mirror of
https://github.com/NVIDIA/cuda-samples.git
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625 lines
18 KiB
C++
625 lines
18 KiB
C++
/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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/*
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Image box filtering example
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This sample uses CUDA to perform a simple box filter on an image
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and uses OpenGL to display the results.
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It processes rows and columns of the image in parallel.
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The box filter is implemented such that it has a constant cost,
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regardless of the filter width.
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Press '=' to increment the filter radius, '-' to decrease it
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Version 1.1 - modified to process 8-bit RGBA images
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*/
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// OpenGL Graphics includes
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#include <helper_gl.h>
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#if defined(__APPLE__) || defined(__MACOSX)
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#pragma clang diagnostic ignored "-Wdeprecated-declarations"
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#include <GLUT/glut.h>
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#ifndef glutCloseFunc
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#define glutCloseFunc glutWMCloseFunc
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#endif
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#else
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#include <GL/freeglut.h>
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#endif
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// CUDA utilities and system includes
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#include <cuda_runtime.h>
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#include <cuda_gl_interop.h>
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// Helper functions
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#include <helper_functions.h> // CUDA SDK Helper functions
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#include <helper_cuda.h> // CUDA device initialization helper functions
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#define MAX_EPSILON_ERROR 5.0f
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#define REFRESH_DELAY 10 // ms
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const static char *sSDKsample = "CUDA Iterative Box Filter";
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// Define the files that are to be save and the reference images for validation
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const char *sOriginal[] = {"lenaRGB_14.ppm", "lenaRGB_22.ppm", NULL};
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const char *sReference[] = {"ref_14.ppm", "ref_22.ppm", NULL};
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const char *image_filename = "lenaRGB.ppm";
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int iterations = 1;
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int filter_radius = 14;
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int nthreads = 64;
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unsigned int width, height;
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unsigned int *h_img = NULL;
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unsigned int *d_img = NULL;
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unsigned int *d_temp = NULL;
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GLuint pbo; // OpenGL pixel buffer object
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struct cudaGraphicsResource *cuda_pbo_resource; // handles OpenGL-CUDA exchange
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GLuint texid; // Texture
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GLuint shader;
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StopWatchInterface *timer = NULL, *kernel_timer = NULL;
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// Auto-Verification Code
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int fpsCount = 0; // FPS count for averaging
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int fpsLimit = 8; // FPS limit for sampling
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int g_Index = 0;
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int g_nFilterSign = 1;
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float avgFPS = 0.0f;
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unsigned int frameCount = 0;
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unsigned int g_TotalErrors = 0;
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bool g_bInteractive = false;
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int *pArgc = NULL;
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char **pArgv = NULL;
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extern "C" int runSingleTest(char *ref_file, char *exec_path);
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extern "C" int runBenchmark();
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extern "C" void loadImageData(int argc, char **argv);
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extern "C" void computeGold(float *id, float *od, int w, int h, int n);
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// These are CUDA functions to handle allocation and launching the kernels
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extern "C" void initTexture(int width, int height, void *pImage, bool useRGBA);
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extern "C" void freeTextures();
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extern "C" double boxFilter(float *d_src, float *d_temp, float *d_dest,
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int width, int height, int radius, int iterations,
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int nthreads, StopWatchInterface *timer);
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extern "C" double boxFilterRGBA(unsigned int *d_src, unsigned int *d_temp,
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unsigned int *d_dest, int width, int height,
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int radius, int iterations, int nthreads,
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StopWatchInterface *timer);
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// This varies the filter radius, so we can see automatic animation
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void varySigma() {
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filter_radius += g_nFilterSign;
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if (filter_radius > 64) {
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filter_radius = 64; // clamp to 64 and then negate sign
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g_nFilterSign = -1;
