#include <../src/mat/impls/baij/seq/baij.h>
#include <petsc/private/kernels/blockinvert.h>

/*
      Special case where the matrix was ILU(0) factored in the natural
   ordering. This eliminates the need for the column and row permutation.
*/
PetscErrorCode MatSolve_SeqBAIJ_4_NaturalOrdering_inplace(Mat A,Vec bb,Vec xx)
{
  Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
  PetscInt          n  =a->mbs;
  const PetscInt    *ai=a->i,*aj=a->j;
  PetscErrorCode    ierr;
  const PetscInt    *diag = a->diag;
  const MatScalar   *aa   =a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr);
  ierr = VecGetArray(xx,&x);CHKERRQ(ierr);

#if defined(PETSC_USE_FORTRAN_KERNEL_SOLVEBAIJ)
  {
    static PetscScalar w[2000]; /* very BAD need to fix */
    fortransolvebaij4_(&n,x,ai,aj,diag,aa,b,w);
  }
#elif defined(PETSC_USE_FORTRAN_KERNEL_SOLVEBAIJUNROLL)
  fortransolvebaij4unroll_(&n,x,ai,aj,diag,aa,b);
#else
  {
    PetscScalar     s1,s2,s3,s4,x1,x2,x3,x4;
    const MatScalar *v;
    PetscInt        jdx,idt,idx,nz,i,ai16;
    const PetscInt  *vi;

    /* forward solve the lower triangular */
    idx  = 0;
    x[0] = b[0]; x[1] = b[1]; x[2] = b[2]; x[3] = b[3];
    for (i=1; i<n; i++) {
      v    =  aa      + 16*ai[i];
      vi   =  aj      + ai[i];
      nz   =  diag[i] - ai[i];
      idx +=  4;
      s1   =  b[idx];s2 = b[1+idx];s3 = b[2+idx];s4 = b[3+idx];
      while (nz--) {
        jdx = 4*(*vi++);
        x1  = x[jdx];x2 = x[1+jdx];x3 = x[2+jdx];x4 = x[3+jdx];
        s1 -= v[0]*x1 + v[4]*x2 + v[8]*x3  + v[12]*x4;
        s2 -= v[1]*x1 + v[5]*x2 + v[9]*x3  + v[13]*x4;
        s3 -= v[2]*x1 + v[6]*x2 + v[10]*x3 + v[14]*x4;
        s4 -= v[3]*x1 + v[7]*x2 + v[11]*x3 + v[15]*x4;
        v  += 16;
      }
      x[idx]   = s1;
      x[1+idx] = s2;
      x[2+idx] = s3;
      x[3+idx] = s4;
    }
    /* backward solve the upper triangular */
    idt = 4*(n-1);
    for (i=n-1; i>=0; i--) {
      ai16 = 16*diag[i];
      v    = aa + ai16 + 16;
      vi   = aj + diag[i] + 1;
      nz   = ai[i+1] - diag[i] - 1;
      s1   = x[idt];  s2 = x[1+idt];
      s3   = x[2+idt];s4 = x[3+idt];
      while (nz--) {
        idx = 4*(*vi++);
        x1  = x[idx];   x2 = x[1+idx];x3    = x[2+idx]; x4 = x[3+idx];
        s1 -= v[0]*x1 + v[4]*x2 + v[8]*x3   + v[12]*x4;
        s2 -= v[1]*x1 + v[5]*x2 + v[9]*x3   + v[13]*x4;
        s3 -= v[2]*x1 + v[6]*x2 + v[10]*x3  + v[14]*x4;
        s4 -= v[3]*x1 + v[7]*x2 + v[11]*x3  + v[15]*x4;
        v  += 16;
      }
      v        = aa + ai16;
      x[idt]   = v[0]*s1 + v[4]*s2 + v[8]*s3  + v[12]*s4;
      x[1+idt] = v[1]*s1 + v[5]*s2 + v[9]*s3  + v[13]*s4;
      x[2+idt] = v[2]*s1 + v[6]*s2 + v[10]*s3 + v[14]*s4;
      x[3+idt] = v[3]*s1 + v[7]*s2 + v[11]*s3 + v[15]*s4;
      idt     -= 4;
    }
  }
#endif

  ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr);
  ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
  ierr = PetscLogFlops(2.0*16*(a->nz) - 4.0*A->cmap->n);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqBAIJ_4_NaturalOrdering(Mat A,Vec bb,Vec xx)
{
  Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
  const PetscInt    n=a->mbs,*vi,*ai=a->i,*aj=a->j,*adiag=a->diag;
  PetscInt          i,k,nz,idx,jdx,idt;
  PetscErrorCode    ierr;
  const PetscInt    bs = A->rmap->bs,bs2 = a->bs2;
  const MatScalar   *aa=a->a,*v;
  PetscScalar       *x;
  const PetscScalar *b;
  PetscScalar       s1,s2,s3,s4,x1,x2,x3,x4;

  PetscFunctionBegin;
  ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr);
  ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
  /* forward solve the lower triangular */
  idx  = 0;
  x[0] = b[idx]; x[1] = b[1+idx];x[2] = b[2+idx];x[3] = b[3+idx];
  for (i=1; i<n; i++) {
    v   = aa + bs2*ai[i];
    vi  = aj + ai[i];
    nz  = ai[i+1] - ai[i];
    idx = bs*i;
    s1  = b[idx];s2 = b[1+idx];s3 = b[2+idx];s4 = b[3+idx];
    for (k=0; k<nz; k++) {
      jdx = bs*vi[k];
      x1  = x[jdx];x2 = x[1+jdx]; x3 =x[2+jdx];x4 =x[3+jdx];
      s1 -= v[0]*x1 + v[4]*x2 + v[8]*x3 + v[12]*x4;
      s2 -= v[1]*x1 + v[5]*x2 + v[9]*x3 + v[13]*x4;
      s3 -= v[2]*x1 + v[6]*x2 + v[10]*x3 + v[14]*x4;
      s4 -= v[3]*x1 + v[7]*x2 + v[11]*x3 + v[15]*x4;

      v +=  bs2;
    }

    x[idx]   = s1;
    x[1+idx] = s2;
    x[2+idx] = s3;
    x[3+idx] = s4;
  }

  /* backward solve the upper triangular */
  for (i=n-1; i>=0; i--) {
    v   = aa + bs2*(adiag[i+1]+1);
    vi  = aj + adiag[i+1]+1;
    nz  = adiag[i] - adiag[i+1]-1;
    idt = bs*i;
    s1  = x[idt];  s2 = x[1+idt];s3 = x[2+idt];s4 = x[3+idt];

    for (k=0; k<nz; k++) {
      idx = bs*vi[k];
      x1  = x[idx];   x2 = x[1+idx]; x3 = x[2+idx];x4 = x[3+idx];
      s1 -= v[0]*x1 + v[4]*x2 + v[8]*x3 + v[12]*x4;
      s2 -= v[1]*x1 + v[5]*x2 + v[9]*x3 + v[13]*x4;
      s3 -= v[2]*x1 + v[6]*x2 + v[10]*x3 + v[14]*x4;
      s4 -= v[3]*x1 + v[7]*x2 + v[11]*x3 + v[15]*x4;

      v +=  bs2;
    }
    /* x = inv_diagonal*x */
    x[idt]   = v[0]*s1 + v[4]*s2 + v[8]*s3 + v[12]*s4;
    x[1+idt] = v[1]*s1 + v[5]*s2 + v[9]*s3 + v[13]*s4;
    x[2+idt] = v[2]*s1 + v[6]*s2 + v[10]*s3 + v[14]*s4;
    x[3+idt] = v[3]*s1 + v[7]*s2 + v[11]*s3 + v[15]*s4;

  }

  ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr);
  ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
  ierr = PetscLogFlops(2.0*bs2*(a->nz) - bs*A->cmap->n);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqBAIJ_4_NaturalOrdering_Demotion(Mat A,Vec bb,Vec xx)
{
  Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
  const PetscInt    n  =a->mbs,*ai=a->i,*aj=a->j,*diag=a->diag;
  PetscErrorCode    ierr;
  const MatScalar   *aa=a->a;
  const PetscScalar *b;
  PetscScalar       *x;

