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!14605 FIX NB14 ERROR 

From: @mamba_ni
Reviewed-by: @ljl0711,@wang_zi_dong
Signed-off-by: @wang_zi_dong
This commit is contained in:
mindspore-ci-bot 2021-04-02 17:03:27 +08:00 committed by Gitee
parent 0af32e3422 3dae6103ec
commit ad9c04cc4e
5 changed files with 7 additions and 15 deletions
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7
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nb14/dihedral_14_cf_energy_impl.cu
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@ -54,8 +54,8 @@ __global__ void Dihedral14CFEnergyKernel(const int dihedral_14_numbers, const UI
void Dihedral14CFEnergy(const int dihedral_14_numbers, const int atom_numbers, const int *uint_crd_f, const int *LJtype, void Dihedral14CFEnergy(const int dihedral_14_numbers, const int atom_numbers, const int *uint_crd_f, const int *LJtype,
const float *charge, float *uint_crd_with_LJ_f, const float *boxlength_f, const int *a_14, const float *charge, float *uint_crd_with_LJ_f, const float *boxlength_f, const int *a_14,
const int *b_14, const float *cf_scale_factor, float *ene, cudaStream_t stream) { const int *b_14, const float *cf_scale_factor, float *ene, cudaStream_t stream) {
size_t thread_per_block = 128; size_t thread_per_block = 32;
size_t block_per_grid = ceilf(static_cast<float>(atom_numbers) / 128); size_t block_per_grid = ceilf(static_cast<float>(dihedral_14_numbers) / 32);
UNSIGNED_INT_VECTOR *uint_crd = UNSIGNED_INT_VECTOR *uint_crd =
const_cast<UNSIGNED_INT_VECTOR *>(reinterpret_cast<const UNSIGNED_INT_VECTOR *>(uint_crd_f)); const_cast<UNSIGNED_INT_VECTOR *>(reinterpret_cast<const UNSIGNED_INT_VECTOR *>(uint_crd_f));
@ -65,12 +65,9 @@ void Dihedral14CFEnergy(const int dihedral_14_numbers, const int atom_numbers, c
atom_numbers, uint_crd, uint_crd_with_LJ, LJtype, charge); atom_numbers, uint_crd, uint_crd_with_LJ, LJtype, charge);
VECTOR *boxlength = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(boxlength_f)); VECTOR *boxlength = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(boxlength_f));
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(atom_numbers, ene, 0.);
Dihedral14CFEnergyKernel<<<block_per_grid, thread_per_block, 0, stream>>>( Dihedral14CFEnergyKernel<<<block_per_grid, thread_per_block, 0, stream>>>(
dihedral_14_numbers, uint_crd_with_LJ, boxlength, a_14, b_14, cf_scale_factor, ene); dihedral_14_numbers, uint_crd_with_LJ, boxlength, a_14, b_14, cf_scale_factor, ene);
cudaStreamSynchronize(stream);
return; return;
} }

4
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nb14/dihedral_14_lj_cf_force_with_atom_energy_impl.cu
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@ -111,7 +111,7 @@ void Dihedral14LJCFForceWithAtomEnergy(const int dihedral_14_numbers, const int
const float *LJ_type_A, const float *LJ_type_B, float *frc_f, float *atom_energy, const float *LJ_type_A, const float *LJ_type_B, float *frc_f, float *atom_energy,
cudaStream_t stream) { cudaStream_t stream) {
size_t thread_per_block = 128; size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(atom_numbers) / 128); size_t block_per_grid = ceilf(static_cast<float>(dihedral_14_numbers) / 128);
UNSIGNED_INT_VECTOR *uint_crd = UNSIGNED_INT_VECTOR *uint_crd =
const_cast<UNSIGNED_INT_VECTOR *>(reinterpret_cast<const UNSIGNED_INT_VECTOR *>(uint_crd_f)); const_cast<UNSIGNED_INT_VECTOR *>(reinterpret_cast<const UNSIGNED_INT_VECTOR *>(uint_crd_f));
@ -129,8 +129,6 @@ void Dihedral14LJCFForceWithAtomEnergy(const int dihedral_14_numbers, const int
dihedral_14_numbers, uint_crd_with_LJ, boxlength, a_14, b_14, lj_scale_factor, cf_scale_factor, LJ_type_A, dihedral_14_numbers, uint_crd_with_LJ, boxlength, a_14, b_14, lj_scale_factor, cf_scale_factor, LJ_type_A,
LJ_type_B, frc, atom_energy); LJ_type_B, frc, atom_energy);
cudaStreamSynchronize(stream);
return; return;
} }

