convect_scalar_kernel.h

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#ifndef __MATH_CONVECT_SCALAR_KERNEL_H__
#define __MATH_CONVECT_SCALAR_KERNEL_H__
/*
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*/
 
template< typename T, const int LX, const int CHUNKS >
__global__ void convect_scalar_kernel_1d(T * __restrict__ du,
                                const T * __restrict__ u,
                                const T * __restrict__ cr,
                                const T * __restrict__ cs,
                                const T * __restrict__ ct,
                                const T * __restrict__ dx,
                                const T * __restrict__ dy,
                                const T * __restrict__ dz) {
 
  __shared__ T shu[LX * LX * LX];
 
  __shared__ T shcr[LX * LX * LX];
  __shared__ T shcs[LX * LX * LX];
  __shared__ T shct[LX * LX * LX];
 
  __shared__ T shdx[LX * LX];
  __shared__ T shdy[LX * LX];
  __shared__ T shdz[LX * LX];
 
  const int e = blockIdx.x;
  const int iii = threadIdx.x;
  const int nchunks = (LX * LX * LX - 1) / CHUNKS + 1;
  const int ele = e*LX*LX*LX;
 
  if (iii < (LX * LX)) {
    shdx[iii] = dx[iii];
    shdy[iii] = dy[iii];
    shdz[iii] = dz[iii];
  }
 
  int l = iii;
  while(l < (LX * LX * LX)) {
    shu[l] = u[l + ele];
 
    shcr[l] = cr[l + ele];
    shcs[l] = cs[l + ele];
    shct[l] = ct[l + ele];
 
    l = l + CHUNKS;
  }
 
  __syncthreads();
 
  for (int n = 0; n < nchunks; n++) {
    const int ijk = iii + n * CHUNKS;
    const int jk = ijk / LX;
    const int i = ijk - jk * LX;
    const int k = jk / LX;
    const int j = jk - k * LX;
    if ( i < LX && j < LX && k < LX) {
      T rtmp = 0.0;
      T stmp = 0.0;
      T ttmp = 0.0;
      for (int l = 0; l < LX; l++) {
    rtmp += shdx[i + l * LX] * shu[l + j * LX + k * LX * LX];
    stmp += shdy[j + l * LX] * shu[i + l * LX + k * LX * LX];
    ttmp += shdz[k + l * LX] * shu[i + j * LX + l * LX * LX];
      }
 
      du[ijk + e * LX * LX * LX] = shcr[ijk] * rtmp
                + shcs[ijk] * stmp
                + shct[ijk] * ttmp;
    }
  }
}
 
template< typename T, const int LX >
__global__ void __launch_bounds__(LX*LX,3)
  convect_scalar_kernel_kstep(T * __restrict__ du,
                     const T * __restrict__ u,
                     const T * __restrict__ cr,
                     const T * __restrict__ cs,
                     const T * __restrict__ ct,
                     const T * __restrict__ dx,
                     const T * __restrict__ dy,
                     const T * __restrict__ dz) {
 
  __shared__ T shu[LX * LX];
 
  __shared__ T shdx[LX*LX];
  __shared__ T shdy[LX*LX];
  __shared__ T shdz[LX*LX];
 
  const int e = blockIdx.x;
  const int j = threadIdx.y;
  const int i = threadIdx.x;
  const int ij = i + j * LX;
  const int ele = e*LX*LX*LX;
 
  shdx[ij] = dx[ij];
  shdy[ij] = dy[ij];
  shdz[ij] = dz[ij];
 
  T ru[LX];
  T rcr[LX];
  T rcs[LX];
  T rct[LX];
 
#pragma unroll LX
  for (int k = 0; k < LX; ++k) {
    ru[k] = u[ij + k*LX*LX + ele];
    rcr[k] = cr[ij + k*LX*LX + ele];
    rcs[k] = cs[ij + k*LX*LX + ele];
    rct[k] = ct[ij + k*LX*LX + ele];
  }
 
  __syncthreads();
 
#pragma unroll
  for (int k = 0; k < LX; ++k) {
    const int ijk = ij + k*LX*LX;
    T ttmp = 0.0;
    shu[ij] = ru[k];
    for (int l = 0; l < LX; l++) {
      ttmp += shdz[k+l*LX] * ru[l];
    }
    __syncthreads();
 
    T rtmp = 0.0;
    T stmp = 0.0;
#pragma unroll
    for (int l = 0; l < LX; l++) {
      rtmp += shdx[i+l*LX] * shu[l+j*LX];
      stmp += shdy[j+l*LX] * shu[i+l*LX];
    }
 
    du[ijk + ele] = rcr[k] * rtmp
                    + rcs[k] * stmp
                    + rct[k] * ttmp;
    __syncthreads();
  }
}
 
 
#endif // __MATH_CONVECT_SCALAR_KERNEL_H__