  PetscFunctionBegin;
  ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr);
  ierr = VecGetArray(xx,&x);CHKERRQ(ierr);

  {
    MatScalar       s1,s2,s3,s4,x1,x2,x3,x4;
    const MatScalar *v;
    MatScalar       *t=(MatScalar*)x;
    PetscInt        jdx,idt,idx,nz,i,ai16;
    const PetscInt  *vi;

    /* forward solve the lower triangular */
    idx  = 0;
    t[0] = (MatScalar)b[0];
    t[1] = (MatScalar)b[1];
    t[2] = (MatScalar)b[2];
    t[3] = (MatScalar)b[3];
    for (i=1; i<n; i++) {
      v    =  aa      + 16*ai[i];
      vi   =  aj      + ai[i];
      nz   =  diag[i] - ai[i];
      idx +=  4;
      s1   = (MatScalar)b[idx];
      s2   = (MatScalar)b[1+idx];
      s3   = (MatScalar)b[2+idx];
      s4   = (MatScalar)b[3+idx];
      while (nz--) {
        jdx = 4*(*vi++);
        x1  = t[jdx];
        x2  = t[1+jdx];
        x3  = t[2+jdx];
        x4  = t[3+jdx];
        s1 -= v[0]*x1 + v[4]*x2 + v[8]*x3  + v[12]*x4;
        s2 -= v[1]*x1 + v[5]*x2 + v[9]*x3  + v[13]*x4;
        s3 -= v[2]*x1 + v[6]*x2 + v[10]*x3 + v[14]*x4;
        s4 -= v[3]*x1 + v[7]*x2 + v[11]*x3 + v[15]*x4;
        v  += 16;
      }
      t[idx]   = s1;
      t[1+idx] = s2;
      t[2+idx] = s3;
      t[3+idx] = s4;
    }
    /* backward solve the upper triangular */
    idt = 4*(n-1);
    for (i=n-1; i>=0; i--) {
      ai16 = 16*diag[i];
      v    = aa + ai16 + 16;
      vi   = aj + diag[i] + 1;
      nz   = ai[i+1] - diag[i] - 1;
      s1   = t[idt];
      s2   = t[1+idt];
      s3   = t[2+idt];
      s4   = t[3+idt];
      while (nz--) {
        idx = 4*(*vi++);
        x1  = (MatScalar)x[idx];
        x2  = (MatScalar)x[1+idx];
        x3  = (MatScalar)x[2+idx];
        x4  = (MatScalar)x[3+idx];
        s1 -= v[0]*x1 + v[4]*x2 + v[8]*x3  + v[12]*x4;
        s2 -= v[1]*x1 + v[5]*x2 + v[9]*x3  + v[13]*x4;
        s3 -= v[2]*x1 + v[6]*x2 + v[10]*x3 + v[14]*x4;
        s4 -= v[3]*x1 + v[7]*x2 + v[11]*x3 + v[15]*x4;
        v  += 16;
      }
      v        = aa + ai16;
      x[idt]   = (PetscScalar)(v[0]*s1 + v[4]*s2 + v[8]*s3  + v[12]*s4);
      x[1+idt] = (PetscScalar)(v[1]*s1 + v[5]*s2 + v[9]*s3  + v[13]*s4);
      x[2+idt] = (PetscScalar)(v[2]*s1 + v[6]*s2 + v[10]*s3 + v[14]*s4);
      x[3+idt] = (PetscScalar)(v[3]*s1 + v[7]*s2 + v[11]*s3 + v[15]*s4);
      idt     -= 4;
    }
  }

  ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr);
  ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
  ierr = PetscLogFlops(2.0*16*(a->nz) - 4.0*A->cmap->n);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#if defined(PETSC_HAVE_SSE)

#include PETSC_HAVE_SSE
PetscErrorCode MatSolve_SeqBAIJ_4_NaturalOrdering_SSE_Demotion_usj(Mat A,Vec bb,Vec xx)
{
  Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
  unsigned short *aj=(unsigned short*)a->j;
  PetscErrorCode ierr;
  int            *ai=a->i,n=a->mbs,*diag = a->diag;
  MatScalar      *aa=a->a;
  PetscScalar    *x,*b;

