llama-cpp-sys-4 0.2.46

Low Level Bindings to llama.cpp
Documentation 
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#pragma once

// Computes C[M x N] += A[M x K] * B[K x N]

#include "simd-mappings.h"

// TODO: add support for sizeless vector types
#if defined(GGML_SIMD) && !defined(__ARM_FEATURE_SVE) && !defined(__riscv_v_intrinsic)

// TODO: untested on avx512
// These are in units of GGML_F32_EPR
#if defined(__AVX512F__) || defined (__ARM_NEON__)
    static constexpr int GEMM_RM = 4;
    static constexpr int GEMM_RN = 4; // 16+4+1 = 25/32
#elif defined(__AVX2__) || defined(__AVX__)
    static constexpr int GEMM_RM = 6;
    static constexpr int GEMM_RN = 2; // 12+2+1 = 15/16
#else
    static constexpr int GEMM_RM = 2;
    static constexpr int GEMM_RN = 2;
#endif

template <int RM, int RN>
static inline void simd_gemm_ukernel(
    float       * GGML_RESTRICT C,
    const float * GGML_RESTRICT A,
    const float * GGML_RESTRICT B,
    int K, int N)
{
    static constexpr int KN = GGML_F32_EPR;

    GGML_F32_VEC acc[RM][RN];
    for (int64_t i = 0; i < RM; i++) {
        for (int r = 0; r < RN; r++) {
            acc[i][r] = GGML_F32_VEC_LOAD(C + i * N + r * KN);
        }
    }

    for (int64_t kk = 0; kk < K; kk++) {
        GGML_F32_VEC Bv[RN];
        for (int r = 0; r < RN; r++) {
            Bv[r] = GGML_F32_VEC_LOAD(B + kk * N + r * KN);
        }
        for (int64_t i = 0; i < RM; i++) {
            GGML_F32_VEC p = GGML_F32_VEC_SET1(A[i * K + kk]);
            for (int r = 0; r < RN; r++) {
                acc[i][r] = GGML_F32_VEC_FMA(acc[i][r], Bv[r], p);
            }
        }
    }

    for (int64_t i = 0; i < RM; i++) {
        for (int r = 0; r < RN; r++) {
            GGML_F32_VEC_STORE(C + i * N + r * KN, acc[i][r]);
        }
    }
}

// C[M x N] += A[M x K] * B[K x N]
static void simd_gemm(
    float       * GGML_RESTRICT C,
    const float * GGML_RESTRICT A,
    const float * GGML_RESTRICT B,
    int M, int K, int N)
{
    static constexpr int KN = GGML_F32_EPR;

    int64_t ii = 0;
    for (; ii + GEMM_RM <= M; ii += GEMM_RM) {
        int64_t jj = 0;
        for (; jj + GEMM_RN * KN <= N; jj += GEMM_RN * KN) {
            simd_gemm_ukernel<GEMM_RM, GEMM_RN>(C + jj, A, B + jj, K, N);
        }
        for (; jj + KN <= N; jj += KN) {
            simd_gemm_ukernel<GEMM_RM, 1>(C + jj, A, B + jj, K, N);
        }
        for (; jj < N; jj++) {
            for (int64_t i = 0; i < GEMM_RM; i++) {
                float a = C[i * N + jj];
                for (int64_t kk = 0; kk < K; kk++) {
                    a += A[i + kk] * B[kk * N + jj];
                }
                C[i * N + jj] = a;
            }
        }

        A += GEMM_RM * K;
        C += GEMM_RM * N;
    }

    // Tail rows: one at a time
    for (; ii < M; ii++) {
        int64_t jj = 0;
        for (; jj + GEMM_RN * KN <= N; jj += GEMM_RN * KN) {
            simd_gemm_ukernel<1, GEMM_RN>(C + jj, A, B + jj, K, N);
        }
        for (; jj + KN <= N; jj += KN) {
            simd_gemm_ukernel<1, 1>(C + jj, A, B + jj, K, N);
        }
        for (; jj < N; jj++) {
            float a = C[jj];
            for (int64_t kk = 0; kk < K; kk++) {
                a += A[kk] * B[kk * N + jj];
            }
            C[jj] = a;
        }

        A += K;
        C += N;
    }
}
#elif defined(GGML_SIMD) && defined(__riscv_v_intrinsic)
// RM accumulators + 1 B vector = RM + 1 <= 8  =>  RM <= 7
// Microkernel: C[RM x vl] += A[RM x K] * B[K x N]
template <int RM>
static inline void rvv_simd_gemm_ukernel(
    float       * GGML_RESTRICT C,
    const float * GGML_RESTRICT A,
    const float * GGML_RESTRICT B,
    int K, int N, size_t vl)
{
    static_assert(RM >= 1 && RM <= 7, "RM must be 1..7 for LMUL=4");

    vfloat32m4_t acc_0 = __riscv_vle32_v_f32m4(C + 0 * N, vl);
    vfloat32m4_t acc_1, acc_2, acc_3, acc_4, acc_5, acc_6;
    if constexpr (RM > 1) acc_1 = __riscv_vle32_v_f32m4(C + 1 * N, vl);
    if constexpr (RM > 2) acc_2 = __riscv_vle32_v_f32m4(C + 2 * N, vl);
    if constexpr (RM > 3) acc_3 = __riscv_vle32_v_f32m4(C + 3 * N, vl);
    if constexpr (RM > 4) acc_4 = __riscv_vle32_v_f32m4(C + 4 * N, vl);
    if constexpr (RM > 5) acc_5 = __riscv_vle32_v_f32m4(C + 5 * N, vl);
    if constexpr (RM > 6) acc_6 = __riscv_vle32_v_f32m4(C + 6 * N, vl);

    for (int kk = 0; kk < K; kk++) {
        vfloat32m4_t b_0 = __riscv_vle32_v_f32m4(B + kk * N, vl);

