/* K=7 r=1/2 Viterbi decoder for PowerPC G4/G5 Altivec instructions
 * Feb 2004, Phil Karn, KA9Q
 */
#include <stdio.h>
#include <memory.h>
#include <stdlib.h>
#include "fec.h"

typedef union {
  long long p;
  unsigned char c[64];
  vector bool char v[4];
} decision_t;
typedef union {
  long long p;
  unsigned char c[64];
  vector unsigned char v[4];
} metric_t;

static union branchtab27 {
  unsigned char c[32];
  vector unsigned char v[2];
} Branchtab27[2];
static int Init = 0;

/* State info for instance of Viterbi decoder
 * Don't change this without also changing references in [mmx|sse|sse2]bfly29.s!
 */
struct v27 {
  metric_t metrics1; /* path metric buffer 1 */
  metric_t metrics2; /* path metric buffer 2 */
  decision_t *dp;          /* Pointer to current decision */
  metric_t *old_metrics,
           *new_metrics; /* Pointers to path metrics, swapped on every bit */
  decision_t *decisions;   /* Beginning of decisions for block */
};

/* Initialize Viterbi decoder for start of new frame */
int init_viterbi27_av(void *p, int starting_state)
{
  struct v27 *vp = p;
  int i;

  if (p == NULL) {
    return -1;
  }
  for (i = 0; i < 4; i++) {
    vp->metrics1.v[i] = (vector unsigned char)(63);
  }
  vp->old_metrics = &vp->metrics1;
  vp->new_metrics = &vp->metrics2;
  vp->dp = vp->decisions;
  vp->old_metrics->c[starting_state & 63] = 0; /* Bias known start state */
  return 0;
}

void set_viterbi27_polynomial_av(int polys[2])
{
  int state;

  for (state = 0; state < 32; state++) {
    Branchtab27[0].c[state] = (polys[0] < 0) ^ parity((2 * state) & abs(
                                polys[0])) ? 255 : 0;
    Branchtab27[1].c[state] = (polys[1] < 0) ^ parity((2 * state) & abs(
                                polys[1])) ? 255 : 0;
  }
  Init++;
}

/* Create a new instance of a Viterbi decoder */
void *create_viterbi27_av(int len)
{
  struct v27 *vp;

  if (!Init) {
    int polys[2] = { V27POLYA, V27POLYB };
    set_viterbi27_polynomial_av(polys);
  }
  if ((vp = (struct v27 *)malloc(sizeof(struct v27))) == NULL) {
    return NULL;
  }
  if ((vp->decisions = (decision_t *)malloc((len + 6) * sizeof(
                         decision_t))) == NULL) {
    free(vp);
    return NULL;
  }
  init_viterbi27_av(vp, 0);
  return vp;
}

/* Viterbi chainback */
int chainback_viterbi27_av(
  void *p,
  unsigned char *data, /* Decoded output data */
  unsigned int nbits, /* Number of data bits */
  unsigned int endstate)  /* Terminal encoder state */
{
  struct v27 *vp = p;
  decision_t *d = (decision_t *)vp->decisions;

  if (p == NULL) {
    return -1;
  }

  /* Make room beyond the end of the encoder register so we can
   * accumulate a full byte of decoded data
   */
  endstate %= 64;
  endstate <<= 2;

  /* The store into data[] only needs to be done every 8 bits.
   * But this avoids a conditional branch, and the writes will
   * combine in the cache anyway
   */
  d += 6; /* Look past tail */
  while (nbits-- != 0) {
    int k;

    k = d[nbits].c[endstate >> 2] & 1;
    data[nbits >> 3] = endstate = (endstate >> 1) | (k << 7);
  }
  return 0;
}

/* Delete instance of a Viterbi decoder */
void delete_viterbi27_av(void *p)
{
  struct v27 *vp = p;

  if (vp != NULL) {
    free(vp->decisions);
    free(vp);
  }
}

/* Process received symbols */
int update_viterbi27_blk_av(void *p, unsigned char *syms, int nbits)
{
  struct v27 *vp = p;
  decision_t *d;

  if (p == NULL) {
    return -1;
  }
  d = (decision_t *)vp->dp;
  while (nbits--) {
    vector unsigned char survivor0, survivor1, sym0v, sym1v;
    vector bool char decision0, decision1;
    vector unsigned char metric, m_metric, m0, m1, m2, m3;
    void *tmp;

