// Auto-generated file. Do not edit!
//   Template: src/qs8-gemm/c8-neoni8mm.c.in
//   Generator: tools/xngen
//
// Copyright 2023 Google LLC
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.

#include <assert.h>

#include <arm_neon.h>

#include "xnnpack/gemm.h"
#include "xnnpack/math.h"


void xnn_qd8_f16_qc8w_gemm_minmax_ukernel_2x8c8__neoni8mm(
    size_t mr,
    size_t nc,
    size_t kc,
    const int8_t* restrict a,
    size_t a_stride,
    const void* restrict w,
    xnn_float16* restrict c,
    size_t cm_stride,
    size_t cn_stride,
    const union xnn_f16_minmax_params params[restrict XNN_MIN_ELEMENTS(1)],
    const struct xnn_qd8_quantization_params quantization_params[restrict XNN_MIN_ELEMENTS(1)]) XNN_OOB_READS
{
  assert(mr != 0);
  assert(mr <= 2);
  assert(nc != 0);
  assert(kc != 0);
  assert(kc % sizeof(int8_t) == 0);
  assert(a != NULL);
  assert(w != NULL);
  assert(c != NULL);

  kc = round_up_po2(kc, 8 * sizeof(int8_t));
  const int8_t* a0 = a;
  uint16_t* c0 = (uint16_t*) c;
  const int8_t* a1 = (const int8_t*) ((uintptr_t) a0 + a_stride);
  uint16_t* c1 = (uint16_t*) ((uintptr_t) c0 + cm_stride);
  if XNN_UNPREDICTABLE(mr != 2) {
    a1 = a0;
    c1 = c0;
  }

  // Loop over groups of 8 columns.
  do {
    // Initialize accumulators with bias. 8 bias values are loaded from the
    // weight matrix, at the start of the group of 8 columns.
    const int32x4_t vinput_zero_point01 = vld1q_s32(&quantization_params[0].zero_point);
    const int32x4_t vksum0123 = vld1q_s32(w); w = (const int32_t*) w + 4;
    const int32x4_t vksumzp0x0123 = vmulq_lane_s32(vksum0123, vget_low_s32(vinput_zero_point01), 0);
    const int32x4_t vksumzp1x0123 = vmulq_lane_s32(vksum0123, vget_high_s32(vinput_zero_point01), 0);
    const int32x4_t vksum4567 = vld1q_s32(w); w = (const int32_t*) w + 4;
    const int32x4_t vksumzp0x4567 = vmulq_lane_s32(vksum4567, vget_low_s32(vinput_zero_point01), 0);
    const int32x4_t vksumzp1x4567 = vmulq_lane_s32(vksum4567, vget_high_s32(vinput_zero_point01), 0);

    int32x4_t vacc01x01 = vreinterpretq_s32_u64(vtrn1q_u64(vreinterpretq_u64_s32(vksumzp0x0123), vreinterpretq_u64_s32(vksumzp1x0123)));
    int32x4_t vacc01x23 = vreinterpretq_s32_u64(vtrn2q_u64(vreinterpretq_u64_s32(vksumzp0x0123), vreinterpretq_u64_s32(vksumzp1x0123)));
    int32x4_t vacc01x45 = vreinterpretq_s32_u64(vtrn1q_u64(vreinterpretq_u64_s32(vksumzp0x4567), vreinterpretq_u64_s32(vksumzp1x4567)));
    int32x4_t vacc01x67 = vreinterpretq_s32_u64(vtrn2q_u64(vreinterpretq_u64_s32(vksumzp0x4567), vreinterpretq_u64_s32(vksumzp1x4567)));

    // Inner accumulation loop along the 8 columns.
    size_t k = kc;
    // 2x partial unrolled loop to load 8 bytes at a time.

    uint64x2x2_t va01x0123456789ABCDEF;
    va01x0123456789ABCDEF.val[0] = vdupq_n_u64(0);
    va01x0123456789ABCDEF.val[1] = vdupq_n_u64(0);

    while (k >= 16 * sizeof(int8_t)) {
      // Load a 2x16 block of activations.
      va01x0123456789ABCDEF = vld2q_lane_u64((const void*) a0, va01x0123456789ABCDEF, 0); a0 += 16;
      va01x0123456789ABCDEF = vld2q_lane_u64((const void*) a1, va01x0123456789ABCDEF, 1); a1 += 16;

      const int8x16_t va01x01234567 = vreinterpretq_s8_u64(va01x0123456789ABCDEF.val[0]);
      const int8x16_t va01x89ABCDEF = vreinterpretq_s8_u64(va01x0123456789ABCDEF.val[1]);