                              acc_0 = __riscv_vfmacc_vf_f32m4(acc_0, A[0 * K + kk], b_0, vl);
        if constexpr (RM > 1) acc_1 = __riscv_vfmacc_vf_f32m4(acc_1, A[1 * K + kk], b_0, vl);
        if constexpr (RM > 2) acc_2 = __riscv_vfmacc_vf_f32m4(acc_2, A[2 * K + kk], b_0, vl);
        if constexpr (RM > 3) acc_3 = __riscv_vfmacc_vf_f32m4(acc_3, A[3 * K + kk], b_0, vl);
        if constexpr (RM > 4) acc_4 = __riscv_vfmacc_vf_f32m4(acc_4, A[4 * K + kk], b_0, vl);
        if constexpr (RM > 5) acc_5 = __riscv_vfmacc_vf_f32m4(acc_5, A[5 * K + kk], b_0, vl);
        if constexpr (RM > 6) acc_6 = __riscv_vfmacc_vf_f32m4(acc_6, A[6 * K + kk], b_0, vl);
    }

                          __riscv_vse32_v_f32m4(C + 0 * N, acc_0, vl);
    if constexpr (RM > 1) __riscv_vse32_v_f32m4(C + 1 * N, acc_1, vl);
    if constexpr (RM > 2) __riscv_vse32_v_f32m4(C + 2 * N, acc_2, vl);
    if constexpr (RM > 3) __riscv_vse32_v_f32m4(C + 3 * N, acc_3, vl);
    if constexpr (RM > 4) __riscv_vse32_v_f32m4(C + 4 * N, acc_4, vl);
    if constexpr (RM > 5) __riscv_vse32_v_f32m4(C + 5 * N, acc_5, vl);
    if constexpr (RM > 6) __riscv_vse32_v_f32m4(C + 6 * N, acc_6, vl);
}

template <int RM>
static inline void rvv_simd_gemm_dispatch_tail(
    float       * GGML_RESTRICT C,
    const float * GGML_RESTRICT A,
    const float * GGML_RESTRICT B,
    int K, int N, int KN, int remaining_rows)
{
    if constexpr (RM > 0) {
        if (remaining_rows == RM) {
            int64_t jj = 0;
            for (; jj + KN <= N; jj += KN) {
                rvv_simd_gemm_ukernel<RM>(C + jj, A, B + jj, K, N, KN);
            }
            if (jj < N) {
                rvv_simd_gemm_ukernel<RM>(C + jj, A, B + jj, K, N, N - jj);
            }
        } else {
            rvv_simd_gemm_dispatch_tail<RM - 1>(C, A, B, K, N, KN, remaining_rows);
        }
    }
}

static constexpr int GEMM_RM = 7;

// C[M x N] += A[M x K] * B[K x N]
static void simd_gemm(
    float       * GGML_RESTRICT C,
    const float * GGML_RESTRICT A,
    const float * GGML_RESTRICT B,
    int M, int K, int N)
{
    const int KN = (int)__riscv_vlenb();
    int64_t ii = 0;
    for (; ii + GEMM_RM <= M; ii += GEMM_RM) {
        int64_t jj = 0;
        for (; jj + KN <= N; jj += KN) {
            rvv_simd_gemm_ukernel<GEMM_RM>(C + jj, A, B + jj, K, N, KN);
        }
        if (jj < N) {
            rvv_simd_gemm_ukernel<GEMM_RM>(C + jj, A, B + jj, K, N, N - jj);
        }
        A += GEMM_RM * K;
        C += GEMM_RM * N;
    }

    int remaining_rows = M - ii;
    rvv_simd_gemm_dispatch_tail<GEMM_RM - 1>(C, A, B, K, N, KN, remaining_rows);
}

#if defined(__GNUC__) && !defined(__clang__)
#pragma GCC diagnostic pop
#endif

#else // scalar path

static void simd_gemm(
    float       * GGML_RESTRICT C,
    const float * GGML_RESTRICT A,
    const float * GGML_RESTRICT B,
    int M, int K, int N)
{
    for (int64_t i = 0; i < M; i++) {
        for (int64_t j = 0; j < N; j++) {
            float sum = C[i * N + j];
            for (int64_t kk = 0; kk < K; kk++) {
                sum += A[i * K + kk] * B[kk * N + j];
            }
            C[i * N + j] = sum;
        }
    }
}

#endif // GGML_SIMD