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} else if (filter_radius < 0) {
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filter_radius = 0;
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g_nFilterSign = 1;
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}
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}
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// Calculate the Frames per second and print in the title bar
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void computeFPS() {
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frameCount++;
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fpsCount++;
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if (fpsCount == fpsLimit) {
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avgFPS = 1.0f / (sdkGetAverageTimerValue(&timer) / 1000.0f);
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fpsCount = 0;
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fpsLimit = (int)MAX(avgFPS, 1.0f);
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sdkResetTimer(&timer);
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}
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char fps[256];
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sprintf(fps,
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"CUDA Rolling Box Filter <Animation=%s> (radius=%d, passes=%d): "
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"%3.1f fps",
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(!g_bInteractive ? "ON" : "OFF"), filter_radius, iterations, avgFPS);
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glutSetWindowTitle(fps);
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if (!g_bInteractive) {
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varySigma();
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}
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}
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// display results using OpenGL
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void display() {
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sdkStartTimer(&timer);
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// execute filter, writing results to pbo
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unsigned int *d_result;
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checkCudaErrors(cudaGraphicsMapResources(1, &cuda_pbo_resource, 0));
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size_t num_bytes;
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checkCudaErrors(cudaGraphicsResourceGetMappedPointer(
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(void **)&d_result, &num_bytes, cuda_pbo_resource));
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boxFilterRGBA(d_img, d_temp, d_result, width, height, filter_radius,
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iterations, nthreads, kernel_timer);
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checkCudaErrors(cudaGraphicsUnmapResources(1, &cuda_pbo_resource, 0));
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// OpenGL display code path
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{
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glClear(GL_COLOR_BUFFER_BIT);
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// load texture from pbo
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glBindBuffer(GL_PIXEL_UNPACK_BUFFER_ARB, pbo);
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glBindTexture(GL_TEXTURE_2D, texid);
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glTexSubImage2D(GL_TEXTURE_2D, 0, 0, 0, width, height, GL_RGBA,
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GL_UNSIGNED_BYTE, 0);
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glBindBuffer(GL_PIXEL_UNPACK_BUFFER_ARB, 0);
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// fragment program is required to display floating point texture
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glBindProgramARB(GL_FRAGMENT_PROGRAM_ARB, shader);
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glEnable(GL_FRAGMENT_PROGRAM_ARB);
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glDisable(GL_DEPTH_TEST);
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glBegin(GL_QUADS);
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{
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glTexCoord2f(0.0f, 0.0f);
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glVertex2f(0.0f, 0.0f);
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glTexCoord2f(1.0f, 0.0f);
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glVertex2f(1.0f, 0.0f);
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glTexCoord2f(1.0f, 1.0f);
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glVertex2f(1.0f, 1.0f);
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glTexCoord2f(0.0f, 1.0f);
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glVertex2f(0.0f, 1.0f);
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}
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glEnd();
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glBindTexture(GL_TEXTURE_2D, 0);
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glDisable(GL_FRAGMENT_PROGRAM_ARB);
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}
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glutSwapBuffers();
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glutReportErrors();
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sdkStopTimer(&timer);
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computeFPS();
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}
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// Keyboard callback function for OpenGL (GLUT)
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void keyboard(unsigned char key, int /*x*/, int /*y*/) {
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switch (key) {
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case 27:
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#if defined(__APPLE__) || defined(MACOSX)
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exit(EXIT_SUCCESS);
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#else
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glutDestroyWindow(glutGetWindow());
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return;
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#endif
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break;
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case 'a':
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case 'A':
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g_bInteractive = !g_bInteractive;
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printf("> Animation is %s\n", !g_bInteractive ? "ON" : "OFF");
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break;
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case '=':
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case '+':
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if (filter_radius < (int)width - 1 && filter_radius < (int)height - 1) {
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filter_radius++;
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}
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break;
