#pragma once

#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 900) && CUDART_VERSION >= 12010
#define NVCC_SUPPORTS_MULTICAST 1
#endif

#include <ATen/ATen.h>

namespace c10d::symmetric_memory {

constexpr size_t max_num_threads_per_block = 1024;
constexpr size_t max_num_blocks = 8;

template <typename T>
__inline__ size_t get_alignment(T ptr_or_size) {
  auto val = reinterpret_cast<uintptr_t>(ptr_or_size);
  if (val % 16 == 0) {
    return 16;
  } else if (val % 8 == 0) {
    return 8;
  } else if (val % 4 == 0) {
    return 4;
  } else if (val % 2 == 0) {
    return 2;
  } else {
    return 1;
  }
}

template <>
__inline__ size_t get_alignment<size_t>(size_t size) {
  return get_alignment(reinterpret_cast<void*>(size));
}

__device__ __forceinline__ uint32_t
cas_sys(uint32_t* addr, uint32_t compare, uint32_t val) {
#if defined(USE_ROCM) || (defined(__CUDA_ARCH__) && (__CUDA_ARCH__ < 800))
  CUDA_KERNEL_ASSERT(false);
#else
  uint32_t old_val;
  asm volatile("atom.global.sys.cas.b32 %0, [%1], %2, %3;"
               : "=r"(old_val)
               : "l"(addr), "r"(compare), "r"(val)
               : "memory");
  return old_val;
#endif
}

__device__ __forceinline__ uint32_t
cas_release_sys(uint32_t* addr, uint32_t compare, uint32_t val) {
#if defined(USE_ROCM) || (defined(__CUDA_ARCH__) && (__CUDA_ARCH__ < 800))
  CUDA_KERNEL_ASSERT(false);
#else
  uint32_t old_val;
  asm volatile("atom.global.release.sys.cas.b32 %0, [%1], %2, %3;"
               : "=r"(old_val)
               : "l"(addr), "r"(compare), "r"(val)
               : "memory");
  return old_val;
#endif
}

__device__ __forceinline__ void release_signal(uint32_t* addr) {
  while (cas_release_sys(addr, 0, 1) != 0)
    ;
}

__device__ __forceinline__ void wait_signal(uint32_t* addr) {
  while (cas_sys(addr, 1, 0) != 1)
    ;
}

__device__ __forceinline__ uint32_t acquire_signal(uint32_t* addr) {
#if defined(USE_ROCM) || (defined(__CUDA_ARCH__) && (__CUDA_ARCH__ < 800))
  CUDA_KERNEL_ASSERT(false);
#else
  uint32_t val;
  asm volatile("ld.acquire.sys.global.u32 %0, [%1];"
               : "=r"(val)
               : "l"(addr)
               : "memory");
  return val;
#endif
}

// Perform a barrier to establish observation order between memory operations
// issued before and after the barrier.
__device__ __forceinline__ void barrier(
    uint32_t** signal_pads,
    size_t rank,
    size_t world_size) {
  if (threadIdx.x < world_size) {
    auto target_rank = threadIdx.x;
    release_signal(signal_pads[target_rank] + blockIdx.x * world_size + rank);
    wait_signal(signal_pads[rank] + blockIdx.x * world_size + target_rank);
  }
  __syncthreads();
}

// Perform a barrier and establish causality order between memory operations
// issued before the calling kernel on all devices and memory operations
// issued after this function by all thread in the calling kernel.
//
// NOTE: this function does NOT ensure that memory operations issues in the
// current kernel are visible to all threads in the current kernel.
//
// | mem ops (guaranteed to be visible by all threads at point T)
// | kernel K
// | +- mem ops (not guaranteed to be visible all threads at point T)
// | +- barrier_and_acquire_previous_kernel_writes()
// | +- point T
// v
__device__ __forceinline__ void barrier_and_acquire_previous_kernel_writes(
    uint32_t** signal_pads,
    size_t rank,
    size_t world_size) {
  if (threadIdx.x < world_size) {
    auto target_rank = threadIdx.x;
    release_signal(signal_pads[target_rank] + blockIdx.x * world_size + rank);
    wait_signal(signal_pads[rank] + blockIdx.x * world_size + target_rank);
  }
  __syncthreads();
  // At this point, we established observation order between memory operations
  // issued before and after the barrier. Now we convert the observation order
  // into causality order by having every thread acquire the signals released
  // by threads on peer devices. Due to the implicit synchronizes-with
  // relationships at task/kernel boundaries, acquiring the signal released by
  // thread T in kernel K transitively acquires memory operations issued prior
  // to kernel K.
  //
  // https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#memory-fence-interference
  for (size_t target_rank = 0; target_rank < world_size; ++target_rank) {
    acquire_signal(signal_pads[rank] + blockIdx.x * world_size + target_rank);
  }
}

