cfl_kernel.h

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#ifndef __MATH_CFL_KERNEL_H__
#define __MATH_CFL_KERNEL_H__
/*
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 "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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template< typename T>
__inline__ __device__ T cfl_reduce_warp(T val) {
  val = fmax(val, __shfl_down_sync(0xffffffff, val, 16));
  val = fmax(val, __shfl_down_sync(0xffffffff, val, 8));
  val = fmax(val, __shfl_down_sync(0xffffffff, val, 4));
  val = fmax(val, __shfl_down_sync(0xffffffff, val, 2));
  val = fmax(val, __shfl_down_sync(0xffffffff, val, 1));
  return val;
}
 
template< typename T >
__global__ void cfl_reduce_kernel(T * bufred, const int n) {
                
  T cfl = 0;
  const int idx = blockIdx.x * blockDim.x + threadIdx.x;
  const int str = blockDim.x * gridDim.x;
  for (int i = idx; i<n ; i += str) 
  {
    cfl = fmax(cfl, bufred[i]);
  }
 
  __shared__ T shared[32];
  unsigned int lane = threadIdx.x % warpSize;
  unsigned int wid = threadIdx.x / warpSize;
 
  cfl = cfl_reduce_warp<T>(cfl);
  if (lane == 0)
    shared[wid] = cfl;
  __syncthreads();
 
  cfl = (threadIdx.x < blockDim.x / warpSize) ? shared[lane] : 0;
  if (wid == 0)
    cfl = cfl_reduce_warp<T>(cfl);
 
  if (threadIdx.x == 0)
    bufred[blockIdx.x] = cfl;
}
 
template< typename T, const int LX, const int CHUNKS >
__global__ void cfl_kernel(const T dt,
               const T * __restrict__ u,
               const T * __restrict__ v,
               const T * __restrict__ w,
               const T * __restrict__ drdx,
               const T * __restrict__ dsdx,
               const T * __restrict__ dtdx,
               const T * __restrict__ drdy,
               const T * __restrict__ dsdy,
               const T * __restrict__ dtdy,
               const T * __restrict__ drdz,
               const T * __restrict__ dsdz,
               const T * __restrict__ dtdz,
               const T * __restrict__ dr_inv,
               const T * __restrict__ ds_inv, 
               const T * __restrict__ dt_inv,
               const T * __restrict__ jacinv,
               T * __restrict__ cfl_h) { 
 
  int i,j,k;
  
  const int e = blockIdx.x;
  const int iii = threadIdx.x;
  const int nchunks = (LX * LX * LX - 1) / CHUNKS + 1;
  const unsigned int lane = threadIdx.x % warpSize;
  const unsigned int wid = threadIdx.x / warpSize;
 
  __shared__ T shu[LX * LX * LX];
  __shared__ T shv[LX * LX * LX];
  __shared__ T shw[LX * LX * LX];
 
  __shared__ T shdr_inv[LX];
  __shared__ T shds_inv[LX];
  __shared__ T shdt_inv[LX];
 
  __shared__ T shjacinv[LX * LX * LX];
 
  __shared__ T shared[32];
 
  if (iii < LX) {
    shdr_inv[iii] = dr_inv[iii];
    shds_inv[iii] = ds_inv[iii];
    shdt_inv[iii] = dt_inv[iii];
  }
 
  j = iii;
  while(j < (LX * LX * LX)) {
    shu[j] = u[j + e * LX * LX * LX];
    shv[j] = v[j + e * LX * LX * LX];
    shw[j] = w[j + e * LX * LX * LX];
    
    shjacinv[j] = jacinv[j + e * LX * LX * LX];
 
    j = j + CHUNKS;
  }
  
  __syncthreads();
 
  T cfl_tmp = 0.0;
  for (int n = 0; n < nchunks; n++) {
    const int ijk = iii + n * CHUNKS;
    const int jk = ijk / LX;
    i = ijk - jk * LX;
    k = jk / LX;
    j = jk - k * LX;
    if ( i < LX && j < LX && k < LX) {
      const T cflr = fabs( dt * ( ( shu[ijk] * drdx[ijk + e * LX * LX * LX]
                                    + shv[ijk] * drdy[ijk + e * LX * LX * LX]
                                    * shw[ijk] * drdz[ijk + e * LX * LX * LX] 
                                    ) * shjacinv[ijk]) * shdr_inv[i]);
      const T cfls = fabs( dt * ( ( shu[ijk] * dsdx[ijk + e * LX * LX * LX]
                                    + shv[ijk] * dsdy[ijk + e * LX * LX * LX]
                                    + shw[ijk] * dsdz[ijk + e * LX * LX * LX] 
                                    ) * shjacinv[ijk]) * shds_inv[j]);
      const T cflt = fabs( dt * ( ( shu[ijk] * dtdx[ijk + e * LX * LX * LX]
                                    + shv[ijk] * dtdy[ijk + e * LX * LX * LX]
                                    + shw[ijk] * dtdz[ijk + e * LX * LX * LX] 
                                    ) * shjacinv[ijk]) * shdt_inv[k]);
 
      cfl_tmp = fmax(cflr + cfls + cflt, cfl_tmp);
 
    }
  }
 
  cfl_tmp = cfl_reduce_warp<T>(cfl_tmp);
  if (lane == 0)
    shared[wid] = cfl_tmp;
  __syncthreads();
  
  cfl_tmp = (threadIdx.x < blockDim.x / warpSize) ? shared[lane] : 0;
  if (wid == 0)
    cfl_tmp = cfl_reduce_warp<T>(cfl_tmp);
 
  if (threadIdx.x == 0)
    cfl_h[blockIdx.x] = cfl_tmp;
}
 
 
#endif // __MATH_CFL_KERNEL_H__