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 * 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.
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/*
  Recursive Gaussian filter
  sgreen 8/1/08

  This code sample implements a Gaussian blur using Deriche's recursive method:
  http://citeseer.ist.psu.edu/deriche93recursively.html

  This is similar to the box filter sample in the SDK, but it uses the previous
  outputs of the filter as well as the previous inputs. This is also known as an
  IIR (infinite impulse response) filter, since its response to an input impulse
  can last forever.

  The main advantage of this method is that the execution time is independent of
  the filter width.

  The GPU processes columns of the image in parallel. To avoid uncoalesced reads
  for the row pass we transpose the image and then transpose it back again
  afterwards.

  The implementation is based on code from the CImg library:
  http://cimg.sourceforge.net/
  Thanks to David Tschumperl� and all the CImg contributors!
*/

#pragma warning(disable : 4819)

// OpenGL Graphics includes
#include <helper_gl.h>
#if defined(__APPLE__) || defined(MACOSX)
#pragma clang diagnostic ignored "-Wdeprecated-declarations"
#include <GLUT/glut.h>
#ifndef glutCloseFunc
#define glutCloseFunc glutWMCloseFunc
#endif
#else
#include <GL/freeglut.h>
#endif

// CUDA includes and interop headers
#include <cuda_runtime.h>
#include <cuda_gl_interop.h>

// CUDA utilities and system includes
#include <helper_functions.h>
#include <helper_cuda.h>  // includes cuda.h and cuda_runtime_api.h

// Includes
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>

#define MAX(a, b) ((a > b) ? a : b)

#define USE_SIMPLE_FILTER 0

#define MAX_EPSILON_ERROR 5.0f
#define THRESHOLD 0.15f

// Define the files that are to be save and the reference images for validation
const char *sOriginal[] = {"lena_10.ppm", "lena_14.ppm", "lena_18.ppm",
                           "lena_22.ppm", NULL};

const char *sReference[] = {"ref_10.ppm", "ref_14.ppm", "ref_18.ppm",
                            "ref_22.ppm", NULL};

const char *image_filename = "lena.ppm";
float sigma = 10.0f;
int order = 0;
int nthreads = 64;  // number of threads per block

unsigned int width, height;
unsigned int *h_img = NULL;
unsigned int *d_img = NULL;
unsigned int *d_temp = NULL;

GLuint pbo = 0;    // OpenGL pixel buffer object
GLuint texid = 0;  // texture

cudaGraphicsResource_t cuda_vbo_resource;

StopWatchInterface *timer = 0;

// Auto-Verification Code
const int frameCheckNumber = 4;
int fpsCount = 0;  // FPS count for averaging
int fpsLimit = 1;  // FPS limit for sampling
unsigned int frameCount = 0;

int *pArgc = NULL;
char **pArgv = NULL;

bool runBenchmark = false;

const char *sSDKsample = "CUDA Recursive Gaussian";

extern "C" void transpose(unsigned int *d_src, unsigned int *d_dest,
                          unsigned int width, int height);

extern "C" void gaussianFilterRGBA(unsigned int *d_src, unsigned int *d_dest,
                                   unsigned int *d_temp, int width, int height,
                                   float sigma, int order, int nthreads);

void cleanup();

void computeFPS() {
  frameCount++;
  fpsCount++;

  if (fpsCount == fpsLimit) {
    char fps[256];
    float ifps = 1.f / (sdkGetAverageTimerValue(&timer) / 1000.f);
    sprintf(fps, "%s (sigma=%4.2f): %3.1f fps", sSDKsample, sigma, ifps);

    glutSetWindowTitle(fps);
    fpsCount = 0;

    fpsLimit = ftoi(MAX(ifps, 1.f));
    sdkResetTimer(&timer);
  }
}

// display results using OpenGL
void display() {
  sdkStartTimer(&timer);

  // execute filter, writing results to pbo
  unsigned int *d_result;
  checkCudaErrors(cudaGraphicsMapResources(1, &cuda_vbo_resource, 0));
  size_t num_bytes;
  checkCudaErrors(cudaGraphicsResourceGetMappedPointer(
      (void **)&d_result, &num_bytes, cuda_vbo_resource));
  gaussianFilterRGBA(d_img, d_result, d_temp, width, height, sigma, order,
                     nthreads);

  // unmap buffer object
  checkCudaErrors(cudaGraphicsUnmapResources(1, &cuda_vbo_resource, 0));

  // load texture from pbo
  glBindBuffer(GL_PIXEL_UNPACK_BUFFER_ARB, pbo);
  glBindTexture(GL_TEXTURE_2D, texid);
  glPixelStorei(GL_UNPACK_ALIGNMENT, 1);
  glTexSubImage2D(GL_TEXTURE_2D, 0, 0, 0, width, height, GL_RGBA,
                  GL_UNSIGNED_BYTE, 0);
  glBindBuffer(GL_PIXEL_UNPACK_BUFFER_ARB, 0);

  // display results
  glClear(GL_COLOR_BUFFER_BIT);

  glEnable(GL_TEXTURE_2D);
  glDisable(GL_DEPTH_TEST);

  glBegin(GL_QUADS);
  glTexCoord2f(0, 1);
  glVertex2f(0, 0);
  glTexCoord2f(1, 1);
  glVertex2f(1, 0);
  glTexCoord2f(1, 0);
  glVertex2f(1, 1);
  glTexCoord2f(0, 0);
  glVertex2f(0, 1);
  glEnd();

  glDisable(GL_TEXTURE_2D);
  glutSwapBuffers();

  sdkStopTimer(&timer);

  computeFPS();
}

void idle() { glutPostRedisplay(); }

void cleanup() {
  sdkDeleteTimer(&timer);

  checkCudaErrors(cudaFree(d_img));
  checkCudaErrors(cudaFree(d_temp));

  if (!runBenchmark) {
    if (pbo) {
      // unregister this buffer object with CUDA
      checkCudaErrors(cudaGraphicsUnregisterResource(cuda_vbo_resource));
      glDeleteBuffers(1, &pbo);
    }

    if (texid) {
      glDeleteTextures(1, &texid);
    }
  }
}

void keyboard(unsigned char key, int x, int y) {
  switch (key) {
    case 27:
#if defined(__APPLE__) || defined(MACOSX)
      exit(EXIT_SUCCESS);
#else
      glutDestroyWindow(glutGetWindow());
      return;
#endif
      break;

    case '=':
      sigma += 0.1f;
      break;

    case '-':
      sigma -= 0.1f;

      if (sigma < 0.0) {
        sigma = 0.0f;
      }

      break;

    case '+':
      sigma += 1.0f;
      break;

    case '_':
      sigma -= 1.0f;

      if (sigma < 0.0) {
        sigma = 0.0f;
      }

      break;

    case '0':
      order = 0;
      break;

    case '1':
      order = 1;
      sigma = 0.5f;
      break;

    case '2':
      order = 2;
      sigma = 0.5f;
      break;

    default:
      break;
  }

  printf("sigma = %f\n", sigma);
  glutPostRedisplay();
}

void reshape(int x, int y) {
  glViewport(0, 0, x, y);

  glMatrixMode(GL_MODELVIEW);
  glLoadIdentity();

  glMatrixMode(GL_PROJECTION);
  glLoadIdentity();
  glOrtho(0.0, 1.0, 0.0, 1.0, 0.0, 1.0);
}

void initCudaBuffers() {
  unsigned int size = width * height * sizeof(unsigned int);

