } + static inline Acc acc_r4(Acc acc, const Data * xv, const Data& yv) { + acc = _mm512_fmadd_ps(xv[0], _mm512_shuffle_ps(yv, yv, 0x00), acc); + acc = _mm512_fmadd_ps(xv[1], _mm512_shuffle_ps(yv, yv, 0x55), acc); + acc = _mm512_fmadd_ps(xv[2], _mm512_shuffle_ps(yv, yv, 0xaa), acc); + acc = _mm512_fmadd_ps(xv[3], _mm512_shuffle_ps(yv, yv, 0xff), acc); + return acc; + } + static inline Acc acc_r4_first(const Data * xv, const Data& yv) { + auto acc = _mm512_mul_ps(xv[0], _mm512_shuffle_ps(yv, yv, 0x00)); + acc = _mm512_fmadd_ps(xv[1], _mm512_shuffle_ps(yv, yv, 0x55), acc); + acc = _mm512_fmadd_ps(xv[2], _mm512_shuffle_ps(yv, yv, 0xaa), acc); + acc = _mm512_fmadd_ps(xv[3], _mm512_shuffle_ps(yv, yv, 0xff), acc); + return acc; + } + static inline __m128 hsum_r4(Acc acc) { + auto sum1 = _mm_add_ps(_mm512_extractf32x4_ps(acc, 0), _mm512_extractf32x4_ps(acc, 1)); + auto sum2 = _mm_add_ps(_mm512_extractf32x4_ps(acc, 2), _mm512_extractf32x4_ps(acc, 3)); + return _mm_add_ps(sum1, sum2); + } +#else + constexpr static int k_step = 8; + using Data = __m256; + using Acc = __m256; + static inline Data load(const ggml_half * x) { return _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)x)); } + static inline Data load(const float * x) { return _mm256_loadu_ps(x); } + static inline Data load(const ggml_bf16_t * x) { + return _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_cvtepu16_epi32(_mm_loadu_si128((const __m128i*)x)), 16)); + } + static inline Acc acc(Acc prev, const Data& y, const Data& x) { + return _mm256_fmadd_ps(y, x, prev); + } + static inline Acc add(Acc x, Acc y) { return _mm256_add_ps(x, y); } + static inline Acc acc_r4(Acc acc, const Data * xv, const Data& yv) { + acc = _mm256_fmadd_ps(xv[0], _mm256_shuffle_ps(yv, yv, 0x00), acc); + acc = _mm256_fmadd_ps(xv[1], _mm256_shuffle_ps(yv, yv, 0x55), acc); + acc = _mm256_fmadd_ps(xv[2], _mm256_shuffle_ps(yv, yv, 0xaa), acc); + acc = _mm256_fmadd_ps(xv[3], _mm256_shuffle_ps(yv, yv, 0xff), acc); + return acc; + } + static inline Acc acc_r4_first(const Data * xv, const Data& yv) { + auto acc = _mm256_mul_ps(xv[0], _mm256_shuffle_ps(yv, yv, 0x00)); + acc = _mm256_fmadd_ps(xv[1], _mm256_shuffle_ps(yv, yv, 0x55), acc); + acc = _mm256_fmadd_ps(xv[2], _mm256_shuffle_ps(yv, yv, 0xaa), acc); + acc = _mm256_fmadd_ps(xv[3], _mm256_shuffle_ps(yv, yv, 0xff), acc); + return acc; + } + static inline Acc acc_first(const Data& y, const Data& x) { + return _mm256_mul_ps(y, x); + } + static inline float hsum(Acc acc) { + return hsum_float_8(acc); + } + static inline __m128 hsum_r4(Acc acc) { + return _mm_add_ps(_mm256_castps256_ps128(acc), _mm256_extractf128_ps(acc, 1)); + } + template <typename Float> + static inline Data load4Floats(const Float * x) { + return _mm256_insertf128_ps(_mm256_setzero_ps(), load128(x), 0); + } +#endif + static inline __m128 load128(const ggml_half * x) { return _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)x)); } + static inline __m128 load128(const float * x) { return _mm_loadu_ps(x); } + static inline __m128 load128(const ggml_bf16_t * x) { + return _mm_castsi128_ps(_mm_slli_epi32(_mm_cvtepu16_epi32(_mm_loadl_epi64((const __m128i*)x)), 16)); + } +}; + +template <typename Float, int nrc_in> struct QFT final : public QFBase { + constexpr static int nrc = nrc_in; + QFT(const DataInfo& info) { + for (int iy = 0; iy < nrc; ++iy) y[iy] = (const Float *)info.src1_row(iy); + } + QFT(const char * cx, size_t bx) { + for (int iy = 0; iy < nrc; ++iy) y[iy] = (const Float *)(cx + iy*bx); + } + IQK_ALWAYS_INLINE Data load1(int iy, int i) const { return load(y[iy] + k_step*i); } + IQK_ALWAYS_INLINE Data load_tail(int iy, int i) const { return load4Floats(y[iy] + 4*i); } + IQK_ALWAYS_INLINE void load_r4(int ix, int i, Data * xv) const { + xv[0] = load1(ix+0, i); + xv[1] = load1(ix+1, i); + xv[2] = load1(ix+2, i); + xv[3] = load1(ix+3, i); +#ifdef __AVX512F__ + auto t0 = _mm512_unpacklo_ps(xv[0], xv[1]); + auto t1 = _mm512_unpacklo_ps(xv[2], xv[3]); + auto t2 = _mm512_unpackhi_ps(xv[0], xv[1]); + auto t3 = _mm512_unpackhi_ps(xv[2], xv[3]); + xv[0] = _mm512_castpd_ps(_mm512_unpacklo_pd(_mm512_castps_pd(t0), _mm512_castps_pd(t1))); + xv[1] = _mm512_castpd_ps(_mm512_unpackhi_pd(_mm512_castps_pd(t0), _mm512_castps_pd(t1))); + xv[2] = _mm512_castpd_ps(_mm512_unpacklo_pd(_mm512_castps_pd(t2), _mm512_castps_pd(t3))); + xv[3] = _mm512_castpd_ps(_mm512_unpackhi_pd(_mm512_castps_pd(t2), _mm512_castps_pd(t3))); +#else + auto t0 = _mm256_unpacklo_ps(xv[0], xv[1]); + auto t1 = _mm256_unpacklo_ps(xv[2], xv[3]); + auto t2 = _mm256_unpackhi_ps(xv[0], xv[1]); + auto t3 = _mm256_unpackhi_ps(xv[2], xv[3]); + xv[0] = _mm256_castpd_ps(_mm256_unpacklo_pd(_mm256_castps_pd(t0), _mm256_castps_pd(t1))); + xv[1] = _mm256_castpd_ps(_mm256_unpackhi_pd(_mm256_castps_pd(t0), _mm256_castps_pd(t1))); + xv[2] = _mm256_castpd_ps(_mm256_unpacklo_pd(_mm256_castps_pd(t2), _mm256_castps_pd(t3))); + xv[3] = _mm256_castpd_ps(_mm256_unpackhi_pd(_mm256_castps_pd(t2), _mm256_castps_pd(t3))); +#endif + } + const Float * y[nrc]; +}; + +// TBD if we want this +//template <typename Qy, typename Qx> +//IQK_NOINLINE void mul_mat_Qx_Qy_Mx1(int n, const char * cx, size_t bx, int ix0, const DataInfo& info) { +// static_assert(Qy::nrc == 1); +// int nb = n/QFBase::k_step; +// int nb4 = n/4; +// Qy y(info); +// Qx x(cx + ix0*bx, bx); +// QFBase::Data xv[2*Qx::nrc]; +// QFBase::Acc acc[2*Qx::nrc]; +// auto yv1 = y.load1(0, 0); +// auto yv2 = y.load1(0, 1); +// for (int ix = 0; ix < Qx::nrc; ++ix) { +// xv[2*ix+0] = x.load1(ix, 0); +// xv[2*ix+1] = x.load1(ix, 1); +// acc[2*ix+0] = QFBase::acc_first(yv1, xv[2*ix+0]); +// acc[2*ix+1] = QFBase::acc_first(yv2, xv[2*ix+1]); +// } +// for (int i = 1; i < nb/2; ++i) { +// yv1 = y.load1(0, 2*i+0); +// yv2 = y.load1(0, 2*i+1); +// for (int ix = 0; ix < Qx::nrc; ++ix) { +// xv[2*ix+0] = x.load1(ix, 2*i+0); +// xv[2*ix+1] = x.load1(ix, 2*i+1); +// acc[2*ix+0] = QFBase::acc(acc[2*ix+0], yv1, xv[2*ix+0]); +// acc[2*ix+1] = QFBase::acc(acc[2*ix+1], yv2, xv[2*ix+1]); +// } +// } +// for (int i = (QFBase::k_step/4)*nb; i < nb4; ++i) { +// yv1 = y.load_tail(0, i); +// for (int ix = 0; ix < Qx::nrc; ++ix) { +// xv[ix] = x.load_tail(ix, i); +// acc[2*ix+0] = QFBase::acc(acc[2*ix+0], yv1, xv[ix]); +// } +// } +// for (int ix = 0; ix < Qx::nrc; ++ix) info.store(ix0+ix, 0, QFBase::hsum(QFBase::add(acc[2*ix+0], acc[2*ix+1]))); +//} + +template <typename Qy, typename Qx> +IQK_NOINLINE void mul_mat_Qx_Qy_MxN(int n, const char * cx, size_t bx, int ix0, const DataInfo& info) { + int nb = n/QFBase::k_step; + int nb4 = n/4; + Qy y(info); + Qx x(cx + ix0*bx, bx); + QFBase::Data xv[Qx::nrc]; + QFBase::Acc acc[Qx::nrc*Qy::nrc]; + auto yv = y.load1(0, 0); + for (int ix = 0; ix < Qx::nrc; ++ix) { + xv[ix] = x.load1(ix, 0); + acc[ix] = QFBase::acc_first(yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc; ++iy) { + yv = y.load1(iy, 0); + for (int ix = 0; ix < Qx::nrc; ++ix) acc[Qx::nrc*iy + ix] = QFBase::acc_first(yv, xv[ix]); + } + for (int i = 1; i < nb; ++i) { + yv = y.load1(0, i); + for (int ix = 0; ix < Qx::nrc; ++ix) { + xv[ix] = x.load1(ix, i); + acc[ix] = QFBase::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc; ++iy) { + yv = y.load1(iy, i); + for (int ix = 0; ix < Qx::nrc; ++ix) acc[Qx::nrc*iy + ix] = QFBase::acc(acc[Qx::nrc*iy + ix], yv, xv[ix]); + } + } + for (int i = (QFBase::k_step/4)*nb; i < nb4; ++i) { + yv = y.load_tail(0, i); + for (int ix = 0; ix < Qx::nrc; ++ix) { + xv[ix] = x.load_tail(ix, i); + acc[ix] = QFBase::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc; ++iy) { + yv = y.load_tail(iy, i); + for (int ix = 0; ix < Qx::nrc; ++ix) acc[Qx::nrc*iy + ix] = QFBase::acc(acc[Qx::nrc*iy + ix], yv, xv[ix]); + } + } + for (int iy = 0; iy < Qy::nrc; ++iy) for (int ix = 0; ix < Qx::nrc; ++ix) info.store(ix0+ix, iy, QFBase::hsum(acc[Qx::nrc*iy+ix])); +} + +template <typename Qy, typename Qx> +inline void mul_mat_Qx_Qy_MxN_fa(int n, const char * cx, size_t bx, int ix0, const DataInfo& info) { + int nb = n/QFBase::k_step; + Qy y(info); + Qx x(cx + ix0*bx, bx); + QFBase::Data xv[Qx::nrc]; + QFBase::Acc acc[Qx::nrc*Qy::nrc]; + auto yv = y.load1(0, 0); + for (int ix = 0; ix < Qx::nrc; ++ix) { + xv[ix] = x.load1(ix, 0); + acc[ix] = QFBase::acc_first(yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc; ++iy) { + yv = y.load1(iy, 0); + for (int ix = 0; ix < Qx::nrc; ++ix) acc[Qx::nrc*iy + ix] = QFBase::acc_first(yv, xv[ix]); + } + for (int i = 1; i < nb; ++i) { + yv = y.load1(0, i); + for (int ix = 0; ix < Qx::nrc; ++ix) { + xv[ix] = x.load1(ix, i); + acc[ix] = QFBase::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc; ++iy) { + yv = y.load1(iy, i); + for (int ix = 0; ix < Qx::nrc; ++ix) acc[Qx::nrc*iy + ix] = QFBase::acc(acc[Qx::nrc*iy + ix], yv, xv[ix]); + } + } + for (int iy = 0; iy < Qy::nrc; ++iy) for (int ix = 0; ix < Qx::nrc; ++ix) info.store(ix0+ix, iy, QFBase::hsum(acc[Qx::nrc*iy+ix])); +} + +template <typename Qy, typename Qx> +inline void mul_mat_Qx_Qy_MxN_fa4(int D, const char * cx, size_t bx, int ix0, const DataInfo& info) { + static_assert(Qx::nrc%4 == 0); + int nb = D/QFBase::k_step; + Qy y(info); + Qx x(cx + ix0*bx, bx); + QFBase::Data xv[Qx::nrc]; + QFBase::Acc acc[Qx::nrc*Qy::nrc/4] = {}; + for (int i = 0; i < nb; ++i) { + for (int ix = 0; ix < Qx::nrc/4; ++ix) x.load_r4(4*ix, i, xv + 4*ix); + for (int iy = 0; iy < Qy::nrc; ++iy) { + auto yv = y.load1(iy, i); + for (int ix = 0; ix < Qx::nrc/4; ++ix) acc[ix*Qy::nrc + iy] = QFBase::acc_r4(acc[ix*Qy::nrc + iy], xv + 4*ix, yv); + } + } + for (int iy = 0; iy < Qy::nrc; ++iy) { + for (int ix = 0; ix < Qx::nrc/4; ++ix) info.store(ix0+4*ix, iy, QFBase::hsum_r4(acc[ix*Qy::nrc + iy])); + } +} + +// This will handle any of f16 x f32, f32 x f16, f16 x f16, f32 x f32, with computations done +// in f32 (i.e., f16 is first converted to f32). It is easy to extend to computations done in +// f16, but I don't have a CPU capable of f16 vector arithmetic, so not doing it for now. +template <int nrc_y, typename FloatX, typename FloatY> +void mul_mat_fX_fY_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + const char * cx = (const char *)vx; + // TBD if we want this + //if constexpr (nrc_y == 1) { + // constexpr int k_nx = 2; + // for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + // mul_mat_Qx_Qy_Mx1<QFT<FloatY, nrc_y>, QFT<FloatX, k_nx>>(n, cx, bx, ix*k_nx, info); + // } + // if (int lastx = k_nx*(nrc_x/k_nx); lastx < nrc_x) { + // int nx = nrc_x - lastx; + // switch (nx) { + // case 1: mul_mat_Qx_Qy_Mx1<QFT<FloatY, nrc_y>, QFT<FloatX, 1>>(n, cx, bx, lastx, info); break; + // case 2: mul_mat_Qx_Qy_Mx1<QFT<FloatY, nrc_y>, QFT<FloatX, 2>>(n, cx, bx, lastx, info); break; + // case 3: mul_mat_Qx_Qy_Mx1<QFT<FloatY, nrc_y>, QFT<FloatX, 3>>(n, cx, bx, lastx, info); break; + // } + // //mul_mat_Qx_Qy_Mx1<QFT<FloatY, nrc_y>, QFT<FloatX, 1>>(n, cx, bx, lastx, info); + // } + // return; + //} +#ifdef __AVX512F__ + constexpr int k_nx = 5; +#else + constexpr int k_nx = nrc_y == 1 ? 4 : 2; +#endif + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + mul_mat_Qx_Qy_MxN<QFT<FloatY, nrc_y>, QFT<FloatX, k_nx>>(n, cx, bx, ix*k_nx, info); + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + int nx = nrc_x - last_x; +#ifdef __AVX512F__ + switch (nx) { + case 1: mul_mat_Qx_Qy_MxN<QFT<FloatY, nrc_y>, QFT<FloatX, 1>>(n, cx, bx, last_x, info); break; + case 2: mul_mat_Qx_Qy_MxN<QFT<FloatY, nrc_y>, QFT<FloatX, 2>>(n, cx, bx, last_x, info); break; + case 3: mul_mat_Qx_Qy_MxN<QFT<FloatY, nrc_y>, QFT<FloatX, 3>>(n, cx, bx, last_x, info); break; + case 4: mul_mat_Qx_Qy_MxN<QFT<FloatY, nrc_y>, QFT<FloatX, 4>>(n, cx, bx, last_x, info); break; + } +#else + if constexpr (nrc_y == 1) { + switch (nx) { + case 1: mul_mat_Qx_Qy_MxN<QFT<FloatY, nrc_y>, QFT<FloatX, 1>>(n, cx, bx, last_x, info); break; + case 2: mul_mat_Qx_Qy_MxN<QFT<FloatY, nrc_y>, QFT<FloatX, 2>>(n, cx, bx, last_x, info); break; + case 3: mul_mat_Qx_Qy_MxN<QFT<FloatY, nrc_y>, QFT<FloatX, 3>>(n, cx, bx, last_x, info); break; + } + } else { + switch (nx) { + case 1: mul_mat_Qx_Qy_MxN<QFT<FloatY, nrc_y>, QFT<FloatX, 1>>(n, cx, bx, last_x, info); break; + } + } +#endif +} + +#ifdef __AVX512BF16__ +template <int nrc_y> +static void mul_mat_bf16_r16_bf16(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + GGML_ASSERT(nrc_x%16 == 0); + const ggml_bf16_t * y[nrc_y]; + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const ggml_bf16_t *)info.src1_row(iy); + for (int ix = 0; ix < nrc_x/32; ++ix) { + __m512 acc[2*nrc_y] = {}; + __m512bh qx[8]; + const ggml_bf16_t * b8_1 = (const ggml_bf16_t *)((const char *)vx + (32*ix+ 0)*bx); + const ggml_bf16_t * b8_2 = (const ggml_bf16_t *)((const char *)vx + (32*ix+16)*bx); + for (int ib = 0; ib < n/8; ++ib) { + qx[0] = (__m512bh)_mm512_loadu_si512((const __m512i *)b8_1+4*ib+0); + qx[1] = (__m512bh)_mm512_loadu_si512((const __m512i *)b8_1+4*ib+1); + qx[2] = (__m512bh)_mm512_loadu_si512((const __m512i *)b8_1+4*ib+2); + qx[3] = (__m512bh)_mm512_loadu_si512((const __m512i *)b8_1+4*ib+3); + qx[4] = (__m512bh)_mm512_loadu_si512((const __m512i *)b8_2+4*ib+0); + qx[5] = (__m512bh)_mm512_loadu_si512((const __m512i *)b8_2+4*ib+1); + qx[6] = (__m512bh)_mm512_loadu_si512((const __m512i *)b8_2+4*ib+2); + qx[7] = (__m512bh)_mm512_loadu_si512((const __m512i *)b8_2+4*ib+3); + for (int iy = 0; iy < nrc_y; ++iy) { + auto y128 = _mm_loadu_si128((const __m128i*)y[iy]+ib); + //auto y = _mm512_broadcast_i32x4(y128); + auto y256 = MM256_SET_M128I(y128, y128); + auto y = _mm512_inserti32x8(_mm512_castsi256_si512(y256), y256, 1); + acc[2*iy+0] = _mm512_dpbf16_ps(acc[2*iy+0], qx[0], (__m512bh)_mm512_shuffle_epi32(y, _MM_PERM_ENUM(0x00))); + acc[2*iy+0] = _mm512_dpbf16_ps(acc[2*iy+0], qx[1], (__m512bh)_mm512_shuffle_epi32(y, _MM_PERM_ENUM(0x55))); + acc[2*iy+0] = _mm512_dpbf16_ps(acc[2*iy+0], qx[2], (__m512bh)_mm512_shuffle_epi32(y, _MM_PERM_ENUM(0xaa))); + acc[2*iy+0] = _mm512_dpbf16_ps(acc[2*iy+0], qx[3], (__m512bh)_mm512_shuffle_epi32(y, _MM_PERM_ENUM(0xff))); + acc[2*iy+1] = _mm512_dpbf16_ps(acc[2*iy+1], qx[4], (__m512bh)_mm512_shuffle_epi32(y, _MM_PERM_ENUM(0x00))); + acc[2*iy+1] = _mm512_dpbf16_ps(acc[2*iy+1], qx[5], (__m512bh)_mm512_shuffle_epi32(y, _MM_PERM_ENUM(0x55))); + acc[2*iy+1] = _mm512_dpbf16_ps(acc[2*iy+1], qx[6], (__m512bh)_mm512_shuffle_epi32(y, _MM_PERM_ENUM(0xaa))); + acc[2*iy+1] = _mm512_dpbf16_ps(acc[2*iy+1], qx[7], (__m512bh)_mm512_shuffle_epi32(y, _MM_PERM_ENUM(0xff))); + } + } + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(32*ix+ 