      // Load a 16x8 block of weights.
      const int8x16_t vb01x01234567 = vld1q_s8(w); w = (const int8_t*) w + 16;
      const int8x16_t vb23x01234567 = vld1q_s8(w); w = (const int8_t*) w + 16;
      const int8x16_t vb45x01234567 = vld1q_s8(w); w = (const int8_t*) w + 16;
      const int8x16_t vb67x01234567 = vld1q_s8(w); w = (const int8_t*) w + 16;
      const int8x16_t vb01x89ABCDEF = vld1q_s8(w); w = (const int8_t*) w + 16;
      const int8x16_t vb23x89ABCDEF = vld1q_s8(w); w = (const int8_t*) w + 16;
      const int8x16_t vb45x89ABCDEF = vld1q_s8(w); w = (const int8_t*) w + 16;
      const int8x16_t vb67x89ABCDEF = vld1q_s8(w); w = (const int8_t*) w + 16;

      // Multiply-accumulate: 2x8 * 8x8 --> 2x8.
      vacc01x01 = vmmlaq_s32(vacc01x01, va01x01234567, vb01x01234567);
      vacc01x23 = vmmlaq_s32(vacc01x23, va01x01234567, vb23x01234567);
      vacc01x45 = vmmlaq_s32(vacc01x45, va01x01234567, vb45x01234567);
      vacc01x67 = vmmlaq_s32(vacc01x67, va01x01234567, vb67x01234567);
      vacc01x01 = vmmlaq_s32(vacc01x01, va01x89ABCDEF, vb01x89ABCDEF);
      vacc01x23 = vmmlaq_s32(vacc01x23, va01x89ABCDEF, vb23x89ABCDEF);
      vacc01x45 = vmmlaq_s32(vacc01x45, va01x89ABCDEF, vb45x89ABCDEF);
      vacc01x67 = vmmlaq_s32(vacc01x67, va01x89ABCDEF, vb67x89ABCDEF);

      k -= 16 * sizeof(int8_t);
    }
    // Handle up to 8 final positions of `k`
    if XNN_UNLIKELY(k != 0) {
      // Load a 2x8 block of activations.
      uint64x2_t va01x01234567 = vld1q_dup_u64((const void*) a0); a0 += 8;
      va01x01234567 = vld1q_lane_u64((const void*) a1, va01x01234567, 1); a1 += 8;

      // Load a 16x8 block of weights.
      const int8x16_t vb01x01234567 = vld1q_s8(w); w = (const int8_t*) w + 16;
      const int8x16_t vb23x01234567 = vld1q_s8(w); w = (const int8_t*) w + 16;
      const int8x16_t vb45x01234567 = vld1q_s8(w); w = (const int8_t*) w + 16;
      const int8x16_t vb67x01234567 = vld1q_s8(w); w = (const int8_t*) w + 16;

      // Multiply-accumulate: 2x4 * 4x8 --> 2x8.
      vacc01x01 = vmmlaq_s32(vacc01x01, vreinterpretq_s8_u64(va01x01234567), vb01x01234567);
      vacc01x23 = vmmlaq_s32(vacc01x23, vreinterpretq_s8_u64(va01x01234567), vb23x01234567);
      vacc01x45 = vmmlaq_s32(vacc01x45, vreinterpretq_s8_u64(va01x01234567), vb45x01234567);
      vacc01x67 = vmmlaq_s32(vacc01x67, vreinterpretq_s8_u64(va01x01234567), vb67x01234567);
    }

    int32x4_t vacc0x0123 = vreinterpretq_s32_u64(vtrn1q_u64(vreinterpretq_u64_s32(vacc01x01), vreinterpretq_u64_s32(vacc01x23)));
    int32x4_t vacc1x0123 = vreinterpretq_s32_u64(vtrn2q_u64(vreinterpretq_u64_s32(vacc01x01), vreinterpretq_u64_s32(vacc01x23)));
    int32x4_t vacc0x4567 = vreinterpretq_s32_u64(vtrn1q_u64(vreinterpretq_u64_s32(vacc01x45), vreinterpretq_u64_s32(vacc01x67)));
    int32x4_t vacc1x4567 = vreinterpretq_s32_u64(vtrn2q_u64(vreinterpretq_u64_s32(vacc01x45), vreinterpretq_u64_s32(vacc01x67)));
    float32x4_t vout0x0123 = vcvtq_f32_s32(vacc0x0123);
    float32x4_t vout0x4567 = vcvtq_f32_s32(vacc0x4567);
    float32x4_t vout1x0123 = vcvtq_f32_s32(vacc1x0123);
    float32x4_t vout1x4567 = vcvtq_f32_s32(vacc1x4567);