  // allocate device memory
  checkCudaErrors(cudaMalloc((void **)&d_img, size));
  checkCudaErrors(cudaMalloc((void **)&d_temp, size));

  checkCudaErrors(cudaMemcpy(d_img, h_img, size, cudaMemcpyHostToDevice));

  sdkCreateTimer(&timer);
}

void initGLBuffers() {
  // create pixel buffer object to store final image
  glGenBuffers(1, &pbo);
  glBindBuffer(GL_PIXEL_UNPACK_BUFFER_ARB, pbo);
  glBufferData(GL_PIXEL_UNPACK_BUFFER_ARB, width * height * sizeof(GLubyte) * 4,
               h_img, GL_STREAM_DRAW_ARB);

  glBindBuffer(GL_PIXEL_UNPACK_BUFFER_ARB, 0);
  checkCudaErrors(cudaGraphicsGLRegisterBuffer(
      &cuda_vbo_resource, pbo, cudaGraphicsRegisterFlagsWriteDiscard));

  // create texture for display
  glGenTextures(1, &texid);
  glBindTexture(GL_TEXTURE_2D, texid);
  glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA8, width, height, 0, GL_RGBA,
               GL_UNSIGNED_BYTE, NULL);
  glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
  glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
  glBindTexture(GL_TEXTURE_2D, 0);
}

void initGL(int *argc, char **argv) {
  glutInit(argc, argv);
  glutInitDisplayMode(GLUT_RGB | GLUT_DOUBLE);
  glutInitWindowSize(width, height);
  glutCreateWindow(sSDKsample);
  glutDisplayFunc(display);
  glutKeyboardFunc(keyboard);
  glutReshapeFunc(reshape);
  glutIdleFunc(idle);

#if defined(__APPLE__) || defined(MACOSX)
  atexit(cleanup);
#else
  glutCloseFunc(cleanup);
#endif

  printf("Press '+' and '-' to change filter width\n");
  printf("0, 1, 2 - change filter order\n");

  if (!isGLVersionSupported(2, 0) ||
      !areGLExtensionsSupported(
          "GL_ARB_vertex_buffer_object GL_ARB_pixel_buffer_object")) {
    fprintf(stderr, "Required OpenGL extensions missing.");
    exit(EXIT_FAILURE);
  }
}

void benchmark(int iterations) {
  // allocate memory for result
  unsigned int *d_result;
  unsigned int size = width * height * sizeof(unsigned int);
  checkCudaErrors(cudaMalloc((void **)&d_result, size));

  // warm-up
  gaussianFilterRGBA(d_img, d_result, d_temp, width, height, sigma, order,
                     nthreads);

  checkCudaErrors(cudaDeviceSynchronize());
  sdkStartTimer(&timer);

  // execute the kernel
  for (int i = 0; i < iterations; i++) {
    gaussianFilterRGBA(d_img, d_result, d_temp, width, height, sigma, order,
                       nthreads);
  }

  checkCudaErrors(cudaDeviceSynchronize());
  sdkStopTimer(&timer);

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

  printf("Processing time: %f (ms)\n", sdkGetTimerValue(&timer));
  printf("%.2f Mpixels/sec\n",
         (width * height * iterations / (sdkGetTimerValue(&timer) / 1000.0f)) /
             1e6);

  checkCudaErrors(cudaFree(d_result));
}

bool runSingleTest(const char *ref_file, const char *exec_path) {
  // allocate memory for result
  int nTotalErrors = 0;
  unsigned int *d_result;
  unsigned int size = width * height * sizeof(unsigned int);
  checkCudaErrors(cudaMalloc((void **)&d_result, size));

  // warm-up
  gaussianFilterRGBA(d_img, d_result, d_temp, width, height, sigma, order,
                     nthreads);

  checkCudaErrors(cudaDeviceSynchronize());
  sdkStartTimer(&timer);

  gaussianFilterRGBA(d_img, d_result, d_temp, width, height, sigma, order,
                     nthreads);
  checkCudaErrors(cudaDeviceSynchronize());
  getLastCudaError("Kernel execution failed");
  sdkStopTimer(&timer);

  unsigned char *h_result = (unsigned char *)malloc(width * height * 4);
  checkCudaErrors(cudaMemcpy(h_result, d_result, width * height * 4,
                             cudaMemcpyDeviceToHost));

  char dump_file[1024];
  sprintf(dump_file, "lena_%02d.ppm", (int)sigma);
  sdkSavePPM4ub(dump_file, h_result, width, height);

  if (!sdkComparePPM(dump_file, sdkFindFilePath(ref_file, exec_path),
                     MAX_EPSILON_ERROR, THRESHOLD, false)) {
    nTotalErrors++;
  }

  printf("Processing time: %f (ms)\n", sdkGetTimerValue(&timer));
  printf("%.2f Mpixels/sec\n",
         (width * height / (sdkGetTimerValue(&timer) / 1000.0f)) / 1e6);

  checkCudaErrors(cudaFree(d_result));
  free(h_result);

  printf("Summary: %d errors!\n", nTotalErrors);

  printf(nTotalErrors == 0 ? "Test passed\n" : "Test failed!\n");
  return (nTotalErrors == 0);
}

////////////////////////////////////////////////////////////////////////////////
// Program main
////////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv) {
  pArgc = &argc;
  pArgv = argv;
  char *ref_file = NULL;

#if defined(__linux__)
  setenv("DISPLAY", ":0", 0);
#endif

  printf("%s Starting...\n\n", sSDKsample);

  printf(
      "NOTE: The CUDA Samples are not meant for performance measurements. "
      "Results may vary when GPU Boost is enabled.\n\n");

  // use command-line specified CUDA device, otherwise use device with highest
  // Gflops/s
  if (argc > 1) {
    if (checkCmdLineFlag(argc, (const char **)argv, "file")) {
      getCmdLineArgumentString(argc, (const char **)argv, "file", &ref_file);
      fpsLimit = frameCheckNumber;
    }
  }

  // Get the path of the filename
  char *filename;

  if (getCmdLineArgumentString(argc, (const char **)argv, "image", &filename)) {
    image_filename = filename;
  }

  // load image
  char *image_path = sdkFindFilePath(image_filename, argv[0]);

  if (image_path == NULL) {
    fprintf(stderr, "Error unable to find and load image file: '%s'\n",
            image_filename);
    exit(EXIT_FAILURE);
  }

  sdkLoadPPM4ub(image_path, (unsigned char **)&h_img, &width, &height);

  if (!h_img) {
    printf("Error unable to load PPM file: '%s'\n", image_path);
    exit(EXIT_FAILURE);
  }

  printf("Loaded '%s', %d x %d pixels\n", image_path, width, height);

  if (checkCmdLineFlag(argc, (const char **)argv, "threads")) {
    nthreads = getCmdLineArgumentInt(argc, (const char **)argv, "threads");
  }

  if (checkCmdLineFlag(argc, (const char **)argv, "sigma")) {
    sigma = getCmdLineArgumentFloat(argc, (const char **)argv, "sigma");
  }

  runBenchmark = checkCmdLineFlag(argc, (const char **)argv, "benchmark");

  int device;
  struct cudaDeviceProp prop;
  cudaGetDevice(&device);
  cudaGetDeviceProperties(&prop, device);

  if (!strncmp("Tesla", prop.name, 5)) {
    printf(
        "Tesla card detected, running the test in benchmark mode (no OpenGL "
        "display)\n");
    //        runBenchmark = true;
    runBenchmark = true;
  }

  // Benchmark or AutoTest mode detected, no OpenGL
  if (runBenchmark == true || ref_file != NULL) {
    findCudaDevice(argc, (const char **)argv);
  } else {
    // First initialize OpenGL context, and then select CUDA device.
    initGL(&argc, argv);
    findCudaDevice(argc, (const char **)argv);
  }

  initCudaBuffers();

  if (ref_file) {
    printf("(Automated Testing)\n");
    bool testPassed = runSingleTest(ref_file, argv[0]);

    cleanup();
    exit(testPassed ? EXIT_SUCCESS : EXIT_FAILURE);
  }

  if (runBenchmark) {
    printf("(Run Benchmark)\n");
    benchmark(100);

    cleanup();
    exit(EXIT_SUCCESS);
  }

  initGLBuffers();
  glutMainLoop();

  exit(EXIT_SUCCESS);
}
