poisson_kernel.cu

/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

#ifdef __NVCC__
#include <curand_kernel.h>
#endif
#ifdef __HIPCC__
#include <hiprand_kernel.h>
#endif

#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/backends/gpu/gpu_launch_config.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/funcs/for_range.h"
#include "paddle/phi/kernels/poisson_kernel.h"

namespace phi {

template <typename T>
__global__ void GetPoisson(
    const T* in, T* out, const int N, unsigned int seed, unsigned int offset) {
  CUDA_KERNEL_LOOP_TYPE(idx, N, int64_t) {
#ifdef __NVCC__
    curandStatePhilox4_32_10_t state;
    curand_init(seed, idx, offset, &state);
    out[idx] = static_cast<T>(curand_poisson(&state, in[idx]));
#elif __HIPCC__
    hiprandStatePhilox4_32_10_t state;
    hiprand_init(seed, idx, offset, &state);
    out[idx] = static_cast<T>(hiprand_poisson(&state, in[idx]));
#endif
  }
}

template <typename T, typename Context>
void PoissonKernel(const Context& ctx, const DenseTensor& x, DenseTensor* out) {
  const T* x_data = x.data<T>();
  T* out_data = ctx.template Alloc<T>(out);
  const int size = x.numel();
  const int kMaxBlockDim = 256;

  int block_size = std::min(kMaxBlockDim, ctx.GetMaxThreadsPerBlock());
  dim3 dim_block(block_size);
  dim3 dim_grid((size + block_size - 1) / block_size);
  phi::backends::gpu::LimitGridDim(ctx, &dim_grid);

  auto gen_cuda = ctx.GetGenerator();
  auto seed_offset = gen_cuda->IncrementOffset(20);
  uint64_t seed = seed_offset.first;
  uint64_t offset = seed_offset.second;
  GetPoisson<T><<<dim_grid, dim_block>>>(x_data, out_data, size, seed, offset);
}

}  // namespace phi

PD_REGISTER_KERNEL(
    poisson, GPU, ALL_LAYOUT, phi::PoissonKernel, float, double) {}