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case '-':
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if (filter_radius > 1) {
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filter_radius--;
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}
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break;
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case ']':
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iterations++;
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break;
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case '[':
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if (iterations > 1) {
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iterations--;
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}
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break;
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default:
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break;
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}
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printf("radius = %d, iterations = %d\n", filter_radius, iterations);
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}
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// Timer Event so we can refresh the display
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void timerEvent(int value) {
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if (glutGetWindow()) {
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glutPostRedisplay();
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glutTimerFunc(REFRESH_DELAY, timerEvent, 0);
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}
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}
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// Resizing the window
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void reshape(int x, int y) {
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glViewport(0, 0, x, y);
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glMatrixMode(GL_MODELVIEW);
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glLoadIdentity();
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glMatrixMode(GL_PROJECTION);
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glLoadIdentity();
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glOrtho(0.0, 1.0, 0.0, 1.0, 0.0, 1.0);
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}
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void initCuda(bool useRGBA) {
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// allocate device memory
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checkCudaErrors(
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cudaMalloc((void **)&d_img, (width * height * sizeof(unsigned int))));
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checkCudaErrors(
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cudaMalloc((void **)&d_temp, (width * height * sizeof(unsigned int))));
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// Refer to boxFilter_kernel.cu for implementation
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initTexture(width, height, h_img, useRGBA);
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sdkCreateTimer(&timer);
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sdkCreateTimer(&kernel_timer);
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}
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void cleanup() {
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sdkDeleteTimer(&timer);
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sdkDeleteTimer(&kernel_timer);
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if (h_img) {
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free(h_img);
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h_img = NULL;
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}
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if (d_img) {
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cudaFree(d_img);
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d_img = NULL;
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}
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if (d_temp) {
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cudaFree(d_temp);
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d_temp = NULL;
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}
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// Refer to boxFilter_kernel.cu for implementation
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freeTextures();
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cudaGraphicsUnregisterResource(cuda_pbo_resource);
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glDeleteBuffers(1, &pbo);
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glDeleteTextures(1, &texid);
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glDeleteProgramsARB(1, &shader);
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}
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// shader for displaying floating-point texture
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static const char *shader_code =
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"!!ARBfp1.0\n"
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"TEX result.color, fragment.texcoord, texture[0], 2D; \n"
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"END";
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GLuint compileASMShader(GLenum program_type, const char *code) {
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GLuint program_id;
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glGenProgramsARB(1, &program_id);
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glBindProgramARB(program_type, program_id);
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glProgramStringARB(program_type, GL_PROGRAM_FORMAT_ASCII_ARB,
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(GLsizei)strlen(code), (GLubyte *)code);
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GLint error_pos;
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glGetIntegerv(GL_PROGRAM_ERROR_POSITION_ARB, &error_pos);
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if (error_pos != -1) {
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const GLubyte *error_string;
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error_string = glGetString(GL_PROGRAM_ERROR_STRING_ARB);
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printf("Program error at position: %d\n%s\n", (int)error_pos, error_string);
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return 0;
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}
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return program_id;
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}
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// This is where we create the OpenGL PBOs, FBOs, and texture resources
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void initGLResources() {
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// create pixel buffer object
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glGenBuffers(1, &pbo);
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glBindBuffer(GL_PIXEL_UNPACK_BUFFER_ARB, pbo);
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glBufferData(GL_PIXEL_UNPACK_BUFFER_ARB, width * height * sizeof(GLubyte) * 4,
