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Improve the performence of put_along_axis #60618

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merged 3 commits into from
Jan 9, 2024
Merged

Improve the performence of put_along_axis #60618

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b29c130
fix bug of put_along_axis
YibinLiu666 Jan 3, 2024
eb47410
improve performence of put_along_axis
YibinLiu666 Jan 8, 2024
0f168e4
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
YibinLiu666 Jan 8, 2024
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88 changes: 34 additions & 54 deletions paddle/phi/kernels/funcs/gather_scatter_functor.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -92,6 +92,12 @@ class ReduceMin {
};
static ReduceMin reduce_min;

__global__ void CudaMemsetAsync(int* dest, int value, size_t size) {
int tid = threadIdx.x + blockIdx.x * blockDim.x;
if (tid * sizeof(int) >= size) return;
dest[tid] = value;
}

template <typename tensor_t,
typename index_t,
typename func_t,
Expand All @@ -112,13 +118,6 @@ __global__ void ScatterAssignGPUKernel(tensor_t* self_data,
int* thread_ids) {
int tid = threadIdx.x + blockIdx.x * blockDim.x;
if (tid >= numel) return;

if (tid == 0) {
for (int i = 0; i < numel_data; i++) {
thread_ids[i] = 0;
}
}
__syncthreads();
int64_t i, j, k; // The i, j, k here is the index of the 3 layers loop
// squeezed from the N layers loop.
/* tid = i * select_dim_size * outer_dim_size + j * outer_dim_size + k */
Expand Down Expand Up @@ -267,16 +266,6 @@ __global__ void ScatterMeanGPUKernel(tensor_t* self_data,
int tid = threadIdx.x + blockIdx.x * blockDim.x;
if (tid >= numel) return;

if (tid == 0) {
for (int i = 0; i < numel_data; i++) {
shared_mem[i] = 0; // thread_id
if (include_self)
shared_mem[numel_data + i] = 1; // reduce size
else
shared_mem[numel_data + i] = 0;
}
}
__syncthreads();
int64_t i, j, k; // The i, j, k here is the index of the 3 layers loop
// squeezed from the N layers loop.
/* tid = i * select_dim_size * outer_dim_size + j * outer_dim_size + k */
Expand Down Expand Up @@ -384,6 +373,7 @@ struct gpu_gather_scatter_functor {
int* shared_mem;
cudaMallocAsync(
reinterpret_cast<void**>(&shared_mem), shared_mem_size, stream);
cudaMemsetAsync(shared_mem, 0, shared_mem_size, stream);
ScatterAssignGPUKernel<tensor_t, index_t, func_t, is_scatter_like>
<<<grid, block, 0, stream>>>(self_data,
dim,
Expand All @@ -405,6 +395,14 @@ struct gpu_gather_scatter_functor {
int* shared_mem;
cudaMallocAsync(
reinterpret_cast<void**>(&shared_mem), shared_mem_size, stream);
cudaMemsetAsync(shared_mem, 0, sizeof(int) * self_size, stream);
if (include_self) {
int64_t grid_memset = (self_size * 2 + block - 1) / block;
CudaMemsetAsync<<<grid_memset, block, 0, stream>>>(
shared_mem, 1, shared_mem_size);
} else {
cudaMemsetAsync(shared_mem, 0, shared_mem_size, stream);
}
ScatterMeanGPUKernel<tensor_t, index_t, func_t, is_scatter_like>
<<<grid, block, 0, stream>>>(self_data,
dim,
Expand All @@ -429,6 +427,9 @@ struct gpu_gather_scatter_functor {
shared_mem_size = sizeof(int) * self_size;
cudaMallocAsync(
reinterpret_cast<void**>(&shared_mem), shared_mem_size, stream);
int64_t grid_memset = (self_size + block - 1) / block;
CudaMemsetAsync<<<grid_memset, block, 0, stream>>>(
shared_mem, index_size + 1, shared_mem_size);
}
GatherScatterGPUKernel<tensor_t, index_t, func_t, is_scatter_like>
<<<grid, block, shared_mem_size, stream>>>(self_data,
Expand Down Expand Up @@ -640,12 +641,6 @@ __global__ void ScatterMulInputGradGPUKernel(tensor_t* grad_data,
int* thread_ids) {
int tid = threadIdx.x + blockIdx.x * blockDim.x;
if (tid >= numel) return;
if (tid == 0) {
for (int i = 0; i < numel_grad; i++) {
thread_ids[i] = 0;
}
}
__syncthreads();
int64_t i, j, k;
i = tid / (select_dim_size * outer_dim_size);
int64_t remind = tid % (select_dim_size * outer_dim_size);
Expand Down Expand Up @@ -682,13 +677,6 @@ __global__ void ScatterMinMaxInputGradGPUKernel(tensor_t* grad_data,
int* shared_mem) {
int tid = threadIdx.x + blockIdx.x * blockDim.x;
if (tid >= numel) return;

