torch/include/ATen/cuda/detail/KernelUtils.h

#pragma once

#include <limits>

namespace at { namespace cuda { namespace detail {

// CUDA: grid stride looping
//
// int64_t _i_n_d_e_x specifically prevents overflow in the loop increment.
// If input.numel() < INT_MAX, _i_n_d_e_x < INT_MAX, except after the final
// iteration of the loop where _i_n_d_e_x += blockDim.x * gridDim.x can be
// greater than INT_MAX.  But in that case _i_n_d_e_x >= n, so there are no
// further iterations and the overflowed value in i=_i_n_d_e_x is not used.
#define CUDA_KERNEL_LOOP_TYPE(i, n, index_type)                         \
  int64_t _i_n_d_e_x = blockIdx.x * blockDim.x + threadIdx.x;           \
  for (index_type i=_i_n_d_e_x; _i_n_d_e_x < (n); _i_n_d_e_x+=blockDim.x * gridDim.x, i=_i_n_d_e_x)

#define CUDA_KERNEL_LOOP(i, n) CUDA_KERNEL_LOOP_TYPE(i, n, int)


// Use 1024 threads per block, which requires cuda sm_2x or above
constexpr int CUDA_NUM_THREADS = 1024;

// CUDA: number of blocks for threads.
inline int GET_BLOCKS(const int64_t N, const int64_t max_threads_per_block=CUDA_NUM_THREADS) {
  TORCH_INTERNAL_ASSERT(N > 0, "CUDA kernel launch blocks must be positive, but got N=", N);
  constexpr int64_t max_int = std::numeric_limits<int>::max();

  // Round up division for positive number that cannot cause integer overflow
  auto block_num = (N - 1) / max_threads_per_block + 1;
  TORCH_INTERNAL_ASSERT(block_num <= max_int, "Can't schedule too many blocks on CUDA device");

  return static_cast<int>(block_num);
}

}}}  // namespace at::cuda::detail