  PetscFunctionBegin;
  SSE_SCOPE_BEGIN;
  /*
     Note: This code currently uses demotion of double
     to float when performing the mixed-mode computation.
     This may not be numerically reasonable for all applications.
  */
  PREFETCH_NTA(aa+16*ai[1]);

  ierr = VecGetArray(bb,&b);CHKERRQ(ierr);
  ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
  {
    /* x will first be computed in single precision then promoted inplace to double */
    MatScalar      *v,*t=(MatScalar*)x;
    int            nz,i,idt,ai16;
    unsigned int   jdx,idx;
    unsigned short *vi;
    /* Forward solve the lower triangular factor. */

    /* First block is the identity. */
    idx = 0;
    CONVERT_DOUBLE4_FLOAT4(t,b);
    v =  aa + 16*((unsigned int)ai[1]);

    for (i=1; i<n;) {
      PREFETCH_NTA(&v[8]);
      vi   =  aj      + ai[i];
      nz   =  diag[i] - ai[i];
      idx +=  4;

      /* Demote RHS from double to float. */
      CONVERT_DOUBLE4_FLOAT4(&t[idx],&b[idx]);
      LOAD_PS(&t[idx],XMM7);

      while (nz--) {
        PREFETCH_NTA(&v[16]);
        jdx = 4*((unsigned int)(*vi++));

        /* 4x4 Matrix-Vector product with negative accumulation: */
        SSE_INLINE_BEGIN_2(&t[jdx],v)
        SSE_LOAD_PS(SSE_ARG_1,FLOAT_0,XMM6)

        /* First Column */
        SSE_COPY_PS(XMM0,XMM6)
        SSE_SHUFFLE(XMM0,XMM0,0x00)
        SSE_MULT_PS_M(XMM0,SSE_ARG_2,FLOAT_0)
        SSE_SUB_PS(XMM7,XMM0)

        /* Second Column */
        SSE_COPY_PS(XMM1,XMM6)
        SSE_SHUFFLE(XMM1,XMM1,0x55)
        SSE_MULT_PS_M(XMM1,SSE_ARG_2,FLOAT_4)
        SSE_SUB_PS(XMM7,XMM1)

        SSE_PREFETCH_NTA(SSE_ARG_2,FLOAT_24)

        /* Third Column */
        SSE_COPY_PS(XMM2,XMM6)
        SSE_SHUFFLE(XMM2,XMM2,0xAA)
        SSE_MULT_PS_M(XMM2,SSE_ARG_2,FLOAT_8)
        SSE_SUB_PS(XMM7,XMM2)

        /* Fourth Column */
        SSE_COPY_PS(XMM3,XMM6)
        SSE_SHUFFLE(XMM3,XMM3,0xFF)
        SSE_MULT_PS_M(XMM3,SSE_ARG_2,FLOAT_12)
        SSE_SUB_PS(XMM7,XMM3)
        SSE_INLINE_END_2

        v += 16;
      }
      v =  aa + 16*ai[++i];
      PREFETCH_NTA(v);
      STORE_PS(&t[idx],XMM7);
    }

    /* Backward solve the upper triangular factor.*/

    idt  = 4*(n-1);
    ai16 = 16*diag[n-1];
    v    = aa + ai16 + 16;
    for (i=n-1; i>=0;) {
      PREFETCH_NTA(&v[8]);
      vi = aj + diag[i] + 1;
      nz = ai[i+1] - diag[i] - 1;

      LOAD_PS(&t[idt],XMM7);

      while (nz--) {
        PREFETCH_NTA(&v[16]);
        idx = 4*((unsigned int)(*vi++));

        /* 4x4 Matrix-Vector Product with negative accumulation: */
        SSE_INLINE_BEGIN_2(&t[idx],v)
        SSE_LOAD_PS(SSE_ARG_1,FLOAT_0,XMM6)