    const float32x4_t vinput_scale01 = vreinterpretq_f32_s32(vld1q_s32(&quantization_params[0].zero_point));
    vout0x0123 = vmulq_lane_f32(vout0x0123, vget_low_f32(vinput_scale01), 1);
    vout1x0123 = vmulq_lane_f32(vout1x0123, vget_high_f32(vinput_scale01), 1);
    vout0x4567 = vmulq_lane_f32(vout0x4567, vget_low_f32(vinput_scale01), 1);
    vout1x4567 = vmulq_lane_f32(vout1x4567, vget_high_f32(vinput_scale01), 1);

    const float32x4_t vfilter_output_scale0123 = vld1q_f32(w); w = (const float*) w + 4;
    const float32x4_t vfilter_output_scale4567 = vld1q_f32(w); w = (const float*) w + 4;

    const float32x4_t vbias0123 = vld1q_f32(w); w = (const float*) w + 4;
    vout0x0123 = vfmaq_f32(vbias0123, vout0x0123, vfilter_output_scale0123);
    vout1x0123 = vfmaq_f32(vbias0123, vout1x0123, vfilter_output_scale0123);
    const float32x4_t vbias4567 = vld1q_f32(w); w = (const float*) w + 4;
    vout0x4567 = vfmaq_f32(vbias4567, vout0x4567, vfilter_output_scale4567);
    vout1x4567 = vfmaq_f32(vbias4567, vout1x4567, vfilter_output_scale4567);

    float16x8_t vfp16out0x01234567 = vcombine_f16(vcvt_f16_f32(vout0x0123), vcvt_f16_f32(vout0x4567));
    float16x8_t vfp16out1x01234567 = vcombine_f16(vcvt_f16_f32(vout1x0123), vcvt_f16_f32(vout1x4567));

    const float16x8_t voutput_min = vreinterpretq_f16_u16(vld1q_dup_u16((const uint16_t*) &params->scalar.min));
    vfp16out0x01234567 = vmaxq_f16(vfp16out0x01234567, voutput_min);
    vfp16out1x01234567 = vmaxq_f16(vfp16out1x01234567, voutput_min);
    const float16x8_t voutput_max = vreinterpretq_f16_u16(vld1q_dup_u16((const uint16_t*) &params->scalar.max));
    vfp16out0x01234567 = vminq_f16(vfp16out0x01234567, voutput_max);
    vfp16out1x01234567 = vminq_f16(vfp16out1x01234567, voutput_max);
    if XNN_LIKELY(nc >= 8) {
      vst1q_u16(c0, vreinterpretq_u16_f16(vfp16out0x01234567));
      vst1q_u16(c1, vreinterpretq_u16_f16(vfp16out1x01234567));

      a0 = (const int8_t*) ((uintptr_t) a0 - kc);
      a1 = (const int8_t*) ((uintptr_t) a1 - kc);

      c0 = (uint16_t*) ((uintptr_t) c0 + cn_stride);
      c1 = (uint16_t*) ((uintptr_t) c1 + cn_stride);

      nc -= 8;
    } else {
     float16x4_t vfp16out0x0123 = vget_low_f16(vfp16out0x01234567);
     float16x4_t vfp16out1x0123 = vget_low_f16(vfp16out1x01234567);
     if (nc & 4) {
       vst1_u16(c0, vreinterpret_u16_f16(vfp16out0x0123)); c0 += 4;
       vst1_u16(c1, vreinterpret_u16_f16(vfp16out1x0123)); c1 += 4;
       vfp16out0x0123 = vget_high_f16(vfp16out0x01234567);
       vfp16out1x0123 = vget_high_f16(vfp16out1x01234567);
     }
     if (nc & 2) {
       vst1_lane_u32((void*) c0, vreinterpret_u32_f16(vfp16out0x0123), 0); c0 += 2;
       vst1_lane_u32((void*) c1, vreinterpret_u32_f16(vfp16out1x0123), 0); c1 += 2;
       vfp16out0x0123 = vext_f16(vfp16out0x0123, vfp16out0x0123, 2);
       vfp16out1x0123 = vext_f16(vfp16out1x0123, vfp16out1x0123, 2);
     }
     if (nc & 1) {
       vst1_lane_u16(c0, vreinterpret_u16_f16(vfp16out0x0123), 0);
       vst1_lane_u16(c1, vreinterpret_u16_f16(vfp16out1x0123), 0);
     }
      nc = 0;
    }
  } while (nc != 0);
}