    /* sym0v.0 = syms[0]; sym0v.1 = syms[1] */
    sym0v = vec_perm(vec_ld(0, syms), vec_ld(1, syms), vec_lvsl(0, syms));

    sym1v = vec_splat(sym0v, 1); /* Splat syms[1] across sym1v */
    sym0v = vec_splat(sym0v, 0); /* Splat syms[0] across sym0v */
    syms += 2;

    /* Do the 32 butterflies as two interleaved groups of 16 each to keep the pipes full */

    /* Form first set of 16 branch metrics */
    metric = vec_avg(vec_xor(Branchtab27[0].v[0], sym0v),
                     vec_xor(Branchtab27[1].v[0], sym1v));
    metric = vec_sr(metric, (vector unsigned char)(3));
    m_metric = vec_sub((vector unsigned char)(31), metric);

    /* Form first set of path metrics */
    m0 = vec_adds(vp->old_metrics->v[0], metric);
    m3 = vec_adds(vp->old_metrics->v[2], metric);
    m1 = vec_adds(vp->old_metrics->v[2], m_metric);
    m2 = vec_adds(vp->old_metrics->v[0], m_metric);

    /* Form second set of 16 branch metrics */
    metric = vec_avg(vec_xor(Branchtab27[0].v[1], sym0v),
                     vec_xor(Branchtab27[1].v[1], sym1v));
    metric = vec_sr(metric, (vector unsigned char)(3));
    m_metric = vec_sub((vector unsigned char)(31), metric);

    /* Compare and select first set */
    decision0 = vec_cmpgt(m0, m1);
    decision1 = vec_cmpgt(m2, m3);
    survivor0 = vec_min(m0, m1);
    survivor1 = vec_min(m2, m3);

    /* Compute second set of path metrics */
    m0 = vec_adds(vp->old_metrics->v[1], metric);
    m3 = vec_adds(vp->old_metrics->v[3], metric);
    m1 = vec_adds(vp->old_metrics->v[3], m_metric);
    m2 = vec_adds(vp->old_metrics->v[1], m_metric);

    /* Interleave and store first decisions and survivors */
    d->v[0] = vec_mergeh(decision0, decision1);
    d->v[1] = vec_mergel(decision0, decision1);
    vp->new_metrics->v[0] = vec_mergeh(survivor0, survivor1);
    vp->new_metrics->v[1] = vec_mergel(survivor0, survivor1);

    /* Compare and select second set */
    decision0 = vec_cmpgt(m0, m1);
    decision1 = vec_cmpgt(m2, m3);
    survivor0 = vec_min(m0, m1);
    survivor1 = vec_min(m2, m3);

    /* Interleave and store second set of decisions and survivors */
    d->v[2] = vec_mergeh(decision0, decision1);
    d->v[3] = vec_mergel(decision0, decision1);
    vp->new_metrics->v[2] = vec_mergeh(survivor0, survivor1);
    vp->new_metrics->v[3] = vec_mergel(survivor0, survivor1);

    /* renormalize if necessary */
    if (vp->new_metrics->c[0] >= 105) {
      vector unsigned char scale0, scale1;

      /* Find smallest metric and splat */
      scale0 = vec_min(vp->new_metrics->v[0], vp->new_metrics->v[1]);
      scale1 = vec_min(vp->new_metrics->v[2], vp->new_metrics->v[3]);
      scale0 = vec_min(scale0, scale1);
      scale0 = vec_min(scale0, vec_sld(scale0, scale0, 8));
      scale0 = vec_min(scale0, vec_sld(scale0, scale0, 4));
      scale0 = vec_min(scale0, vec_sld(scale0, scale0, 2));
      scale0 = vec_min(scale0, vec_sld(scale0, scale0, 1));

      /* Now subtract from all metrics */
      vp->new_metrics->v[0] = vec_subs(vp->new_metrics->v[0], scale0);
      vp->new_metrics->v[1] = vec_subs(vp->new_metrics->v[1], scale0);
      vp->new_metrics->v[2] = vec_subs(vp->new_metrics->v[2], scale0);
      vp->new_metrics->v[3] = vec_subs(vp->new_metrics->v[3], scale0);
    }
    d++;
    /* Swap pointers to old and new metrics */
    tmp = vp->old_metrics;
    vp->old_metrics = vp->new_metrics;
    vp->new_metrics = tmp;
  }
  vp->dp = d;

  return 0;
}