        /* First Column */
        SSE_COPY_PS(XMM0,XMM6)
        SSE_SHUFFLE(XMM0,XMM0,0x00)
        SSE_MULT_PS_M(XMM0,SSE_ARG_2,FLOAT_0)
        SSE_SUB_PS(XMM7,XMM0)

        /* Second Column */
        SSE_COPY_PS(XMM1,XMM6)
        SSE_SHUFFLE(XMM1,XMM1,0x55)
        SSE_MULT_PS_M(XMM1,SSE_ARG_2,FLOAT_4)
        SSE_SUB_PS(XMM7,XMM1)

        SSE_PREFETCH_NTA(SSE_ARG_2,FLOAT_24)

        /* Third Column */
        SSE_COPY_PS(XMM2,XMM6)
        SSE_SHUFFLE(XMM2,XMM2,0xAA)
        SSE_MULT_PS_M(XMM2,SSE_ARG_2,FLOAT_8)
        SSE_SUB_PS(XMM7,XMM2)

        /* Fourth Column */
        SSE_COPY_PS(XMM3,XMM6)
        SSE_SHUFFLE(XMM3,XMM3,0xFF)
        SSE_MULT_PS_M(XMM3,SSE_ARG_2,FLOAT_12)
        SSE_SUB_PS(XMM7,XMM3)
        SSE_INLINE_END_2
        v += 16;
      }
      v    = aa + ai16;
      ai16 = 16*diag[--i];
      PREFETCH_NTA(aa+ai16+16);
      /*
         Scale the result by the diagonal 4x4 block,
         which was inverted as part of the factorization
      */
      SSE_INLINE_BEGIN_3(v,&t[idt],aa+ai16)
      /* First Column */
      SSE_COPY_PS(XMM0,XMM7)
      SSE_SHUFFLE(XMM0,XMM0,0x00)
      SSE_MULT_PS_M(XMM0,SSE_ARG_1,FLOAT_0)

      /* Second Column */
      SSE_COPY_PS(XMM1,XMM7)
      SSE_SHUFFLE(XMM1,XMM1,0x55)
      SSE_MULT_PS_M(XMM1,SSE_ARG_1,FLOAT_4)
      SSE_ADD_PS(XMM0,XMM1)

      SSE_PREFETCH_NTA(SSE_ARG_3,FLOAT_24)

      /* Third Column */
      SSE_COPY_PS(XMM2,XMM7)
      SSE_SHUFFLE(XMM2,XMM2,0xAA)
      SSE_MULT_PS_M(XMM2,SSE_ARG_1,FLOAT_8)
      SSE_ADD_PS(XMM0,XMM2)

      /* Fourth Column */
      SSE_COPY_PS(XMM3,XMM7)
      SSE_SHUFFLE(XMM3,XMM3,0xFF)
      SSE_MULT_PS_M(XMM3,SSE_ARG_1,FLOAT_12)
      SSE_ADD_PS(XMM0,XMM3)

      SSE_STORE_PS(SSE_ARG_2,FLOAT_0,XMM0)
      SSE_INLINE_END_3

      v    = aa + ai16 + 16;
      idt -= 4;
    }

    /* Convert t from single precision back to double precision (inplace)*/
    idt = 4*(n-1);
    for (i=n-1; i>=0; i--) {
      /*     CONVERT_FLOAT4_DOUBLE4(&x[idt],&t[idt]); */
      /* Unfortunately, CONVERT_ will count from 0 to 3 which doesn't work here. */
      PetscScalar *xtemp=&x[idt];
      MatScalar   *ttemp=&t[idt];
      xtemp[3] = (PetscScalar)ttemp[3];
      xtemp[2] = (PetscScalar)ttemp[2];
      xtemp[1] = (PetscScalar)ttemp[1];
      xtemp[0] = (PetscScalar)ttemp[0];
      idt     -= 4;
    }

  } /* End of artificial scope. */
  ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);
  ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
  ierr = PetscLogFlops(2.0*16*(a->nz) - 4.0*A->cmap->n);CHKERRQ(ierr);
  SSE_SCOPE_END;
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqBAIJ_4_NaturalOrdering_SSE_Demotion(Mat A,Vec bb,Vec xx)
{
  Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
  int            *aj=a->j;
  PetscErrorCode ierr;
  int            *ai=a->i,n=a->mbs,*diag = a->diag;
  MatScalar      *aa=a->a;
  PetscScalar    *x,*b;