if (tid == 0) {
for (int i = 0; i < numel_grad; i++) {
shared_mem[i] = 1; // number of elements
}
}
__syncthreads();
int64_t i, j, k;
i = tid / (select_dim_size * outer_dim_size);
int64_t remind = tid % (select_dim_size * outer_dim_size);
Expand Down Expand Up @@ -762,6 +750,7 @@ void gpu_scatter_mul_min_max_input_grad_kernel(phi::DenseTensor self,
int* shared_mem;
cudaMallocAsync(
reinterpret_cast<void**>(&shared_mem), shared_mem_size, stream);
cudaMemsetAsync(shared_mem, 0, shared_mem_size, stream);
ScatterMulInputGradGPUKernel<tensor_t, index_t>
<<<grid, block, 0, stream>>>(grad_data,
dim,
Expand All @@ -781,6 +770,9 @@ void gpu_scatter_mul_min_max_input_grad_kernel(phi::DenseTensor self,
int* shared_mem;
cudaMallocAsync(
reinterpret_cast<void**>(&shared_mem), shared_mem_size, stream);
int64_t grid_memset = (grad_size + block - 1) / block;
CudaMemsetAsync<<<grid_memset, block, 0, stream>>>(
shared_mem, 1, shared_mem_size);
ScatterMinMaxInputGradGPUKernel<tensor_t, index_t>
<<<grid, block, 0, stream>>>(grad_data,
dim,
Expand Down Expand Up @@ -816,13 +808,6 @@ __global__ void ScatterMeanInputGradGPUKernel(tensor_t* grad_data,
int* shared_mem) {
int tid = threadIdx.x + blockIdx.x * blockDim.x;
if (tid >= numel) return;
if (tid == 0) {
for (int i = 0; i < numel_grad; i++) {
shared_mem[i] = 0; // thread_ids
shared_mem[numel_grad + i] = 1; // number of elements
}
}
__syncthreads();
int64_t i, j, k;
i = tid / (select_dim_size * outer_dim_size);
int64_t remind = tid % (select_dim_size * outer_dim_size);
Expand Down Expand Up @@ -879,6 +864,10 @@ void gpu_scatter_mean_input_grad_kernel(phi::DenseTensor self,
int* shared_mem;
cudaMallocAsync(
reinterpret_cast<void**>(&shared_mem), shared_mem_size, stream);
cudaMemsetAsync(shared_mem, 0, sizeof(int) * grad_size, stream);
int64_t grid_memset = (grad_size + block - 1) / block;
CudaMemsetAsync<<<grid_memset, block, 0, stream>>>(
shared_mem + grad_size, 1, sizeof(int) * grad_size);
ScatterMeanInputGradGPUKernel<tensor_t, index_t>
<<<grid, block, 0, stream>>>(grad_data,
dim,
Expand Down Expand Up @@ -910,12 +899,6 @@ __global__ void ScatterValueGradGPUKernel(tensor_t* grad_data,
int tid = threadIdx.x + blockIdx.x * blockDim.x;
if (tid >= numel) return;

if (tid == 0) {
for (int i = 0; i < numel_data; i++) {
thread_ids[i] = 0;
}
}
__syncthreads();
int64_t i, j, k;
i = tid / (select_dim_size * outer_dim_size);
int64_t remind = tid % (select_dim_size * outer_dim_size);
Expand Down Expand Up @@ -975,6 +958,7 @@ void gpu_scatter_value_grad_kernel(phi::DenseTensor self,
int* shared_mem;
cudaMallocAsync(
reinterpret_cast<void**>(&shared_mem), shared_mem_size, stream);
cudaMemsetAsync(shared_mem, 0, shared_mem_size, stream);
ScatterValueGradGPUKernel<tensor_t, index_t>
<<<grid, block, 0, stream>>>(grad_data,
dim,
Expand Down Expand Up @@ -1005,20 +989,10 @@ __global__ void ScatterMeanValueGradGPUKernel(tensor_t* grad_data,
int64_t outer_dim_size_grad,
int64_t numel,
int64_t numel_self,
bool include_self,
int* shared_mem) {
int tid = threadIdx.x + blockIdx.x * blockDim.x;
if (tid >= numel) return;

if (tid == 0) {
for (int i = 0; i < numel_self; i++) {
if (include_self)
shared_mem[i] = 1; // number of elements
else
shared_mem[i] = 0;
}
}
__syncthreads();
int64_t i, j, k;
i = tid / (select_dim_size * outer_dim_size);
int64_t remind = tid % (select_dim_size * outer_dim_size);
Expand Down Expand Up @@ -1114,6 +1088,13 @@ void gpu_scatter_add_mean_value_grad_kernel(
int* shared_mem;
cudaMallocAsync(
reinterpret_cast<void**>(&shared_mem), shared_mem_size, stream);
if (include_self) {
int64_t grid_memset = (self_size + block - 1) / block;
CudaMemsetAsync<<<grid_memset, block, 0, stream>>>(
shared_mem, 1, shared_mem_size);
} else {
cudaMemsetAsync(shared_mem, 0, shared_mem_size, stream);
}
ScatterMeanValueGradGPUKernel<tensor_t, index_t>
<<<grid, block, 0, stream>>>(grad_data,
dim,
Expand All @@ -1127,7 +1108,6 @@ void gpu_scatter_add_mean_value_grad_kernel(
outer_dim_size_grad,
index_size,
self_size,
include_self,
shared_mem);
cudaFreeAsync(shared_mem, stream);
} else if (reduce == "add") {
Expand Down