0, iy, acc[2*iy+0]); + info.store(32*ix+16, iy, acc[2*iy+1]); + } + } + for (int ix = 32*(nrc_x/32); ix < nrc_x; ix += 16) { + __m512 acc[nrc_y] = {}; + __m512bh qx[4]; + const ggml_bf16_t * b8 = (const ggml_bf16_t *)((const char *)vx + (ix+0)*bx); + for (int ib = 0; ib < n/8; ++ib) { + qx[0] = (__m512bh)_mm512_loadu_si512((const __m512i *)b8+4*ib+0); + qx[1] = (__m512bh)_mm512_loadu_si512((const __m512i *)b8+4*ib+1); + qx[2] = (__m512bh)_mm512_loadu_si512((const __m512i *)b8+4*ib+2); + qx[3] = (__m512bh)_mm512_loadu_si512((const __m512i *)b8+4*ib+3); + for (int iy = 0; iy < nrc_y; ++iy) { + auto y128 = _mm_loadu_si128((const __m128i*)y[iy]+ib); + auto y256 = MM256_SET_M128I(y128, y128); + auto y = _mm512_inserti32x8(_mm512_castsi256_si512(y256), y256, 1); + acc[iy] = _mm512_dpbf16_ps(acc[iy], qx[0], (__m512bh)_mm512_shuffle_epi32(y, _MM_PERM_ENUM(0x00))); + acc[iy] = _mm512_dpbf16_ps(acc[iy], qx[1], (__m512bh)_mm512_shuffle_epi32(y, _MM_PERM_ENUM(0x55))); + acc[iy] = _mm512_dpbf16_ps(acc[iy], qx[2], (__m512bh)_mm512_shuffle_epi32(y, _MM_PERM_ENUM(0xaa))); + acc[iy] = _mm512_dpbf16_ps(acc[iy], qx[3], (__m512bh)_mm512_shuffle_epi32(y, _MM_PERM_ENUM(0xff))); + } + } + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(ix, iy, acc[iy]); + } + } +} + +struct QFBaseBF16 { + constexpr static int k_step = 32; + using Data = __m512bh; + using Acc = __m512; + static inline Data load(const ggml_bf16_t * x) { return __m512bh(_mm512_loadu_si512((const __m512i *)x)); } + static inline Acc acc(Acc prev, Data y, Data x) { + return _mm512_dpbf16_ps(prev, y, x); + } + static inline Acc acc_first(const Data& y, const Data& x) { + return _mm512_dpbf16_ps(_mm512_setzero_ps(), y, x); + } + static inline float hsum(Acc acc) { + return _mm512_reduce_add_ps(acc); + } +}; +template <int nrc_in> struct QFTBF16 final : public QFBaseBF16 { + constexpr static int nrc = nrc_in; + QFTBF16(const DataInfo& info) { + for (int iy = 0; iy < nrc; ++iy) y[iy] = (const ggml_bf16_t *)info.src1_row(iy); + } + QFTBF16(const char * cx, size_t bx) { + for (int iy = 0; iy < nrc; ++iy) y[iy] = (const ggml_bf16_t *)(cx + iy*bx); + } + IQK_ALWAYS_INLINE Data load1(int iy, int i) const { return load(y[iy] + k_step*i); } + const ggml_bf16_t * y[nrc]; +}; + +template <int nrc_y, int nrc_x> +IQK_NOINLINE void mul_mat_Qx_Qy_MxN(int n, const char * cx, size_t bx, int ix0, const DataInfo& info) { + int nb = n/QFBaseBF16::k_step; + QFTBF16<nrc_y> y(info); + QFTBF16<nrc_x> x(cx + ix0*bx, bx); + QFBaseBF16::Data xv[nrc_x]; + QFBaseBF16::Acc acc[nrc_x*nrc_y]; + auto yv = y.load1(0, 0); + for (int ix = 0; ix < nrc_x; ++ix) { + xv[ix] = x.load1(ix, 0); + acc[ix] = QFBaseBF16::acc_first(yv, xv[ix]); + } + for (int iy = 1; iy < nrc_y; ++iy) { + yv = y.load1(iy, 0); + for (int ix = 0; ix < nrc_x; ++ix) acc[nrc_x*iy + ix] = QFBaseBF16::acc_first(yv, xv[ix]); + } + for (int i = 1; i < nb; ++i) { + yv = y.load1(0, i); + for (int ix = 0; ix < nrc_x; ++ix) { + xv[ix] = x.load1(ix, i); + acc[ix] = QFBaseBF16::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < nrc_y; ++iy) { + yv = y.load1(iy, i); + for (int ix = 0; ix < nrc_x; ++ix) acc[nrc_x*iy + ix] = QFBaseBF16::acc(acc[nrc_x*iy + ix], yv, xv[ix]); + } + } + for (int iy = 0; iy < nrc_y; ++iy) for (int ix = 0; ix < nrc_x; ++ix) info.store(ix0+ix, iy, QFBaseBF16::hsum(acc[nrc_x*iy+ix])); +} + +template <int nrc_y> +void mul_mat_fX_fY_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + constexpr int k_nx = nrc_y <= 2 ? 8 : 5; + const char * cx = (const char *)vx; + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + mul_mat_Qx_Qy_MxN<nrc_y, k_nx>(n, cx, bx, ix*k_nx, info); + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + int nx = nrc_x - last_x; + if constexpr (nrc_y <= 2) { + if (nx >= 4) { + mul_mat_Qx_Qy_MxN<nrc_y, 4>(n, cx, bx, last_x, info); + last_x += 4; + if (last_x == nrc_x) return; + nx = nrc_x - last_x; + } + } + switch (nx) { + case 1: mul_mat_Qx_Qy_MxN<nrc_y, 1>(n, cx, bx, last_x, info); break; + case 2: mul_mat_Qx_Qy_MxN<nrc_y, 2>(n, cx, bx, last_x, info); break; + case 3: mul_mat_Qx_Qy_MxN<nrc_y, 3>(n, cx, bx, last_x, info); break; + case 4: mul_mat_Qx_Qy_MxN<nrc_y, 4>(n, cx, bx, last_x, info); break; + } +} +#endif + + +template <typename FloatX, typename FloatY> +void set_mul_mat_f(std::array<mul_mat_t, IQK_MAX_NY>& funcs) { + for (auto& f : funcs) f = nullptr; + funcs[0] = mul_mat_fX_fY_T<1, FloatX, FloatY>; + funcs[1] = mul_mat_fX_fY_T<2, FloatX, FloatY>; + funcs[2] = mul_mat_fX_fY_T<3, FloatX, FloatY>; + funcs[3] = mul_mat_fX_fY_T<4, FloatX, FloatY>; + funcs[4] = mul_mat_fX_fY_T<5, FloatX, FloatY>; +#ifndef __AVX512F__ + funcs[5] = mul_mat_fX_fY_T<6, FloatX, FloatY>; +#endif +} + +#ifdef __AVX512BF16__ +void set_mul_mat_bf16(std::array<mul_mat_t, IQK_MAX_NY>& funcs) { + for (auto& f : funcs) f = nullptr; + funcs[0] = mul_mat_fX_fY_T<1>; + funcs[1] = mul_mat_fX_fY_T<2>; + funcs[2] = mul_mat_fX_fY_T<3>; + funcs[3] = mul_mat_fX_fY_T<4>; + funcs[4] = mul_mat_fX_fY_T<5>; +} +void set_mul_mat_bf16_r16(std::array<mul_mat_t, IQK_MAX_NY>& funcs) { + for (auto& f : funcs) f = nullptr; + funcs[0] = mul_mat_bf16_r16_bf16<1>; + funcs[1] = mul_mat_bf16_r16_bf16<2>; + funcs[2] = mul_mat_bf16_r16_bf16<3>; + funcs[3] = mul_mat_bf16_r16_bf16<4>; + funcs[4] = mul_mat_bf16_r16_bf16<5>; + funcs[5] = mul_mat_bf16_r16_bf16<6>; + funcs[6] = mul_mat_bf16_r16_bf16<7>; + funcs[7] = mul_mat_bf16_r16_bf16<8>; +} +#endif + +} // namespace + +bool iqk_set_kernels_float(int ne00, int typeA, int typeB, std::array<mul_mat_t, IQK_MAX_NY>& kernels) { + + if (typeA == GGML_TYPE_BF16) { + if (ne00 % 32) return false; + switch (typeB) { +#ifdef __AVX512BF16__ + case GGML_TYPE_BF16: set_mul_mat_bf16(kernels); break; +#else + case GGML_TYPE_BF16: set_mul_mat_f<ggml_bf16_t, ggml_bf16_t>(kernels); break; + case GGML_TYPE_F32: set_mul_mat_f<ggml_bf16_t, float>(kernels); break; +#endif + default: return false; + } + return true; + } + + if (typeA == GGML_TYPE_BF16_R16) { + if (ne00 % 16) return false; + switch (typeB) { +#ifdef __AVX512BF16__ + case GGML_TYPE_BF16: set_mul_mat_bf16_r16(kernels); break; +#endif + default: return false; + } + return true; + } + + if (typeA == GGML_TYPE_F16 || typeA == GGML_TYPE_F32) { + if (ne00 % 4) return false; + } + if (typeA == GGML_TYPE_F16) { + switch (typeB) { + case GGML_TYPE_F16: set_mul_mat_f<ggml_half, ggml_half>(kernels); break; + case GGML_TYPE_F32: set_mul_mat_f<ggml_half, float>(kernels); break; + default: return false; + } + return true; + } + if (typeA == GGML_TYPE_F32) { + switch (typeB) { + case GGML_TYPE_F16: set_mul_mat_f<float, ggml_half>(kernels); break; + case GGML_TYPE_F32: set_mul_mat_f<float, float>(kernels); break; + default: return false; + } + return true; + } + + return false; + +} + +void iqk_gemm_default_floats(int D, int nq, const char * cx, size_t bx, DataInfo& info, int k_step) { + using q_float = float; +#ifdef HAVE_FANCY_SIMD + constexpr int nrc_q = 8; + constexpr int nrc_k = 8; +#else + // somewhat surprisingly, nrc_q = 4, nrc_k = 8 is better than nrc_q = 8, nrc_k = 4 + constexpr int nrc_q = 4; + constexpr int nrc_k = 8; +#endif + GGML_ASSERT(k_step%nrc_k == 0); + int qrem = nq - nrc_q*(nq/nrc_q); + for (int iq = 0; iq < nq/nrc_q; ++iq) { + for (int ik = 0; ik < k_step/nrc_k; ++ik) { + mul_mat_Qx_Qy_MxN_fa4<QFT<float, nrc_q>, QFT<ggml_half, nrc_k>>(D, cx, bx, ik*nrc_k, info); + } + info.cur_y += nrc_q; + } + if (qrem > 0) { + switch (qrem) { + case 1: { + for (int ik = 0; ik < k_step/nrc_k; ++ik) { + mul_mat_Qx_Qy_MxN_fa4<QFT<q_float, 1>, QFT<ggml_half, nrc_k>>(D, cx, bx, ik*nrc_k, info); + } + } break; + case 2: { + for (int ik = 0; ik < k_step/nrc_k; ++ik) { + mul_mat_Qx_Qy_MxN_fa4<QFT<q_float, 2>, QFT<ggml_half, nrc_k>>(D, cx, bx, ik*nrc_k, info); + } + } break; + case 3: { + for (int ik = 0; ik < k_step/nrc_k; ++ik) { + mul_mat_Qx_Qy_MxN_fa4<QFT<q_float, 3>, QFT<ggml_half, nrc_k>>(D, cx, bx, ik*nrc_k, info); + } + } break; +#ifdef HAVE_FANCY_SIMD + case 4: { + for (int ik = 0; ik < k_step/nrc_k; ++ik) { + mul_mat_Qx_Qy_MxN_fa4<QFT<q_float, 4>, QFT<ggml_half, nrc_k>>(D, cx, bx, ik*nrc_k, info); + } + } break; + case 5: { + for (int ik = 0; ik < k_step/nrc_k; ++ik) { + mul_mat_Qx_Qy_MxN_fa4<QFT<q_float, 5>, QFT<ggml_half, nrc_k>>(D, cx, bx, ik*nrc_k, info); + } + } break; + case 6: { + for (int ik = 0; ik < k_step/nrc_k; ++ik) { + mul_mat_Qx_Qy_MxN_fa4<QFT<q_float, 6>, QFT<ggml_half, nrc_k>>(D, cx, bx, ik*nrc_k, info); + } + } break; + case 7: { + for (int ik = 0; ik < k_step/nrc_k; ++ik) { + mul_mat_Qx_Qy_MxN_fa4<QFT<q_float, 7>, QFT<ggml_half, nrc_k>>(D, cx, bx, ik*nrc_k, info); + } + } break; +#endif + } + } +} + +#else +// ----------------------------------- __aarch64__ ----------------------------------------------- + +namespace { + +struct QF16Base { + constexpr static int k_step = 8; + using Data = float16x8_t; + using Acc = float16x8_t; + static inline Data load(const __fp16 * x) { return vld1q_f16(x); } + static inline Data load4(const __fp16 * x) { return vcombine_f16(vld1_f16(x), vdup_n_f16(0)); } + static inline Acc acc(Acc prev, const Data& y, const Data& x) { + return vfmaq_f16(prev, y, x); + } + static inline Acc acc_first(const Data& y, const Data& x) { + return vmulq_f16(y, x); + } + //constexpr static int k_step = 16; + //using Data = float16x8x2_t; + //static inline Data load(const __fp16 * x) { return vld1q_f16_x2(x); } + //static inline Acc acc(Acc prev, const Data& y, const Data& x) { + // return vfmaq_f16(vfmaq_f16(prev, y.val[0], x.val[0]), y.val[1], x.val[1]); + //} + //static inline Acc acc_first(const Data& y, const Data& x) { + // return vfmaq_f16(vmulq_f16(y.val[0], x.val[0]), y.val[1], x.val[1]); + //} + static inline float hsum(Acc acc) { + float32x4_t sum = vcvt_f32_f16(vadd_f16(vget_low_f16(acc), vget_high_f16(acc))); + return vaddvq_f32(sum); + } +}; +template <int nrc> struct QF16 final : public QF16Base { + using Base = QF16Base; + constexpr static int nrc_y = nrc; + QF16(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const __fp16 *)info.src1_row(iy); + } + QF16(const char * cx, size_t bx) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const __fp16 *)(cx + iy*bx); + } + IQK_ALWAYS_INLINE Data load1(int iy, int i) const { return load(y[iy] + k_step*i); } + IQK_ALWAYS_INLINE Data load_tail(int iy, int i) const { return load4(y[iy] + 4*i); } + IQK_ALWAYS_INLINE float16x8x4_t loadx(int iy, int i) const { return vld1q_f16_x4(y[iy] + 4*k_step*i); } + const __fp16 * y[nrc_y]; +}; + +struct QBF16Base { + constexpr static int k_step = 4; + using Data = float32x4_t; + using Acc = float32x4_t; + static inline Data load(const uint16_t * x) { return vreinterpretq_f32_u32(vshlq_n_u32(vmovl_u16(vld1_u16(x)), 16)); } + static inline Data load4(const uint16_t * x) { return load(x); } + static inline Acc acc(Acc prev, const Data& y, const Data& x) { + return vfmaq_f32(prev, y, x); + } + static inline Acc acc_first(const Data& y, const Data& x) { + return vmulq_f32(y, x); + } + static inline float hsum(Acc acc) { return vaddvq_f32(acc); } +}; +template <int nrc> struct QBF16 final : public QBF16Base { + using Base = QBF16Base; + constexpr static int nrc_y = nrc; + QBF16(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const uint16_t *)info.src1_row(iy); + } + QBF16(const char * cx, size_t bx) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const uint16_t *)(cx + iy*bx); + } + IQK_ALWAYS_INLINE Data load1(int iy, int i) const { return load(y[iy] + k_step*i); } + IQK_ALWAYS_INLINE Data load_tail(int iy, int i) const { return load(y[iy] + 4*i); } + const uint16_t * y[nrc_y]; +}; + +struct QF32Base { + constexpr static int k_step = 4; + using Data = float32x4_t; + using Acc = float32x4_t; + static inline Data load(const float * x) { return vld1q_f32(x); } + static inline Data load4(const float * x) { return load(x); } + static inline Acc acc(Acc prev, const Data& y, const Data& x) { return vfmaq_f32(prev, y, x); } + static inline Acc acc_first(const Data& y, const Data& x) { return vmulq_f32(y, x); } + static inline float hsum(Acc acc) { return vaddvq_f32(acc); } +}; +template <int nrc> struct QF32 final : public QF32Base { + using Base = QF32Base; + constexpr static int nrc_y = nrc; + QF32(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const float *)info.src1_row(iy); + } + QF32(const char * cx, size_t bx) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const float *)(cx + iy*bx); + } + IQK_ALWAYS_INLINE Data load1(int iy, int i) const { return load(y[iy] + k_step*i); } + IQK_ALWAYS_INLINE Data load_tail(int iy, int i) const { return load(y[iy] + 4*i); } + const float * y[nrc_y]; +}; + +template <typename Qy, typename Qx, bool is_multiple_of_k_step> +IQK_NOINLINE void mul_mat_Qx_Qy_NxN(int n, const char * cx, size_t bx, int ix0, const DataInfo& info) { + GGML_ASSERT(Qx::Base::k_step == Qy::Base::k_step); + int nb = n/Qx::Base::k_step; + Qy y(info); + Qx x(cx + ix0*bx, bx); + typename Qx::Base::Data xv[Qx::nrc_y]; + typename Qx::Base::Acc acc[Qx::nrc_y*Qy::nrc_y]; + auto yv = y.load1(0, 0); + for (int ix = 0; ix < Qx::nrc_y; ++ix) { + xv[ix] = x.load1(ix, 0); + acc[ix] = Qx::Base::acc_first(yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc_y; ++iy) { + yv = y.load1(iy, 0); + for (int ix = 0; ix < Qx::nrc_y; ++ix) acc[Qx::nrc_y*iy + ix] = Qx::Base::acc_first(yv, xv[ix]); + } + for (int i = 1; i < nb; ++i) { + yv = y.load1(0, i); + for (int ix = 0; ix < Qx::nrc_y; ++ix) { + xv[ix] = x.load1(ix, i); + acc[ix] = Qx::Base::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc_y; ++iy) { + yv = y.load1(iy, i); + for (int ix = 0; ix < Qx::nrc_y; ++ix) acc[Qx::nrc_y*iy + ix] = Qx::Base::acc(acc[Qx::nrc_y*iy + ix], yv, xv[ix]); + } + } + if constexpr (Qx::Base::k_step > 4 && !is_multiple_of_k_step) { + int nb4 = n/4; + for (int i = (Qx::Base::k_step/4)*nb; i < nb4; ++i) { + yv = y.load_tail(0, i); + for (int ix = 0; ix < Qx::nrc_y; ++ix) { + xv[ix] = x.load_tail(ix, i); + acc[ix] = Qx::Base::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc_y; ++iy) { + yv = y.load_tail(iy, i); + for (int ix = 0; ix < Qx::nrc_y; ++ix) acc[Qx::nrc_y*iy + ix] = Qx::Base::acc(acc[Qx::nrc_y*iy + ix], yv, xv[ix]); + } + } + } + for (int iy = 0; iy < Qy::nrc_y; ++iy) for (int ix = 0; ix < Qx::nrc_y; ++ix) info.store(ix0+ix, iy, Qx::Base::hsum(acc[Qx::nrc_y*iy+ix])); +} + +template <int nrc_y, int nrc_x, bool is_multiple_of_k_step> +IQK_NOINLINE void mul_mat_f16_f16_NxN(int n, const char * cx, size_t bx, int ix0, const DataInfo& info) { + assert(n%QF16Base::k_step == 0); + int nb = n/QF16Base::k_step; + QF16<nrc_y> y(info); + QF16<nrc_x> x(cx + ix0*bx, bx); + QF16Base::Data xv[nrc_x]; + QF16Base::Acc acc[nrc_x*nrc_y]; + auto yv = y.load1(0, 0); + for (int ix = 0; ix < nrc_x; ++ix) { + xv[ix] = x.load1(ix, 0); + acc[ix] = QF16Base::acc_first(yv, xv[ix]); + } + for (int iy = 1; iy < nrc_y; ++iy) { + yv = y.load1(iy, 0); + for (int ix = 0; ix < nrc_x; ++ix) acc[nrc_x*iy + ix] = QF16Base::acc_first(yv, xv[ix]); + } + for (int i = 1; i < nb; ++i) { + yv = y.load1(0, i); + for (int ix = 0; ix < nrc_x; ++ix) { + xv[ix] = x.load1(ix, i); + acc[ix] = QF16Base::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < nrc_y; ++iy) { + yv = y.load1(iy, i); + for (int ix = 0; ix < nrc_x; ++ix) acc[nrc_x*iy + ix] = QF16Base::acc(acc[nrc_x*iy + ix], yv, xv[ix]); + } + } + if constexpr (!is_multiple_of_k_step) { + int nb4 = n/4; + for (int i = (QF16Base::k_step/4)*nb; i < nb4; ++i) { + yv = y.load_tail(0, i); + for (int ix = 0; ix < nrc_x; ++ix) { + xv[ix] = x.load_tail(ix, i); + acc[ix] = QF16Base::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < nrc_y; ++iy) { + yv = y.load_tail(iy, i); + for (int ix = 0; ix < nrc_x; ++ix) acc[nrc_x*iy + ix] = QF16Base::acc(acc[nrc_x*iy + ix], yv, xv[ix]); + } + } + } + for (int iy = 0; iy < nrc_y; ++iy) for (int ix = 0; ix < nrc_x; ++ix) info.store(ix0+ix, iy, QF16Base::hsum(acc[nrc_x*iy+ix])); +} + +template <typename Qy, template<int> typename Qx> +void mul_mat_Qx_Qy_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + GGML_ASSERT(n%4 == 0); + constexpr int k_nx = 5; + const char * cx = (const char *)vx; + if (n%Qx<k_nx>::Base::k_step == 0) { + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + mul_mat_Qx_Qy_NxN<Qy, Qx<k_nx>, true>(n, cx, bx, ix*k_nx, info); + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + int nx = nrc_x - last_x; + switch (nx) { + case 1: mul_mat_Qx_Qy_NxN<Qy, Qx<1>, true>(n, cx, bx, last_x, info); break; + case 2: mul_mat_Qx_Qy_NxN<Qy, Qx<2>, true>(n, cx, bx, last_x, info); break; + case 3: mul_mat_Qx_Qy_NxN<Qy, Qx<3>, true>(n, cx, bx, last_x, info); break; + case 4: mul_mat_Qx_Qy_NxN<Qy, Qx<4>, true>(n, cx, bx, last_x, info); break; + } + } else { + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + mul_mat_Qx_Qy_NxN<Qy, Qx<k_nx>, false>(n, cx, bx, ix*k_nx, info); + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + int nx = nrc_x - last_x; + switch (nx) { + case 1: mul_mat_Qx_Qy_NxN<Qy, Qx<1>, false>(n, cx, bx, last_x, info); break; + case 2: mul_mat_Qx_Qy_NxN<Qy, Qx<2>, false>(n, cx, bx, last_x, info); break; + case 3: mul_mat_Qx_Qy_NxN<Qy, Qx<3>, false>(n, cx, bx, last_x, info); break; + case 4: mul_mat_Qx_Qy_NxN<Qy, Qx<4>, false>(n, cx, bx, last_x, info); break; + } + } +} + +template <int nrc_y> +void mul_mat_f16_f16_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + GGML_ASSERT(n%4 == 0); + constexpr int k_nx = 5; + const char * cx = (const char *)vx; + if (n%QF16Base::k_step == 0) { + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + mul_mat_f16_f16_NxN<nrc_y, k_nx, true>(n, cx, bx, ix*k_nx, info); + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + int nx = nrc_x - last_x; + switch (nx) { + case 1: mul_mat_f16_f16_NxN<nrc_y, 1, true>(n, cx, bx, last_x, info); break; + case 2: mul_mat_f16_f16_NxN<nrc_y, 2, true>(n, cx, bx, last_x, info); break; + case 3: mul_mat_f16_f16_NxN<nrc_y, 3, true>(n, cx, bx, last_x, info); break; + case 4: mul_mat_f16_f16_NxN<nrc_y, 4, true>(n, cx, bx, last_x, info); break; + } + } else { + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + mul_mat_f16_f16_NxN<nrc_y, k_nx, false>(n, cx, bx, ix*k_nx, info); + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + int nx = nrc_x - last_x; + switch (nx) { + case 1: mul_mat_f16_f16_NxN<nrc_y, 1, false>(n, cx, bx, last_x, info); break; + case 2: mul_mat_f16_f16_NxN<nrc_y, 2, false>(n, cx, bx, last_x, info); break; + case 3: mul_mat_f16_f16_NxN<nrc_y, 3, false>(n, cx, bx, last_x, info); break; + case 4: mul_mat_f16_f16_NxN<nrc_y, 4, false>(n, cx, bx, last_x, info); break; + } + } +} + +template <int nrc_x, bool is_multiple_of_k_step> +IQK_NOINLINE void mul_mat_f16_f16_Nx1(int n, const char * cx, size_t bx, int ix0, const DataInfo& info) { + assert(n%QF16Base::k_step == 0); + int nb = n/QF16Base::k_step; + QF16<1> y(info); + QF16<nrc_x> x(cx + ix0*bx, bx); + QF16Base::Acc acc[4*nrc_x]; + auto yv = y.loadx(0, 0); + for (int ix = 0; ix < nrc_x; ++ix) { + for (int k = 0; k < 4; ++k) { + auto xv = x.load1(ix, k); + acc[4*ix+k] = QF16Base::acc_first(yv.val[k], xv); + } + } + for (int i = 1; i < nb/4; ++i) { + yv = y.loadx(0, i); + for (int ix = 0; ix < nrc_x; ++ix) { + for (int k = 0; k < 4; ++k) { + auto xv = x.load1(ix, 4*i+k); + acc[4*ix+k] = QF16Base::acc(acc[4*ix+k], yv.val[k], xv); + } + } + } + for (int i = 4*(nb/4); i < nb; ++i) { + auto yv1 = y.load1(0, i); + for (int ix = 0; ix < nrc_x; ++ix) { + auto xv1 = x.load1(ix, i); + acc[4*ix] = QF16Base::acc(acc[4*ix], yv1, xv1); + } + } + if constexpr (!is_multiple_of_k_step) { + int nb4 = n/4; + for (int i = (QF16Base::k_step/4)*nb; i < nb4; ++i) { + auto yv1 = y.load_tail(0, i); + for (int ix = 0; ix < nrc_x; ++ix) { + auto xv1 = x.load_tail(ix, i); + acc[4*ix] = QF16Base::acc(acc[4*ix], yv1, xv1); + } + } + } + for (int ix = 0; ix < nrc_x; ++ix) { + auto v1 = vaddq_f16(acc[4*ix+0], acc[4*ix+1]); + auto v2 = vaddq_f16(acc[4*ix+2], acc[4*ix+3]); + info.store(ix0+ix, 0, QF16Base::hsum(vaddq_f16(v1, v2))); + } +} + +// At least on my M2-Max the version below, which does the multiplication row-by-row, is faster. +// But let's keep this version commented out for now. +//void mul_mat_f16_f16_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { +// GGML_ASSERT(n%4 == 0); +// constexpr int k_nx = 2; +// const char * cx = (const char *)vx; +// if (n%QF16Base::k_step == 0) { +// for (int ix = 0; ix < nrc_x/k_nx; ++ix) { +// mul_mat_f16_f16_Nx1<k_nx, true>(n, cx, bx, ix*k_nx, info); +// } +// int last_x = k_nx*(nrc_x/k_nx); +// if (last_x == nrc_x) return; +// int nx = nrc_x - last_x; +// switch (nx) { +// case 1: mul_mat_f16_f16_Nx1<1, true>(n, cx, bx, last_x, info); break; +// //case 2: mul_mat_f16_f16_Nx1<2, true>(n, cx, bx, last_x, info); break; +// //case 3: mul_mat_f16_f16_Nx1<3, true>(n, cx, bx, last_x, info); break; +// } +// } else { +// for (int ix = 0; ix < nrc_x/k_nx; ++ix) { +// mul_mat_f16_f16_Nx1<k_nx, false>(n, cx, bx, ix*k_nx, info); +// } +// int last_x = k_nx*(nrc_x/k_nx); +// if (last_x == nrc_x) return; +// int nx = nrc_x - last_x; +// switch (nx) { +// case 1: mul_mat_f16_f16_Nx1<1, false>(n, cx, bx, last_x, info); break; +// //case 2: mul_mat_f16_f16_Nx1<2, false>(n, cx, bx, last_x, info); break; +// //case 3: mul_mat_f16_f16_Nx1<3, false>(n, cx, bx, last_x, info); break; +// } +// } +//} + +void mul_mat_f16_f16_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + GGML_ASSERT(n%4 == 0); + const char * cx = (const char *)vx; + if (n%QF16Base::k_step == 0) { + for (int ix = 0; ix < nrc_x; ++ix) { + mul_mat_f16_f16_Nx1<1, true>(n, cx, bx, ix, info); + } + } else { + for (int ix = 0; ix < nrc_x; ++ix) { + mul_mat_f16_f16_Nx1<1, false>(n, cx, bx, ix, info); + } + } +} + +} + +bool iqk_set_kernels_float(int ne00, int typeA, int typeB, std::array<mul_mat_t, IQK_MAX_NY>& kernels) { + + if (ne00%4 == 0) { + + if (typeA == GGML_TYPE_F16 && typeB == GGML_TYPE_F16) { + for (auto& f : kernels) f = nullptr; + kernels[0] = mul_mat_f16_f16_1; + kernels[1] = mul_mat_f16_f16_T<2>; + kernels[2] = mul_mat_f16_f16_T<3>; + kernels[3] = mul_mat_f16_f16_T<4>; + kernels[4] = mul_mat_f16_f16_T<5>; + return true; + } + else if (typeA == GGML_TYPE_BF16 && typeB == GGML_TYPE_F32) { + for (auto& f : kernels) f = nullptr; + kernels[0] = mul_mat_Qx_Qy_T<QF32<1>, QBF16>; + kernels[1] = mul_mat_Qx_Qy_T<QF32<2>, QBF16>; + kernels[2] = mul_mat_Qx_Qy_T<QF32<3>, QBF16>; + kernels[3] = mul_mat_Qx_Qy_T<QF32<4>, QBF16>; + kernels[4] = mul_mat_Qx_Qy_T<QF32<5>, QBF16>; + return true; + } + + } + + return false; + +} + +namespace { +template <int nrc_q> +inline void mm_helper(int D, int nq, const char * cx, size_t bx, DataInfo& info, int k_step) { + constexpr int nrc_k = 6; + int krem = k_step - nrc_k*(k_step/nrc_k); + for (int iq = 0; iq < nq/nrc_q; ++iq) { + for (int ik = 0; ik < k_step/nrc_k; ++ik) { + mul_mat_f16_f16_NxN<nrc_q, nrc_k, true>(D, cx, bx, ik*nrc_k, info); + } + if (krem > 0) { + switch (krem) { + case 1: mul_mat_f16_f16_NxN<nrc_q, 1, true>(D, cx, bx, k_step - krem, info); break; + case 2: mul_mat_f16_f16_NxN<nrc_q, 2, true>(D, cx, bx, k_step - krem, info); break; + case 3: mul_mat_f16_f16_NxN<nrc_q, 3, true>(D, cx, bx, k_step - krem, info); break; + case 4: mul_mat_f16_f16_NxN<nrc_q, 4, true>(D, cx, bx, k_step - krem, info); break; + default: mul_mat_f16_f16_NxN<nrc_q, 5, true>(D, cx, bx, k_step - krem, info); break; + } + } + info.cur_y += nrc_q; + } +} +} + +void iqk_gemm_default_floats(int D, int nq, const char * cx, size_t bx, DataInfo& info, int k_step) { + constexpr int nrc_q = 4; + mm_helper<nrc_q>(D, nq, cx, bx, info, k_step); + if (int qrem = nq - nrc_q*(nq/nrc_q); qrem > 0) { + switch (qrem) { + case 1: mm_helper<1>(D, nq, cx, bx, info, k_step); + case 2: mm_helper<2>(D, nq, cx, bx, info, k_step); + default: mm_helper<3>(D, nq, cx, bx, info, k_step); + } + } +} + +#endif + +#endif |