  PetscFunctionBegin;
  SSE_SCOPE_BEGIN;
  /*
     Note: This code currently uses demotion of double
     to float when performing the mixed-mode computation.
     This may not be numerically reasonable for all applications.
  */
  PREFETCH_NTA(aa+16*ai[1]);

  ierr = VecGetArray(bb,&b);CHKERRQ(ierr);
  ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
  {
    /* x will first be computed in single precision then promoted inplace to double */
    MatScalar *v,*t=(MatScalar*)x;
    int       nz,i,idt,ai16;
    int       jdx,idx;
    int       *vi;
    /* Forward solve the lower triangular factor. */

    /* First block is the identity. */
    idx = 0;
    CONVERT_DOUBLE4_FLOAT4(t,b);
    v =  aa + 16*ai[1];

    for (i=1; i<n;) {
      PREFETCH_NTA(&v[8]);
      vi   =  aj      + ai[i];
      nz   =  diag[i] - ai[i];
      idx +=  4;

      /* Demote RHS from double to float. */
      CONVERT_DOUBLE4_FLOAT4(&t[idx],&b[idx]);
      LOAD_PS(&t[idx],XMM7);

      while (nz--) {
        PREFETCH_NTA(&v[16]);
        jdx = 4*(*vi++);
/*          jdx = *vi++; */

        /* 4x4 Matrix-Vector product with negative accumulation: */
        SSE_INLINE_BEGIN_2(&t[jdx],v)
        SSE_LOAD_PS(SSE_ARG_1,FLOAT_0,XMM6)

        /* First Column */
        SSE_COPY_PS(XMM0,XMM6)
        SSE_SHUFFLE(XMM0,XMM0,0x00)
        SSE_MULT_PS_M(XMM0,SSE_ARG_2,FLOAT_0)
        SSE_SUB_PS(XMM7,XMM0)

        /* Second Column */
        SSE_COPY_PS(XMM1,XMM6)
        SSE_SHUFFLE(XMM1,XMM1,0x55)
        SSE_MULT_PS_M(XMM1,SSE_ARG_2,FLOAT_4)
        SSE_SUB_PS(XMM7,XMM1)

        SSE_PREFETCH_NTA(SSE_ARG_2,FLOAT_24)

        /* Third Column */
        SSE_COPY_PS(XMM2,XMM6)
        SSE_SHUFFLE(XMM2,XMM2,0xAA)
        SSE_MULT_PS_M(XMM2,SSE_ARG_2,FLOAT_8)
        SSE_SUB_PS(XMM7,XMM2)

        /* Fourth Column */
        SSE_COPY_PS(XMM3,XMM6)
        SSE_SHUFFLE(XMM3,XMM3,0xFF)
        SSE_MULT_PS_M(XMM3,SSE_ARG_2,FLOAT_12)
        SSE_SUB_PS(XMM7,XMM3)
        SSE_INLINE_END_2

        v += 16;
      }
      v =  aa + 16*ai[++i];
      PREFETCH_NTA(v);
      STORE_PS(&t[idx],XMM7);
    }

    /* Backward solve the upper triangular factor.*/

    idt  = 4*(n-1);
    ai16 = 16*diag[n-1];
    v    = aa + ai16 + 16;
    for (i=n-1; i>=0;) {
      PREFETCH_NTA(&v[8]);
      vi = aj + diag[i] + 1;
      nz = ai[i+1] - diag[i] - 1;

      LOAD_PS(&t[idt],XMM7);

      while (nz--) {
        PREFETCH_NTA(&v[16]);
        idx = 4*(*vi++);
/*          idx = *vi++; */

        /* 4x4 Matrix-Vector Product with negative accumulation: */
        SSE_INLINE_BEGIN_2(&t[idx],v)
        SSE_LOAD_PS(SSE_ARG_1,FLOAT_0,XMM6)

