#pragma once #include #include namespace at::cuda::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::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(block_num); } } // namespace at::cuda::detail