// Copyright 2024 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.

$assert MR % 32 == 0
#include <assert.h>

#include <hvx_hexagon_protos.h>
#include <hexagon_protos.h>
#include <hexagon_types.h>

#include "xnnpack/simd/f32-hvx.h"

#include "xnnpack/prefetch.h"
#include "xnnpack/spmm.h"

void xnn_f32_spmm_minmax_ukernel_${MR}x${NR}__hvx_pipelined${"_x" + str(UNROLL) if UNROLL > 1 else ""}(
    size_t mc,
    size_t nc,
    const float* input,
    const float* weights,
    const int32_t* widx_dmap,
    const uint32_t* nidx_nnzmap,
    float* output,
    size_t output_stride,
    const union xnn_f32_minmax_params params[restrict XNN_MIN_ELEMENTS(1)])
{
  assert(mc != 0);
  assert(mc % sizeof(float) == 0);
  assert(nc != 0);

  const HVX_Vector vmin = xnn_set1_f32(params->scalar.min);
  const HVX_Vector vmax = xnn_set1_f32(params->scalar.max);

  size_t output_decrement = output_stride * nc - ${MR} * sizeof(float);
  while XNN_LIKELY(mc >= ${MR} * sizeof(float)) {
    const float* w = weights;
    const int32_t* dmap = widx_dmap;
    const uint32_t* nnzmap = nidx_nnzmap;
    HVX_Vector vw = xnn_set1_f32(*w); w += 1;

    intptr_t diff = *dmap++;

    HVX_Vector vi0 = xnn_loadu_f32(input);
    $for M in range(32, MR, 32):
      HVX_Vector vi${int(M/32)} = xnn_loadu_f32(input + ${M});

    size_t n = nc;

    do {
      uint32_t nnz = *nnzmap++;
      $for M in range(0, MR, 32):
        HVX_Vector vacc${int(M/32)} = vw;
      vw = xnn_set1_f32(*w); w += 1;

      $if UNROLL > 1:
        for(; nnz >= ${UNROLL}; nnz -= ${UNROLL}) {
          $for K in range(0, UNROLL):
            $for M in range(0, MR, 32):
              vacc${int(M/32)} = xnn_fmadd_f32(vi${int(M/32)}, vw, vacc${int(M/32)});
            input = (const float*) ((uintptr_t) input + (uintptr_t) diff);

            diff = *dmap++;

            vw = xnn_set1_f32(*w); w += 1;

            $for M in range(0, MR, 32):
              vi${int(M/32)} = xnn_loadu_f32(input + ${M});
        }
      if XNN_LIKELY(nnz != 0) {
        do {
          $for M in range(0, MR, 32):
            vacc${int(M/32)} = xnn_fmadd_f32(vi${int(M/32)}, vw, vacc${int(M/32)});
          input = (const float*) ((uintptr_t) input + (uintptr_t) diff);

          diff = *dmap++;

          vw = xnn_set1_f32(*w); w += 1;

          vi0 = xnn_loadu_f32(input);
          $for M in range(32, MR, 32):
            vi${int(M/32)} = xnn_loadu_f32(input + ${M});
        } while (--nnz != 0);
      }
      $for M in range(0, MR, 32):
        HVX_Vector vout${int(M/32)} = xnn_min_f32(vacc${int(M/32)}, vmax);

      $for M in range(0, MR, 32):
        vout${int(M/32)} = xnn_max_f32(vout${int(M/32)}, vmin);

      xnn_storeu_f32(output, vout0);
      $for M in range(32, MR, 32):
        xnn_storeu_f32(output + ${M}, vout${int(M/32)});
      output = (float*) ((uintptr_t) output + output_stride);
    } while (--n != 0);
    output = (float*) ((uintptr_t) output - output_decrement);
    input += ${MR};
    mc -= ${MR} * sizeof(float);
  }
  if XNN_UNLIKELY(mc != 0) {
    $for LOG2M in reversed(range((MR - 1).bit_length())):
      $SUBMR = 1 << LOG2M
      $if SUBMR != 1:
        $if SUBMR * 2 >= MR:
          output_decrement += ${MR - SUBMR} * sizeof(float);
        $else:
          output_decrement += ${SUBMR} * sizeof(float);
      if (mc & (${SUBMR} * sizeof(float))) {
        const float* w = weights;
        const int32_t* dmap = widx_dmap;
        const uint32_t* nnzmap = nidx_nnzmap;
        size_t n = nc;
        do {
          uint32_t nnz = *nnzmap++;
          HVX_Vector vacc0 = xnn_set1_f32(*w); w += 1;
          $for M in range(32, SUBMR, 32):
            HVX_Vector vacc${int(M/32)} = vacc0;
          if XNN_LIKELY(nnz != 0) {
            do {
              const intptr_t diff = *dmap++;

              const HVX_Vector vi0 = xnn_loadu_f32(input);
              $for M in range(32, SUBMR, 32):
                const HVX_Vector vi${int(M/32)} = xnn_loadu_f32(input + ${M});
              input = (const float*) ((uintptr_t) input + (uintptr_t) diff);

              const HVX_Vector vw = xnn_set1_f32(*w); w += 1;

              $for M in range(0, SUBMR, 32):
                vacc${int(M/32)} = xnn_fmadd_f32(vi${int(M/32)}, vw, vacc${int(M/32)});
            } while (--nnz != 0);
          }
          $for M in range(0, SUBMR, 32):
            HVX_Vector vout${int(M/32)} = xnn_min_f32(vacc${int(M/32)}, vmax);
          $for M in range(0, SUBMR, 32):
            vout${int(M/32)} = xnn_max_f32(vout${int(M/32)}, vmin);

          $if SUBMR >= 32:
            xnn_storeu_f32(output, vout0);
            $for M in range(32, SUBMR, 32):
              xnn_storeu_f32(output + ${M}, vout${int(M/32)});
          $else:
            xnn_store_tail_f32(output, vout0, ${SUBMR});
          output = (float*) ((uintptr_t) output + output_stride);
        } while (--n != 0);
        $if SUBMR != 1:
          output = (float*) ((uintptr_t) output - output_decrement);
          input += ${SUBMR};
      }
  }
}
