/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions
 * are met:
 *  * Redistributions of source code must retain the above copyright
 *    notice, this list of conditions and the following disclaimer.
 *  * Redistributions in binary form must reproduce the above copyright
 *    notice, this list of conditions and the following disclaimer in the
 *    documentation and/or other materials provided with the distribution.
 *  * Neither the name of NVIDIA CORPORATION nor the names of its
 *    contributors may be used to endorse or promote products derived
 *    from this software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
 * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
 * PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
 * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
 * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
 * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
 * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
 * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 */

#include <helper_cuda.h>
#include <math.h>

#if defined(__APPLE__) || defined(MACOSX)
#pragma clang diagnostic ignored "-Wdeprecated-declarations"
#include <GLUT/glut.h>
#else
#include <GL/freeglut.h>
#endif

// CUDA standard includes
#include <cuda_runtime.h>
#include <cuda_gl_interop.h>

#include <cooperative_groups.h>

namespace cg = cooperative_groups;

#include "bodysystem.h"

__constant__ float softeningSquared;
__constant__ double softeningSquared_fp64;

cudaError_t setSofteningSquared(float softeningSq) {
  return cudaMemcpyToSymbol(softeningSquared, &softeningSq, sizeof(float), 0,
                            cudaMemcpyHostToDevice);
}

cudaError_t setSofteningSquared(double softeningSq) {
  return cudaMemcpyToSymbol(softeningSquared_fp64, &softeningSq, sizeof(double),
                            0, cudaMemcpyHostToDevice);
}

template <class T>
struct SharedMemory {
  __device__ inline operator T *() {
    extern __shared__ int __smem[];
    return (T *)__smem;
  }

  __device__ inline operator const T *() const {
    extern __shared__ int __smem[];
    return (T *)__smem;
  }
};

template <typename T>
__device__ T rsqrt_T(T x) {
  return rsqrt(x);
}

template <>
__device__ float rsqrt_T<float>(float x) {
  return rsqrtf(x);
}

template <>
__device__ double rsqrt_T<double>(double x) {
  return rsqrt(x);
}

// Macros to simplify shared memory addressing
#define SX(i) sharedPos[i + blockDim.x * threadIdx.y]
// This macro is only used when multithreadBodies is true (below)
#define SX_SUM(i, j) sharedPos[i + blockDim.x * j]

template <typename T>
__device__ T getSofteningSquared() {
  return softeningSquared;
}
template <>
__device__ double getSofteningSquared<double>() {
  return softeningSquared_fp64;
}

template <typename T>
struct DeviceData {
  T *dPos[2];  // mapped host pointers
  T *dVel;
  cudaEvent_t event;
  unsigned int offset;
  unsigned int numBodies;
};

template <typename T>
__device__ typename vec3<T>::Type bodyBodyInteraction(
    typename vec3<T>::Type ai, typename vec4<T>::Type bi,
    typename vec4<T>::Type bj) {
  typename vec3<T>::Type r;

  // r_ij  [3 FLOPS]
  r.x = bj.x - bi.x;
  r.y = bj.y - bi.y;
  r.z = bj.z - bi.z;

  // distSqr = dot(r_ij, r_ij) + EPS^2  [6 FLOPS]
  T distSqr = r.x * r.x + r.y * r.y + r.z * r.z;
  distSqr += getSofteningSquared<T>();

  // invDistCube =1/distSqr^(3/2)  [4 FLOPS (2 mul, 1 sqrt, 1 inv)]
  T invDist = rsqrt_T(distSqr);
  T invDistCube = invDist * invDist * invDist;

  // s = m_j * invDistCube [1 FLOP]
  T s = bj.w * invDistCube;

  // a_i =  a_i + s * r_ij [6 FLOPS]
  ai.x += r.x * s;
  ai.y += r.y * s;
  ai.z += r.z * s;

  return ai;
}

template <typename T>
__device__ typename vec3<T>::Type computeBodyAccel(
    typename vec4<T>::Type bodyPos, typename vec4<T>::Type *positions,
    int numTiles, cg::thread_block cta) {
  typename vec4<T>::Type *sharedPos = SharedMemory<typename vec4<T>::Type>();

  typename vec3<T>::Type acc = {0.0f, 0.0f, 0.0f};

  for (int tile = 0; tile < numTiles; tile++) {
    sharedPos[threadIdx.x] = positions[tile * blockDim.x + threadIdx.x];

    cg::sync(cta);