template <bool Value, class... Args>
inline constexpr bool dependent_bool_value = Value;

template <class... Args>
inline constexpr bool dependent_false = dependent_bool_value<false, Args...>;

template <int Size>
union Vec;

template <>
union Vec<4> {
  uint16_t u16[2];
  uint32_t u32, as_scalar;
};

template <>
union Vec<8> {
  uint16_t u16[4];
  uint32_t u32[2];
  uint64_t u64, as_scalar;
};

template <>
union alignas(16) Vec<16> {
  uint16_t u16[8];
  uint32_t u32[4];
  uint64_t u64[2];
  uint4 u128, as_scalar;
};

template <typename T>
struct MultimemLdReduce {
  template <int Alignment>
  __device__ __inline__ Vec<Alignment> operator()(T* mc_ptr) {
    static_assert(dependent_false<T>);
  }
};

template <int Alignment, typename T>
__device__ __inline__ Vec<Alignment> multimem_ld_reduce_add(T* mc_ptr) {
  MultimemLdReduce<T> functor;
  return functor.template operator()<Alignment>(mc_ptr);
}

#if defined(USE_ROCM) || !defined(NVCC_SUPPORTS_MULTICAST)
#define SPECIALIZE_MULTIMEM_LD_REDUCE_VEC_32(type, asm_type)        \
  template <>                                                       \
  struct MultimemLdReduce<type> {                                   \
    template <int Alignment>                                        \
    __device__ __inline__ Vec<Alignment> operator()(type* mc_ptr) { \
      CUDA_KERNEL_ASSERT(false);                                    \
    }                                                               \
  };
#else
#define SPECIALIZE_MULTIMEM_LD_REDUCE_VEC_32(type, asm_type)                   \
  template <>                                                                  \
  struct MultimemLdReduce<type> {                                              \
    template <int Alignment>                                                   \
    __device__ __inline__ Vec<Alignment> operator()(type* mc_ptr) {            \
      Vec<Alignment> vec;                                                      \
      if constexpr (Alignment == 16) {                                         \
        asm("multimem.ld_reduce.relaxed.sys.global.add.v4." asm_type           \
            " {%0,%1,%2,%3}, [%4];"                                            \
            : "=r"(vec.u32[0]),                                                \
              "=r"(vec.u32[1]),                                                \
              "=r"(vec.u32[2]),                                                \
              "=r"(vec.u32[3])                                                 \
            : "l"(mc_ptr)                                                      \
            : "memory");                                                       \
      } else if constexpr (Alignment == 8) {                                   \
        asm("multimem.ld_reduce.relaxed.sys.global.add.v2." asm_type           \
            " {%0,%1}, [%2];"                                                  \
            : "=r"(vec.u32[0]), "=r"(vec.u32[1])                               \
            : "l"(mc_ptr)                                                      \
            : "memory");                                                       \
      } else if constexpr (Alignment == 4) {                                   \
        asm("multimem.ld_reduce.relaxed.sys.global.add." asm_type " %0, [%1];" \
            : "=r"(vec.u32)                                                    \
            : "l"(mc_ptr)                                                      \
            : "memory");                                                       \
      }                                                                        \
      return vec;                                                              \
    }                                                                          \
  };
#endif

SPECIALIZE_MULTIMEM_LD_REDUCE_VEC_32(at::BFloat16, "bf16x2");
SPECIALIZE_MULTIMEM_LD_REDUCE_VEC_32(float, "f32");

template <int Alignment, typename T>
__device__ __inline__ void multimem_st(T* mc_ptr, Vec<Alignment>& vec) {
#if defined(USE_ROCM) || !defined(NVCC_SUPPORTS_MULTICAST)
  CUDA_KERNEL_ASSERT(false);
#else
  if constexpr (Alignment == 16) {
    asm("multimem.st.relaxed.sys.global.v4.f32 [%0], {%1,%2,%3,%4};"
        :
        : "l"(mc_ptr),
          "r"(vec.u32[0]),
          "r"(vec.u32[1]),
          "r"(vec.u32[2]),
          "r"(vec.u32[3])
        : "memory");
  } else if constexpr (Alignment == 8) {
    asm("multimem.st.relaxed.sys.global.v2.f32 [%0], {%1,%2};"
        :
        : "l"(mc_ptr), "r"(vec.u32[0]), "r"(vec.u32[1])
        : "memory");
  } else if constexpr (Alignment == 4) {
    asm("multimem.st.relaxed.sys.global.f32 [%0], %1;"
        :
        : "l"(mc_ptr), "r"(vec.u32)
        : "memory");
  } else {
    static_assert(dependent_false<T>);
  }
#endif
}

} // namespace c10d::symmetric_memory