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h_img, GL_STREAM_DRAW_ARB);
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glBindBuffer(GL_PIXEL_UNPACK_BUFFER_ARB, 0);
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checkCudaErrors(cudaGraphicsGLRegisterBuffer(
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&cuda_pbo_resource, pbo, cudaGraphicsMapFlagsWriteDiscard));
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// create texture for display
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glGenTextures(1, &texid);
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glBindTexture(GL_TEXTURE_2D, texid);
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glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA8, width, height, 0, GL_RGBA,
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GL_UNSIGNED_BYTE, NULL);
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glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
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glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
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glBindTexture(GL_TEXTURE_2D, 0);
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// load shader program
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shader = compileASMShader(GL_FRAGMENT_PROGRAM_ARB, shader_code);
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}
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void initGL(int *argc, char **argv) {
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// initialize GLUT
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glutInit(argc, argv);
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glutInitDisplayMode(GLUT_RGBA | GLUT_DOUBLE);
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glutInitWindowSize(768, 768);
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glutCreateWindow("CUDA Rolling Box Filter");
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glutDisplayFunc(display);
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glutKeyboardFunc(keyboard);
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glutReshapeFunc(reshape);
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glutTimerFunc(REFRESH_DELAY, timerEvent, 0);
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if (!isGLVersionSupported(2, 0) ||
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!areGLExtensionsSupported(
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"GL_ARB_vertex_buffer_object GL_ARB_pixel_buffer_object")) {
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printf("Error: failed to get minimal extensions for demo\n");
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printf("This sample requires:\n");
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printf(" OpenGL version 2.0\n");
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printf(" GL_ARB_vertex_buffer_object\n");
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printf(" GL_ARB_pixel_buffer_object\n");
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exit(EXIT_FAILURE);
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}
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}
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////////////////////////////////////////////////////////////////////////////////
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//! Run a simple benchmark test for CUDA
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////////////////////////////////////////////////////////////////////////////////
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int runBenchmark() {
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printf("[runBenchmark]: [%s]\n", sSDKsample);
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initCuda(true);
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unsigned int *d_result;
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checkCudaErrors(
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cudaMalloc((void **)&d_result, width * height * sizeof(unsigned int)));
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// warm-up
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boxFilterRGBA(d_img, d_temp, d_temp, width, height, filter_radius, iterations,
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nthreads, kernel_timer);
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checkCudaErrors(cudaDeviceSynchronize());
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sdkStartTimer(&kernel_timer);
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// Start round-trip timer and process iCycles loops on the GPU
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iterations = 1; // standard 1-pass filtering
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const int iCycles = 150;
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double dProcessingTime = 0.0;
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printf("\nRunning BoxFilterGPU for %d cycles...\n\n", iCycles);
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for (int i = 0; i < iCycles; i++) {
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dProcessingTime +=
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boxFilterRGBA(d_img, d_temp, d_img, width, height, filter_radius,
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iterations, nthreads, kernel_timer);
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}
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// check if kernel execution generated an error and sync host
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getLastCudaError("Error: boxFilterRGBA Kernel execution FAILED");
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checkCudaErrors(cudaDeviceSynchronize());
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sdkStopTimer(&kernel_timer);
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// Get average computation time
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dProcessingTime /= (double)iCycles;
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// log testname, throughput, timing and config info to sample and master logs
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printf(
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"boxFilter-texture, Throughput = %.4f M RGBA Pixels/s, Time = %.5f s, "
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"Size = %u RGBA Pixels, NumDevsUsed = %u, Workgroup = %u\n",
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(1.0e-6 * width * height) / dProcessingTime, dProcessingTime,
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(width * height), 1, nthreads);
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printf("\n");
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return 0;
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}
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// This test specifies a single test (where you specify radius and/or
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// iterations)
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int runSingleTest(char *ref_file, char *exec_path) {
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int nTotalErrors = 0;