7
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nb14/dihedral_14_lj_energy_impl.cu
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@ -75,8 +75,8 @@ void Dihedral14LJEnergy(const int dihedral_14_numbers, const int atom_numbers, c
const float *charge, float *uint_crd_with_LJ_f, const float *boxlength_f, const int *a_14, const float *charge, float *uint_crd_with_LJ_f, const float *boxlength_f, const int *a_14,
const int *b_14, const float *lj_scale_factor, const float *LJ_type_A, const float *LJ_type_B, const int *b_14, const float *lj_scale_factor, const float *LJ_type_A, const float *LJ_type_B,
float *ene, cudaStream_t stream) { float *ene, cudaStream_t stream) {
size_t thread_per_block = 128; size_t thread_per_block = 32;
size_t block_per_grid = ceilf(static_cast<float>(atom_numbers) / 128); size_t block_per_grid = ceilf(static_cast<float>(dihedral_14_numbers) / 32);
UNSIGNED_INT_VECTOR *uint_crd = UNSIGNED_INT_VECTOR *uint_crd =
const_cast<UNSIGNED_INT_VECTOR *>(reinterpret_cast<const UNSIGNED_INT_VECTOR *>(uint_crd_f)); const_cast<UNSIGNED_INT_VECTOR *>(reinterpret_cast<const UNSIGNED_INT_VECTOR *>(uint_crd_f));
@ -84,14 +84,11 @@ void Dihedral14LJEnergy(const int dihedral_14_numbers, const int atom_numbers, c
Copy_Crd_To_New_Crd_Start<<<ceilf(static_cast<float>(atom_numbers) / 32), 32, 0, stream>>>( Copy_Crd_To_New_Crd_Start<<<ceilf(static_cast<float>(atom_numbers) / 32), 32, 0, stream>>>(
atom_numbers, uint_crd, uint_crd_with_LJ, LJtype, charge); atom_numbers, uint_crd, uint_crd_with_LJ, LJtype, charge);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(dihedral_14_numbers, ene, 0.);
VECTOR *boxlength = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(boxlength_f)); VECTOR *boxlength = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(boxlength_f));
Dihedral14LJEnergyKernel<<<block_per_grid, thread_per_block, 0, stream>>>( Dihedral14LJEnergyKernel<<<block_per_grid, thread_per_block, 0, stream>>>(
dihedral_14_numbers, uint_crd_with_LJ, boxlength, a_14, b_14, lj_scale_factor, LJ_type_A, LJ_type_B, ene); dihedral_14_numbers, uint_crd_with_LJ, boxlength, a_14, b_14, lj_scale_factor, LJ_type_A, LJ_type_B, ene);
cudaStreamSynchronize(stream);
return; return;
} }

2
mindspore/ccsrc/backend/kernel_compiler/gpu/sponge/nb14/dihedral_14_cf_energy_kernel.h
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@ -92,7 +92,7 @@ class Dihedral14CFEnergyGpuKernel : public GpuKernel {
input_size_list_.push_back(ele_b_14 * sizeof(T1)); input_size_list_.push_back(ele_b_14 * sizeof(T1));
input_size_list_.push_back(ele_cf_scale_factor * sizeof(T)); input_size_list_.push_back(ele_cf_scale_factor * sizeof(T));
workspace_size_list_.push_back(atom_numbers * sizeof(UINT_VECTOR_LJ_TYPE)); workspace_size_list_.push_back(atom_numbers * sizeof(UINT_VECTOR_LJ_TYPE));
output_size_list_.push_back(atom_numbers * sizeof(T)); output_size_list_.push_back(dihedral_14_numbers * sizeof(T));
} }
private: private:

2
mindspore/ccsrc/backend/kernel_compiler/gpu/sponge/nb14/dihedral_14_lj_energy_kernel.h
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@ -102,7 +102,7 @@ class Dihedral14LJEnergyGpuKernel : public GpuKernel {
input_size_list_.push_back(ele_LJ_type_B * sizeof(T)); input_size_list_.push_back(ele_LJ_type_B * sizeof(T));
workspace_size_list_.push_back(atom_numbers * sizeof(UINT_VECTOR_LJ_TYPE)); workspace_size_list_.push_back(atom_numbers * sizeof(UINT_VECTOR_LJ_TYPE));
output_size_list_.push_back(atom_numbers * sizeof(T)); output_size_list_.push_back(dihedral_14_numbers * sizeof(T));
} }
private: private: