/* 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.
 */

#ifndef _BOXFILTER_KERNEL_CH_
#define _BOXFILTER_KERNEL_CH_

#include <helper_math.h>
#include <helper_functions.h>

cudaTextureObject_t tex;
cudaTextureObject_t texTempArray;
cudaTextureObject_t rgbaTex;
cudaTextureObject_t rgbaTexTempArray;
cudaArray *d_array, *d_tempArray;

////////////////////////////////////////////////////////////////////////////////
// These are CUDA Helper functions

// This will output the proper CUDA error strings in the event that a CUDA host
// call returns an error
#define checkCudaErrors(err) __checkCudaErrors(err, __FILE__, __LINE__)

inline void __checkCudaErrors(cudaError err, const char *file, const int line) {
  if (cudaSuccess != err) {
    fprintf(stderr, "%s(%i) : CUDA Runtime API error %d: %s.\n", file, line,
            (int)err, cudaGetErrorString(err));
    exit(EXIT_FAILURE);
  }
}

/*
  Perform a fast box filter using the sliding window method.

  As the kernel moves from left to right, we add in the contribution of the
  new sample on the right, and subtract the value of the exiting sample on the
  left. This only requires 2 adds and a mul per output value, independent of the
  filter radius. The box filter is separable, so to perform a 2D box filter we
  perform the filter in the x direction, followed by the same filter in the y
  direction. Applying multiple iterations of the box filter converges towards a
  Gaussian blur. Using CUDA, rows or columns of the image are processed in
  parallel. This version duplicates edge pixels.

  Note that the x (row) pass suffers from uncoalesced global memory reads,
  since each thread is reading from a different row. For this reason it is
  better to use texture lookups for the x pass.
  The y (column) pass is perfectly coalesced.

  Parameters
  id - pointer to input data in global memory
  od - pointer to output data in global memory
  w  - image width
  h  - image height
  r  - filter radius

  e.g. for r = 2, w = 8:

  0 1 2 3 4 5 6 7
  x - -
  - x - -
  - - x - -
    - - x - -
      - - x - -
        - - x - -
          - - x -
            - - x
*/

// process row
__device__ void d_boxfilter_x(float *id, float *od, int w, int h, int r) {
  float scale = 1.0f / (float)((r << 1) + 1);

  float t;
  // do left edge
  t = id[0] * r;

  for (int x = 0; x < (r + 1); x++) {
    t += id[x];
  }

  od[0] = t * scale;

  for (int x = 1; x < (r + 1); x++) {
    t += id[x + r];
    t -= id[0];
    od[x] = t * scale;
  }

  // main loop
  for (int x = (r + 1); x < w - r; x++) {
    t += id[x + r];
    t -= id[x - r - 1];
    od[x] = t * scale;
  }

  // do right edge
  for (int x = w - r; x < w; x++) {
    t += id[w - 1];
    t -= id[x - r - 1];
    od[x] = t * scale;
  }
}

// process column
__device__ void d_boxfilter_y(float *id, float *od, int w, int h, int r) {
  float scale = 1.0f / (float)((r << 1) + 1);

  float t;
  // do left edge
  t = id[0] * r;

  for (int y = 0; y < (r + 1); y++) {
    t += id[y * w];
  }

  od[0] = t * scale;

  for (int y = 1; y < (r + 1); y++) {
    t += id[(y + r) * w];
    t -= id[0];
    od[y * w] = t * scale;
  }

  // main loop
  for (int y = (r + 1); y < (h - r); y++) {
    t += id[(y + r) * w];
    t -= id[((y - r) * w) - w];
    od[y * w] = t * scale;
  }

  // do right edge
  for (int y = h - r; y < h; y++) {
    t += id[(h - 1) * w];
    t -= id[((y - r) * w) - w];
    od[y * w] = t * scale;
  }
}

__global__ void d_boxfilter_x_global(float *id, float *od, int w, int h,
                                     int r) {
  unsigned int y = blockIdx.x * blockDim.x + threadIdx.x;
  d_boxfilter_x(&id[y * w], &od[y * w], w, h, r);
}

__global__ void d_boxfilter_y_global(float *id, float *od, int w, int h,
                                     int r) {
  unsigned int x = blockIdx.x * blockDim.x + threadIdx.x;
  d_boxfilter_y(&id[x], &od[x], w, h, r);
}

// texture version
// texture fetches automatically clamp to edge of image
__global__ void d_boxfilter_x_tex(float *od, int w, int h, int r,
                                  cudaTextureObject_t tex) {
  float scale = 1.0f / (float)((r << 1) + 1);
  unsigned int y = blockIdx.x * blockDim.x + threadIdx.x;

  float t = 0.0f;

  for (int x = -r; x <= r; x++) {
    t += tex2D<float>(tex, x, y);
  }

  od[y * w] = t * scale;

  for (int x = 1; x < w; x++) {
    t += tex2D<float>(tex, x + r, y);
    t -= tex2D<float>(tex, x - r - 1, y);
    od[y * w + x] = t * scale;
  }
}

__global__ void d_boxfilter_y_tex(float *od, int w, int h, int r,
                                  cudaTextureObject_t tex) {
  float scale = 1.0f / (float)((r << 1) + 1);
  unsigned int x = blockIdx.x * blockDim.x + threadIdx.x;

  float t = 0.0f;

  for (int y = -r; y <= r; y++) {
    t += tex2D<float>(tex, x, y);
  }

  od[x] = t * scale;

  for (int y = 1; y < h; y++) {
    t += tex2D<float>(tex, x, y + r);
    t -= tex2D<float>(tex, x, y - r - 1);
    od[y * w + x] = t * scale;
  }
}

// RGBA version
// reads from 32-bit unsigned int array holding 8-bit RGBA

// convert floating point rgba color to 32-bit integer
__device__ unsigned int rgbaFloatToInt(float4 rgba) {
  rgba.x = __saturatef(rgba.x);  // clamp to [0.0, 1.0]
  rgba.y = __saturatef(rgba.y);
  rgba.z = __saturatef(rgba.z);
  rgba.w = __saturatef(rgba.w);
  return ((unsigned int)(rgba.w * 255.0f) << 24) |
         ((unsigned int)(rgba.z * 255.0f) << 16) |
         ((unsigned int)(rgba.y * 255.0f) << 8) |
         ((unsigned int)(rgba.x * 255.0f));
}

__device__ float4 rgbaIntToFloat(unsigned int c) {
  float4 rgba;
  rgba.x = (c & 0xff) * 0.003921568627f;          //  /255.0f;
  rgba.y = ((c >> 8) & 0xff) * 0.003921568627f;   //  /255.0f;
  rgba.z = ((c >> 16) & 0xff) * 0.003921568627f;  //  /255.0f;
  rgba.w = ((c >> 24) & 0xff) * 0.003921568627f;  //  /255.0f;
  return rgba;
}

// row pass using texture lookups
__global__ void d_boxfilter_rgba_x(unsigned int *od, int w, int h, int r,
                                   cudaTextureObject_t rgbaTex) {
  float scale = 1.0f / (float)((r << 1) + 1);
  unsigned int y = blockIdx.x * blockDim.x + threadIdx.x;

  // as long as address is always less than height, we do work
  if (y < h) {
    float4 t = make_float4(0.0f);

    for (int x = -r; x <= r; x++) {
      t += tex2D<float4>(rgbaTex, x, y);
    }

    od[y * w] = rgbaFloatToInt(t * scale);

    for (int x = 1; x < w; x++) {
      t += tex2D<float4>(rgbaTex, x + r, y);
      t -= tex2D<float4>(rgbaTex, x - r - 1, y);
      od[y * w + x] = rgbaFloatToInt(t * scale);
    }
  }
}

// column pass using coalesced global memory reads
__global__ void d_boxfilter_rgba_y(unsigned int *id, unsigned int *od, int w,
                                   int h, int r) {
  unsigned int x = blockIdx.x * blockDim.x + threadIdx.x;
  id = &id[x];
  od = &od[x];

  float scale = 1.0f / (float)((r << 1) + 1);

  float4 t;
  // do left edge
  t = rgbaIntToFloat(id[0]) * r;

  for (int y = 0; y < (r + 1); y++) {
    t += rgbaIntToFloat(id[y * w]);
  }

  od[0] = rgbaFloatToInt(t * scale);

  for (int y = 1; y < (r + 1); y++) {
    t += rgbaIntToFloat(id[(y + r) * w]);
    t -= rgbaIntToFloat(id[0]);
    od[y * w] = rgbaFloatToInt(t * scale);
  }

  // main loop
  for (int y = (r + 1); y < (h - r); y++) {
    t += rgbaIntToFloat(id[(y + r) * w]);
    t -= rgbaIntToFloat(id[((y - r) * w) - w]);
    od[y * w] = rgbaFloatToInt(t * scale);
  }

  // do right edge
  for (int y = h - r; y < h; y++) {
    t += rgbaIntToFloat(id[(h - 1) * w]);
    t -= rgbaIntToFloat(id[((y - r) * w) - w]);
    od[y * w] = rgbaFloatToInt(t * scale);
  }
}

extern "C" void initTexture(int width, int height, void *pImage, bool useRGBA) {
  // copy image data to array
  cudaChannelFormatDesc channelDesc;
  if (useRGBA) {
    channelDesc =
        cudaCreateChannelDesc(8, 8, 8, 8, cudaChannelFormatKindUnsigned);
  } else {
    channelDesc =
        cudaCreateChannelDesc(32, 0, 0, 0, cudaChannelFormatKindFloat);
  }
  checkCudaErrors(cudaMallocArray(&d_array, &channelDesc, width, height));

  size_t bytesPerElem = (useRGBA ? sizeof(uchar4) : sizeof(float));
  checkCudaErrors(cudaMemcpy2DToArray(
      d_array, 0, 0, pImage, width * bytesPerElem, width * bytesPerElem, height,
      cudaMemcpyHostToDevice));

  checkCudaErrors(cudaMallocArray(&d_tempArray, &channelDesc, width, height));

  // set texture parameters
  cudaResourceDesc texRes;
  memset(&texRes, 0, sizeof(cudaResourceDesc));

  texRes.resType = cudaResourceTypeArray;
  texRes.res.array.array = d_array;

  cudaTextureDesc texDescr;
  memset(&texDescr, 0, sizeof(cudaTextureDesc));

  texDescr.normalizedCoords = false;
  texDescr.filterMode = cudaFilterModeLinear;
  texDescr.addressMode[0] = cudaAddressModeWrap;
  texDescr.addressMode[1] = cudaAddressModeWrap;
  texDescr.readMode = cudaReadModeNormalizedFloat;

  checkCudaErrors(cudaCreateTextureObject(&rgbaTex, &texRes, &texDescr, NULL));

  memset(&texRes, 0, sizeof(cudaResourceDesc));

  texRes.resType = cudaResourceTypeArray;
  texRes.res.array.array = d_tempArray;

  memset(&texDescr, 0, sizeof(cudaTextureDesc));

  texDescr.normalizedCoords = false;
  texDescr.filterMode = cudaFilterModeLinear;
  texDescr.addressMode[0] = cudaAddressModeClamp;
  texDescr.addressMode[1] = cudaAddressModeClamp;
  texDescr.readMode = cudaReadModeNormalizedFloat;

  checkCudaErrors(
      cudaCreateTextureObject(&rgbaTexTempArray, &texRes, &texDescr, NULL));

  memset(&texRes, 0, sizeof(cudaResourceDesc));

  texRes.resType = cudaResourceTypeArray;
  texRes.res.array.array = d_array;

  memset(&texDescr, 0, sizeof(cudaTextureDesc));

  texDescr.normalizedCoords = true;
  texDescr.filterMode = cudaFilterModePoint;
  texDescr.addressMode[0] = cudaAddressModeWrap;
  texDescr.addressMode[1] = cudaAddressModeWrap;
  texDescr.readMode = cudaReadModeElementType;

  checkCudaErrors(cudaCreateTextureObject(&tex, &texRes, &texDescr, NULL));

  memset(&texRes, 0, sizeof(cudaResourceDesc));

  texRes.resType = cudaResourceTypeArray;
  texRes.res.array.array = d_tempArray;

  memset(&texDescr, 0, sizeof(cudaTextureDesc));