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char dump_file[256];
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printf("[runSingleTest]: [%s]\n", sSDKsample);
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initCuda(true);
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unsigned int *d_result;
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unsigned int *h_result =
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(unsigned int *)malloc(width * height * sizeof(unsigned int));
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checkCudaErrors(
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cudaMalloc((void **)&d_result, width * height * sizeof(unsigned int)));
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// run the sample radius
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{
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printf("%s (radius=%d) (passes=%d) ", sSDKsample, filter_radius,
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iterations);
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boxFilterRGBA(d_img, d_temp, d_result, width, height, filter_radius,
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iterations, nthreads, kernel_timer);
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// check if kernel execution generated an error
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getLastCudaError("Error: boxFilterRGBA Kernel execution FAILED");
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checkCudaErrors(cudaDeviceSynchronize());
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// readback the results to system memory
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cudaMemcpy((unsigned char *)h_result, (unsigned char *)d_result,
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width * height * sizeof(unsigned int), cudaMemcpyDeviceToHost);
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sprintf(dump_file, "lenaRGB_%02d.ppm", filter_radius);
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sdkSavePPM4ub((const char *)dump_file, (unsigned char *)h_result, width,
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height);
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if (!sdkComparePPM(dump_file, sdkFindFilePath(ref_file, exec_path),
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MAX_EPSILON_ERROR, 0.15f, false)) {
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printf("Image is Different ");
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nTotalErrors++;
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} else {
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printf("Image is Matching ");
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}
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printf(" <%s>\n", ref_file);
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}
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printf("\n");
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free(h_result);
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checkCudaErrors(cudaFree(d_result));
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return nTotalErrors;
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}
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void loadImageData(int argc, char **argv) {
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// load image (needed so we can get the width and height before we create the
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// window
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char *image_path = NULL;
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if (argc >= 1) {
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image_path = sdkFindFilePath(image_filename, argv[0]);
|
|
}
|
|
|
|
if (image_path == 0) {
|
|
printf("Error finding image file '%s'\n", image_filename);
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
sdkLoadPPM4(image_path, (unsigned char **)&h_img, &width, &height);
|
|
|
|
if (!h_img) {
|
|
printf("Error opening file '%s'\n", image_path);
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
printf("Loaded '%s', %d x %d pixels\n", image_path, width, height);
|
|
}
|
|
|
|
void printHelp() {
|
|
printf("boxFilter usage\n");
|
|
printf(" -threads=n (specify the # of of threads to use)\n");
|
|
printf(" -radius=n (specify the filter radius n to use)\n");
|
|
printf(" -passes=n (specify the number of passes n to use)\n");
|
|
printf(" -file=name (specify reference file for comparison)\n");
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// Program main
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
int main(int argc, char **argv) {
|
|
int devID = 0;
|
|
char *ref_file = NULL;
|
|
|
|
#if defined(__linux__)
|
|
setenv("DISPLAY", ":0", 0);
|
|
#endif
|
|
|
|
pArgc = &argc;
|
|
pArgv = argv;
|
|
|
|
// start logs
|
|
printf("%s Starting...\n\n", argv[0]);
|
|
|
|
if (checkCmdLineFlag(argc, (const char **)argv, "help")) {
|
|
printHelp();
|
|
exit(EXIT_SUCCESS);
|
|
}
|
|
|
|
// use command-line specified CUDA device, otherwise use device with highest
|
|
// Gflops/s
|
|
if (argc > 1) {
|
|
if (checkCmdLineFlag(argc, (const char **)argv, "threads")) {
|
|
nthreads = getCmdLineArgumentInt(argc, (const char **)argv, "threads");
|
|
}
|
|
|
|
if (checkCmdLineFlag(argc, (const char **)argv, "radius")) {
|
|
filter_radius =
|
|
getCmdLineArgumentInt(argc, (const char **)argv, "radius");
|
|
}
|
|
|
|
if (checkCmdLineFlag(argc, (const char **)argv, "passes")) {
|
|
iterations = getCmdLineArgumentInt(argc, (const char **)argv, "passes");
|
|
}
|
|
|
|
if (checkCmdLineFlag(argc, (const char **)argv, "file")) {
|
|
getCmdLineArgumentString(argc, (const char **)argv, "file",
|
|
(char **)&ref_file);
|
|
}
|
|
}
|
|
|
|
// load image to process
|
|
loadImageData(argc, argv);
|
|
devID = findCudaDevice(argc, (const char **)argv);
|
|
|
|
if (checkCmdLineFlag(argc, (const char **)argv, "benchmark")) {
|
|
// This is a separate mode of the sample, where we are benchmark the kernels
|
|
// for performance
|
|
// Running CUDA kernels (boxfilter) in Benchmarking mode
|
|
g_TotalErrors += runBenchmark();
|
|
exit(g_TotalErrors == 0 ? EXIT_SUCCESS : EXIT_FAILURE);
|
|
} else if (checkCmdLineFlag(argc, (const char **)argv, "radius") ||
|
|
checkCmdLineFlag(argc, (const char **)argv, "passes")) {
|
|
// This overrides the default mode. Users can specify the radius used by
|
|
// the filter kernel
|
|
g_TotalErrors += runSingleTest(ref_file, argv[0]);
|
|
exit(g_TotalErrors == 0 ? EXIT_SUCCESS : EXIT_FAILURE);
|
|
} else {
|
|
// Default mode running with OpenGL visualization and in automatic mode
|
|
// the output automatically changes animation
|
|
printf("\n");
|
|
|
|
initGL(&argc, argv);
|
|
|
|
initCuda(true);
|
|
initGLResources();
|
|
|
|
// sets the callback function so it will call cleanup upon exit
|
|
#if defined(__APPLE__) || defined(MACOSX)
|
|
atexit(cleanup);
|
|
#else
|
|
glutCloseFunc(cleanup);
|
|
#endif
|
|
|
|
printf("Running Standard Demonstration with GLUT loop...\n\n");
|
|
printf(
|
|
"Press '+' and '-' to change filter width\n"
|
|
"Press ']' and '[' to change number of iterations\n"
|
|
"Press 'a' or 'A' to change animation ON/OFF\n\n");
|
|
|
|
// Main OpenGL loop that will run visualization for every vsync
|
|
glutMainLoop();
|
|
}
|
|
}
|