dc/dd2/cuda_2tensor__kernel_8h_source.html

#ifndef __MATH_TENSOR_KERNEL_H__

#define __MATH_TENSOR_KERNEL_H__

/*

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 COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,

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 BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;

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*/

template< typename T, const int N >


__global__ void tnsr3d_el_kernel(T  * __restrict__  v,

                              const int nv,

                              const T * __restrict__ u,

                              const int nu,

                              const T * __restrict__ A,

                              const T * __restrict__ Bt,

                              const T * __restrict__ Ct,

                              const int *  elements,

                              const int n_points) {

  __shared__ T shwork[N*N*N];

  __shared__ T shwork2[N*N*N];


  const int idx = threadIdx.x;

  const int str = blockDim.x;

  const int pt = blockIdx.x;

  const int e = elements[pt];


  for (int ii = idx; ii< nu*nu*nv; ii += str) {

    T tmp = 0.0;

    int j = ii/nv;

    int i = ii - j*nv;

    for( int l = 0; l < nu; l++){

      tmp += A[i+l*nv+pt*nv*nu]*u[l+nu*j+e*nu*nu*nu];

    }

    shwork[ii] = tmp;

  }


  __syncthreads();


  for (int ijk = idx; ijk< nu*nv*nv; ijk += str) {

    const int jk = ijk / nv;

    const int i = ijk - jk * nv;

    const int k = jk / nv;

    const int j = jk - k * nv;

    T tmp = 0.0;

    const int ik2 = i + k*nv*nu;

    for( int l = 0; l < nu; l++){

      tmp += Bt[l+j*nu+pt*nv*nu]*shwork[l*nv+ik2];

    }

    shwork2[ijk] = tmp;

  }


  __syncthreads();


  for (int ijk = idx; ijk< nv*nv*nv; ijk += str) {

    const int jk = ijk / nv;

    const int i = ijk - jk * nv;

    const int k = jk / nv;

    const int j = jk - k * nv;

    T tmp = 0.0;

    const int ij2 = i + j*nv;

    for( int l = 0; l < nu; l++){

      tmp += Ct[l+k*nu+pt*nv*nu]*shwork2[ij2 + l*nv*nv];

    }

    v[ijk+pt*nv*nv*nv] = tmp;

  }


}


template< typename T, const int N >


__global__ void tnsr3d_kernel(T  * __restrict__  v,

                              const int nv,

                              const T * __restrict__ u,

                              const int nu,

                              const T * __restrict__ A,

                              const T * __restrict__ Bt,

                              const T * __restrict__ Ct) {

  __shared__ T shwork[N*N*N];

  __shared__ T shwork2[N*N*N];


  const int idx = threadIdx.x;

  const int str = blockDim.x;

  const int e = blockIdx.x;


  for (int ii = idx; ii< nu*nu*nv; ii += str) {

    T tmp = 0.0;

    int j = ii/nv;

    int i = ii - j*nv;

    for( int l = 0; l < nu; l++){

      tmp += A[i+l*nv]*u[l+nu*j+e*nu*nu*nu];

    }

    shwork[ii] = tmp;

  }


  __syncthreads();


  for (int ijk = idx; ijk< nu*nv*nv; ijk += str) {

    const int jk = ijk / nv;

    const int i = ijk - jk * nv;

    const int k = jk / nv;

    const int j = jk - k * nv;

    T tmp = 0.0;

    const int ik2 = i + k*nv*nu;

    for( int l = 0; l < nu; l++){

      tmp += Bt[l+j*nu]*shwork[l*nv+ik2];

    }

    shwork2[ijk] = tmp;

  }


  __syncthreads();


  for (int ijk = idx; ijk< nv*nv*nv; ijk += str) {

    const int jk = ijk / nv;

    const int i = ijk - jk * nv;

    const int k = jk / nv;

    const int j = jk - k * nv;

    T tmp = 0.0;

    const int ij2 = i + j*nv;

    for( int l = 0; l < nu; l++){

      tmp += Ct[l+k*nu]*shwork2[ij2 + l*nv*nv];

    }

    v[ijk+e*nv*nv*nv] = tmp;

  }

}


template< typename T, const int N >


__global__ void tnsr3d_kernel_large(T  * __restrict__  v,

                                    const int nv,

                                    const T * __restrict__ u,

                                    const int nu,

                                    const T * __restrict__ A,

                                    const T * __restrict__ Bt,

                                    const T * __restrict__ Ct) {

  __shared__ T shwork[N*N*N];

  T shwork2[N*N*N];


  const int idx = threadIdx.x;

  const int str = blockDim.x;

  const int e = blockIdx.x;


  for (int ii = idx; ii< nu*nu*nv; ii += str) {

    T tmp = 0.0;

    int j = ii/nv;

    int i = ii - j*nv;

    for( int l = 0; l < nu; l++){

      tmp += A[i+l*nv]*u[l+nu*j+e*nu*nu*nu];

    }

    shwork[ii] = tmp;

  }


  __syncthreads();


  for (int ijk = idx; ijk< nu*nv*nv; ijk += str) {

    const int jk = ijk / nv;

    const int i = ijk - jk * nv;

    const int k = jk / nv;

    const int j = jk - k * nv;

    T tmp = 0.0;

    const int ik2 = i + k*nv*nu;

    for( int l = 0; l < nu; l++){

      tmp += Bt[l+j*nu]*shwork[l*nv+ik2];

    }

    shwork2[ijk] = tmp;

  }


  __syncthreads();


  for (int ijk = idx; ijk< nv*nv*nv; ijk += str) {

    const int jk = ijk / nv;

    const int i = ijk - jk * nv;

    const int k = jk / nv;

    const int j = jk - k * nv;

    T tmp = 0.0;

    const int ij2 = i + j*nv;

    for( int l = 0; l < nu; l++){

      tmp += Ct[l+k*nu]*shwork2[ij2 + l*nv*nv];

    }

    v[ijk+e*nv*nv*nv] = tmp;

  }

}


#endif // __MATH_TENSOR_KERNEL_H__

i
const int i
Definition ax_helm_full_kernel.h:95

u
__global__ void T *__restrict__ T *__restrict__ const T *__restrict__ u
Definition ax_helm_full_kernel.h:46

e
const int e
Definition ax_helm_full_kernel.h:93

v
__global__ void T *__restrict__ T *__restrict__ const T *__restrict__ const T *__restrict__ v
Definition ax_helm_full_kernel.h:47

j
const int j
Definition ax_helm_full_kernel.h:94

__syncthreads
__syncthreads()

dirichlet_apply_scalar_kernel
__global__ void dirichlet_apply_scalar_kernel(const int *__restrict__ msk, T *__restrict__ x, const T g, const int m)
Definition dirichlet_kernel.h:42

tnsr3d_el_kernel
__global__ void tnsr3d_el_kernel(T *__restrict__ v, const int nv, const T *__restrict__ u, const int nu, const T *__restrict__ A, const T *__restrict__ Bt, const T *__restrict__ Ct, const int *elements, const int n_points)
Definition tensor_kernel.h:37

tnsr3d_kernel
__global__ void tnsr3d_kernel(T *__restrict__ v, const int nv, const T *__restrict__ u, const int nu, const T *__restrict__ A, const T *__restrict__ Bt, const T *__restrict__ Ct)
Definition tensor_kernel.h:99

tnsr3d_kernel_large
__global__ void tnsr3d_kernel_large(T *__restrict__ v, const int nv, const T *__restrict__ u, const int nu, const T *__restrict__ A, const T *__restrict__ Bt, const T *__restrict__ Ct)
Definition tensor_kernel.h:155