// This is the "tile_calculation" from the GPUG3 article.
#pragma unroll 128

    for (unsigned int counter = 0; counter < blockDim.x; counter++) {
      acc = bodyBodyInteraction<T>(acc, bodyPos, sharedPos[counter]);
    }

    cg::sync(cta);
  }

  return acc;
}

template <typename T>
__global__ void integrateBodies(typename vec4<T>::Type *__restrict__ newPos,
                                typename vec4<T>::Type *__restrict__ oldPos,
                                typename vec4<T>::Type *vel,
                                unsigned int deviceOffset,
                                unsigned int deviceNumBodies, float deltaTime,
                                float damping, int numTiles) {
  // Handle to thread block group
  cg::thread_block cta = cg::this_thread_block();
  int index = blockIdx.x * blockDim.x + threadIdx.x;

  if (index >= deviceNumBodies) {
    return;
  }

  typename vec4<T>::Type position = oldPos[deviceOffset + index];

  typename vec3<T>::Type accel =
      computeBodyAccel<T>(position, oldPos, numTiles, cta);

  // acceleration = force / mass;
  // new velocity = old velocity + acceleration * deltaTime
  // note we factor out the body's mass from the equation, here and in
  // bodyBodyInteraction
  // (because they cancel out).  Thus here force == acceleration
  typename vec4<T>::Type velocity = vel[deviceOffset + index];

  velocity.x += accel.x * deltaTime;
  velocity.y += accel.y * deltaTime;
  velocity.z += accel.z * deltaTime;

  velocity.x *= damping;
  velocity.y *= damping;
  velocity.z *= damping;

  // new position = old position + velocity * deltaTime
  position.x += velocity.x * deltaTime;
  position.y += velocity.y * deltaTime;
  position.z += velocity.z * deltaTime;

  // store new position and velocity
  newPos[deviceOffset + index] = position;
  vel[deviceOffset + index] = velocity;
}

template <typename T>
void integrateNbodySystem(DeviceData<T> *deviceData,
                          cudaGraphicsResource **pgres,
                          unsigned int currentRead, float deltaTime,
                          float damping, unsigned int numBodies,
                          unsigned int numDevices, int blockSize,
                          bool bUsePBO) {
  if (bUsePBO) {
    checkCudaErrors(cudaGraphicsResourceSetMapFlags(
        pgres[currentRead], cudaGraphicsMapFlagsReadOnly));
    checkCudaErrors(cudaGraphicsResourceSetMapFlags(
        pgres[1 - currentRead], cudaGraphicsMapFlagsWriteDiscard));
    checkCudaErrors(cudaGraphicsMapResources(2, pgres, 0));
    size_t bytes;
    checkCudaErrors(cudaGraphicsResourceGetMappedPointer(
        (void **)&(deviceData[0].dPos[currentRead]), &bytes,
        pgres[currentRead]));
    checkCudaErrors(cudaGraphicsResourceGetMappedPointer(
        (void **)&(deviceData[0].dPos[1 - currentRead]), &bytes,
        pgres[1 - currentRead]));
  }

  for (unsigned int dev = 0; dev != numDevices; dev++) {
    if (numDevices > 1) {
      cudaSetDevice(dev);
    }

    int numBlocks = (deviceData[dev].numBodies + blockSize - 1) / blockSize;
    int numTiles = (numBodies + blockSize - 1) / blockSize;
    int sharedMemSize = blockSize * 4 * sizeof(T);  // 4 floats for pos

    integrateBodies<T><<<numBlocks, blockSize, sharedMemSize>>>(
        (typename vec4<T>::Type *)deviceData[dev].dPos[1 - currentRead],
        (typename vec4<T>::Type *)deviceData[dev].dPos[currentRead],
        (typename vec4<T>::Type *)deviceData[dev].dVel, deviceData[dev].offset,
        deviceData[dev].numBodies, deltaTime, damping, numTiles);

    if (numDevices > 1) {
      checkCudaErrors(cudaEventRecord(deviceData[dev].event));
      // MJH: Hack on older driver versions to force kernel launches to flush!
      cudaStreamQuery(0);
    }

    // check if kernel invocation generated an error
    getLastCudaError("Kernel execution failed");
  }

  if (numDevices > 1) {
    for (unsigned int dev = 0; dev < numDevices; dev++) {
      checkCudaErrors(cudaEventSynchronize(deviceData[dev].event));
    }
  }

  if (bUsePBO) {
    checkCudaErrors(cudaGraphicsUnmapResources(2, pgres, 0));
  }
}

// Explicit specializations needed to generate code
template void integrateNbodySystem<float>(DeviceData<float> *deviceData,
                                          cudaGraphicsResource **pgres,
                                          unsigned int currentRead,
                                          float deltaTime, float damping,
                                          unsigned int numBodies,
                                          unsigned int numDevices,
                                          int blockSize, bool bUsePBO);

template void integrateNbodySystem<double>(DeviceData<double> *deviceData,
                                           cudaGraphicsResource **pgres,
                                           unsigned int currentRead,
                                           float deltaTime, float damping,
                                           unsigned int numBodies,
                                           unsigned int numDevices,
                                           int blockSize, bool bUsePBO);