        /* First Column */
        SSE_COPY_PS(XMM0,XMM6)
        SSE_SHUFFLE(XMM0,XMM0,0x00)
        SSE_MULT_PS_M(XMM0,SSE_ARG_2,FLOAT_0)
        SSE_SUB_PS(XMM7,XMM0)

        /* Second Column */
        SSE_COPY_PS(XMM1,XMM6)
        SSE_SHUFFLE(XMM1,XMM1,0x55)
        SSE_MULT_PS_M(XMM1,SSE_ARG_2,FLOAT_4)
        SSE_SUB_PS(XMM7,XMM1)

        SSE_PREFETCH_NTA(SSE_ARG_2,FLOAT_24)

        /* Third Column */
        SSE_COPY_PS(XMM2,XMM6)
        SSE_SHUFFLE(XMM2,XMM2,0xAA)
        SSE_MULT_PS_M(XMM2,SSE_ARG_2,FLOAT_8)
        SSE_SUB_PS(XMM7,XMM2)

        /* Fourth Column */
        SSE_COPY_PS(XMM3,XMM6)
        SSE_SHUFFLE(XMM3,XMM3,0xFF)
        SSE_MULT_PS_M(XMM3,SSE_ARG_2,FLOAT_12)
        SSE_SUB_PS(XMM7,XMM3)
        SSE_INLINE_END_2
        v += 16;
      }
      v    = aa + ai16;
      ai16 = 16*diag[--i];
      PREFETCH_NTA(aa+ai16+16);
      /*
         Scale the result by the diagonal 4x4 block,
         which was inverted as part of the factorization
      */
      SSE_INLINE_BEGIN_3(v,&t[idt],aa+ai16)
      /* First Column */
      SSE_COPY_PS(XMM0,XMM7)
      SSE_SHUFFLE(XMM0,XMM0,0x00)
      SSE_MULT_PS_M(XMM0,SSE_ARG_1,FLOAT_0)

      /* Second Column */
      SSE_COPY_PS(XMM1,XMM7)
      SSE_SHUFFLE(XMM1,XMM1,0x55)
      SSE_MULT_PS_M(XMM1,SSE_ARG_1,FLOAT_4)
      SSE_ADD_PS(XMM0,XMM1)

      SSE_PREFETCH_NTA(SSE_ARG_3,FLOAT_24)

      /* Third Column */
      SSE_COPY_PS(XMM2,XMM7)
      SSE_SHUFFLE(XMM2,XMM2,0xAA)
      SSE_MULT_PS_M(XMM2,SSE_ARG_1,FLOAT_8)
      SSE_ADD_PS(XMM0,XMM2)

      /* Fourth Column */
      SSE_COPY_PS(XMM3,XMM7)
      SSE_SHUFFLE(XMM3,XMM3,0xFF)
      SSE_MULT_PS_M(XMM3,SSE_ARG_1,FLOAT_12)
      SSE_ADD_PS(XMM0,XMM3)

      SSE_STORE_PS(SSE_ARG_2,FLOAT_0,XMM0)
      SSE_INLINE_END_3

      v    = aa + ai16 + 16;
      idt -= 4;
    }

    /* Convert t from single precision back to double precision (inplace)*/
    idt = 4*(n-1);
    for (i=n-1; i>=0; i--) {
      /*     CONVERT_FLOAT4_DOUBLE4(&x[idt],&t[idt]); */
      /* Unfortunately, CONVERT_ will count from 0 to 3 which doesn't work here. */
      PetscScalar *xtemp=&x[idt];
      MatScalar   *ttemp=&t[idt];
      xtemp[3] = (PetscScalar)ttemp[3];
      xtemp[2] = (PetscScalar)ttemp[2];
      xtemp[1] = (PetscScalar)ttemp[1];
      xtemp[0] = (PetscScalar)ttemp[0];
      idt     -= 4;
    }

  } /* End of artificial scope. */
  ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);
  ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
  ierr = PetscLogFlops(2.0*16*(a->nz) - 4.0*A->cmap->n);CHKERRQ(ierr);
  SSE_SCOPE_END;
  PetscFunctionReturn(0);
}

#endif