/*
 * Copyright (c) 2017, NVIDIA CORPORATION.
 *
 * 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.
 *
 * This source code refers to https://github.com/rapidsai/cudf
 * and is licensed under the license found in the LICENSE file
 * in the root directory of this source tree.
 */

#ifndef MANAGED_ALLOCATOR_CUH 
#define MANAGED_ALLOCATOR_CUH

#include <new>

template <class T>
struct managed_allocator {
  typedef T value_type;

  managed_allocator() = default;

  template <class U>
  constexpr managed_allocator(const managed_allocator<U>&) noexcept {}

  T* allocate(std::size_t n) const {
    T* ptr = 0;
    cudaError_t result = cudaMallocManaged(&ptr, n * sizeof(T));
    if (cudaSuccess != result || nullptr == ptr) {
      std::cerr << "ERROR: CUDA Runtime call in line " << __LINE__ << "of file " << __FILE__
                << " failed with " << cudaGetErrorString(result) << " (" << result << ") "
                << " Attempted to allocate: " << n * sizeof(T) << " bytes.\n";
      throw std::bad_alloc();
    }
    return ptr;
  }
  void deallocate(T* p, std::size_t) const { cudaFree(p); }
};

template <class T, class U>
bool operator==(const managed_allocator<T>&, const managed_allocator<U>&) {
  return true;
}
template <class T, class U>
bool operator!=(const managed_allocator<T>&, const managed_allocator<U>&) {
  return false;
}

#endif
