cutlass/tools/util/reference/device/tensor_foreach.h

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#pragma once

#include <stdexcept>
#include "cutlass/cutlass.h"
#include "tools/util/reference/device/kernel/tensor_foreach.h"

namespace cutlass  {
namespace reference {
namespace device {

///////////////////////////////////////////////////////////////////////////////////////////////////

/// Launches a kernel for each element in a tensor's index space.
template <typename Func, int Rank, typename Params>
struct TensorForEach {

  /// Constructor performs the operation.
  TensorForEach(Coord<Rank> size, Params params = Params(), int grid_size = 0, int block_size = 0) {

    if (!grid_size || !block_size) {

      // if grid_size or block_size are zero, query occupancy using the CUDA Occupancy API
      cudaError_t result = cudaOccupancyMaxPotentialBlockSize(
        &grid_size,
        &block_size,
        reinterpret_cast<void const *>(kernel::TensorForEach<Func, Rank, Params>));

      if (result != cudaSuccess) {
        throw std::runtime_error("Failed to query occupancy.");
      }

      // Limit block size. This has the effect of increasing the number of items processed by a
      // single thread and reduces the impact of initialization overhead.
      block_size = (block_size < 128 ? block_size : 128);
    }

    dim3 grid(grid_size, 1, 1);
    dim3 block(block_size, 1, 1);

    kernel::TensorForEach<Func, Rank, Params><<< grid, block >>>(size, params);
  }
};

///////////////////////////////////////////////////////////////////////////////////////////////////

} // namespace device
} // namespace reference
} // namesace cutlass