  texDescr.normalizedCoords = true;
  texDescr.filterMode = cudaFilterModePoint;
  texDescr.addressMode[0] = cudaAddressModeWrap;
  texDescr.addressMode[1] = cudaAddressModeWrap;
  texDescr.readMode = cudaReadModeElementType;

  checkCudaErrors(
      cudaCreateTextureObject(&texTempArray, &texRes, &texDescr, NULL));
}

extern "C" void freeTextures() {
  checkCudaErrors(cudaDestroyTextureObject(tex));
  checkCudaErrors(cudaDestroyTextureObject(texTempArray));
  checkCudaErrors(cudaDestroyTextureObject(rgbaTex));
  checkCudaErrors(cudaDestroyTextureObject(rgbaTexTempArray));
  checkCudaErrors(cudaFreeArray(d_array));
  checkCudaErrors(cudaFreeArray(d_tempArray));
}

/*
    Perform 2D box filter on image using CUDA

    Parameters:
    d_src  - pointer to input image in device memory
    d_temp - pointer to temporary storage in device memory
    d_dest - pointer to destination image in device memory
    width  - image width
    height - image height
    radius - filter radius
    iterations - number of iterations

*/
extern "C" double boxFilter(float *d_src, float *d_temp, float *d_dest,
                            int width, int height, int radius, int iterations,
                            int nthreads, StopWatchInterface *timer) {
  // var for kernel timing
  double dKernelTime = 0.0;

  // sync host and start computation timer_kernel
  checkCudaErrors(cudaDeviceSynchronize());

  for (int i = 0; i < iterations; i++) {
    sdkResetTimer(&timer);
    // use texture for horizontal pass
    if (iterations > 1) {
      d_boxfilter_x_tex<<<height / nthreads, nthreads, 0>>>(
          d_temp, width, height, radius, texTempArray);
    } else {
      d_boxfilter_x_tex<<<height / nthreads, nthreads, 0>>>(
          d_temp, width, height, radius, tex);
    }

    d_boxfilter_y_global<<<width / nthreads, nthreads, 0>>>(
        d_temp, d_dest, width, height, radius);

    // sync host and stop computation timer_kernel
    checkCudaErrors(cudaDeviceSynchronize());
    dKernelTime += sdkGetTimerValue(&timer);

    if (iterations > 1) {
      // copy result back from global memory to array
      checkCudaErrors(cudaMemcpy2DToArray(
          d_tempArray, 0, 0, d_dest, width * sizeof(float),
          width * sizeof(float), height, cudaMemcpyDeviceToDevice));
    }
  }

  return ((dKernelTime / 1000.) / (double)iterations);
}

// RGBA version
extern "C" double boxFilterRGBA(unsigned int *d_src, unsigned int *d_temp,
                                unsigned int *d_dest, int width, int height,
                                int radius, int iterations, int nthreads,
                                StopWatchInterface *timer) {
  // var for kernel computation timing
  double dKernelTime;

  for (int i = 0; i < iterations; i++) {
    // sync host and start kernel computation timer_kernel
    dKernelTime = 0.0;
    checkCudaErrors(cudaDeviceSynchronize());
    sdkResetTimer(&timer);

    // use texture for horizontal pass
    if (iterations > 1) {
      d_boxfilter_rgba_x<<<height / nthreads, nthreads, 0>>>(
          d_temp, width, height, radius, rgbaTexTempArray);
    } else {
      d_boxfilter_rgba_x<<<height / nthreads, nthreads, 0>>>(
          d_temp, width, height, radius, rgbaTex);
    }

    d_boxfilter_rgba_y<<<width / nthreads, nthreads, 0>>>(d_temp, d_dest, width,
                                                          height, radius);

    // sync host and stop computation timer_kernel
    checkCudaErrors(cudaDeviceSynchronize());
    dKernelTime += sdkGetTimerValue(&timer);

    if (iterations > 1) {
      // copy result back from global memory to array
      checkCudaErrors(cudaMemcpy2DToArray(
          d_tempArray, 0, 0, d_dest, width * sizeof(unsigned int),
          width * sizeof(unsigned int), height, cudaMemcpyDeviceToDevice));
    }
  }

  return ((dKernelTime / 1000.) / (double)iterations);
}

#endif  // #ifndef _BOXFILTER_KERNEL_H_
