Laboratory 5

Introduction to OpenCL programming

The objectives of the current laboratory sessión are the following:

Fundamentals of OpenCL API:
- Environment setup
- Host <-> Device communication
- Simple kernel programming
- Host-Device synchronization basics
Basic kernel programming
- Image flip
- Histogram
- Image rotation

Previous steps

Before starting with the execises, we will install the CImg Library. The CImg Library is a small and open-source C++ toolkit for image processing. The library can be downloaded from: http://cimg.eu/files/CImg_latest.zip. You can also find more documentation and tutorials at http://cimg.eu/

In order to use this library you should include the following code in your .cpp file:

#include "CImg.h" // Path to the previous download directory
using namespace cimg_library;

Let's start by writing the following simple code:

#include "CImg.h"
using namespace cimg_library;
int main() {
  CImg<unsigned char> img(640,400,1,3);  // Define a 640x400 color image with 8 bits per color component
  img.fill(0);                           // Set pixel values to 0 (color : black)
  unsigned char purple[] = { 255,0,255 };        // Define a purple color
  img.draw_text(100,100,"Hello World",purple); // Draw a purple "Hello world" at coordinates (100,100)
  img.display("My first CImg code");             // Display the image in a display window
  return 0;
}

In order to compile you need the following order

$prompt> g++ source.cpp -o executable -I[PATH_TO_CIMG] -lm -lpthread -lX11

Next, we show a code that will load an image, dump some statistics about the loaded image and finally accessing to a given pixel.

int main(){
  CImg<unsigned char> img("image.jpg");  // Load image file "image.jpg" at object img

  std::cout << "Image width: " << img.width() << "Image height: " << img.height() << "Number of slices: " << img.depth() << "Number of channels: " << img.spectrum() << std::endl;  //dump some characteristics of the loaded image

  int i = XXX;
  int j = XXX;
  std::cout << std::hex << img(i, j, 0, 0) << std::endl;  //print pixel value for channel 0 (red) 
  std::cout << std::hex << img(i, j, 0, 1) << std::endl;  //print pixel value for channel 1 (green) 
  std::cout << std::hex << img(i, j, 0, 2) << std::endl;  //print pixel value for channel 2 (blue) 
  
  img.display("My first CImg code");             // Display the image in a display window

  return 0;

}

Task. Write a code that reads an image from a file, dumps image data into an array and prompts the value of a pixel in the screen.

Task. Extend the previous work by modifying the original image with a crossing blue line in the middle of the image and check the result by displaying it on the screen.

Fundamentals of OpenCL API

In this part of the lab, we present the part of the OpenCL API to write code in order to: setup the environment, communicate host<->device, simple kernel programming, and synchronization basics.

Along this section, the following resources will be helpfull:

Abbreviated reference card of the OpenCL API version 2.1 (https://www.khronos.org/files/opencl21-reference-guide.pdf)
Reference manual of the OpenCL API version 2.1 (https://www.khronos.org/registry/OpenCL/specs/opencl-2.1.pdf)

Environment Setup

In this section, we will develop a basic program to set up the basic OpenCL environment and to familiarize with the API for that purpose. To begin with, please have a look to basic_environ.c. In that file, you should find an "almost" complete scheme of an OpenCL program until the creation of the command_queue. The first task is completing the code in basic_environ.c, start by completing each appearance of "/***???***/". Pay attention to the selection of the device to use. Next, complete this basic OpenCL program and dump on the screen more information about the platform and the devices.

Question. How many platforms has this computing system? How many devices has each one of these platforms?

First Kernel on the Device

Once the following steps from 1 to 4 are completed (they refer to the creation of a command_queue for the selected device), in this section we will proceed with the basics to create a new kernel to be launched in the devices. Let's proceed with the following steps, but take into account that some portions of the code must be completed /***???***/:

Create a new file with the kernel you would like to execute into the device. It can be call for example kernel.cl For example, a kernel to calculate the power of two of the elements of an input vector. Feel free to write any other simple kernel you would like to test.

__kernel void pow_of_two(
  __global float *in,
  __global float *out,
  const unsigned int count){

  int i = get_global_id(/***???***/);

  if(i < count){
    out[i] = in[i] * in[i];
  }
}

Add code to the file basic_environ.c to load the source code of kernel.cl in an array of characters to be processed by the OpenCL runtime by the procedure clCreateProgramWithSource(). Consider the following code.

  // Calculate size of the file
  FILE *fileHandler = fopen(/***???***/, "r");
  fseek(/***???***/, 0, SEEK_END);
  size_t fileSize = ftell(fileHandler);
  rewind(fileHandler);

  // read kernel source into buffer
  char * sourceCode = (char*) malloc(fileSize + 1);
  sourceCode[fileSize] = '\0';
  fread(sourceCode, sizeof(char), fileSize, fileHandler);
  fclose(fileHandler);

  // create program from buffer
  program = clCreateProgramWithSource(/***???***/);
  cl_error(err, "Failed to create program with source\n");
  free(sourceCode);

Build the source code of the program for a given device with the procedure clBuildProgram(). Added to this, It is a good idea to check correctness in the resulting log after the compilation process.

  // Build the executable and check errors
  err = clBuildProgram(program, 0, NULL, NULL, NULL, NULL);
  if (err != CL_SUCCESS){
    size_t len;
    char buffer[2048];

    printf("Error: Some error at building process.\n");
    clGetProgramBuildInfo(/***???***/);
    printf("%s\n", buffer);
    exit(-1);
  }

Create a kernel with the selected kernel procedure from the file kernel.cl: __kernel void pow_of_two ( ... ).

  // Create a compute kernel with the program we want to run
  kernel = clCreateKernel(/***???***/);
  cl_error(err, "Failed to create kernel from the program\n");

Create and initialize the input and output arrays at the host memory. Taking into account the kernel definition, data type of these arrays is float.
Create the input and output arrays at the device memory. Computing device will refer these object as the source and destination of the power of two calculations, and they will be referred as arguments of the kernel function at the file kernel.cl.

  // Create OpenCL buffer visible to the OpenCl runtime
  cl_mem in_device_object  = clCreateBuffer(context, CL_MEM_READ_ONLY, /***???***/, NULL, &err);
  cl_error(err, "Failed to create memory buffer at device\n");
  cl_mem out_device_object = clCreateBuffer(context, CL_MEM_WRITE_ONLY, /***???***/, NULL, &err);
  cl_error(err, "Failed to create memory buffer at device\n");

Completely copy float values in the input array at the host memory to the corresponding input array at the device memory.

  // Write date into the memory object 
  err = clEnqueueWriteBuffer(command_queue, in_device_object, CL_TRUE, 0, sizeof(float) * count, /***???***/, 0, NULL, NULL);
  cl_error(err, "Failed to enqueue a write command\n");

Set the proper arguments to the kernel OpenCL object, as they are specified in the kernel function in kernel.cl. First, a pointer to the input memory at the device which should hold the source values on which the power of two operation will be performed. Second, a pointer to the output memory at the device which should hold the result values after finishing the computations in the computation device. Third, the number of elements of the input and output arrays.

  // Set the arguments to the kernel
  err = clSetKernelArg(kernel, 0, sizeof(cl_mem), &in_device_object);
  cl_error(err, "Failed to set argument 0\n");
  err = clSetKernelArg(kernel, 1, sizeof(cl_mem), &out_device_object);
  cl_error(err, "Failed to set argument 1\n");
  err = clSetKernelArg(kernel, 2, /***???***/);
  cl_error(err, "Failed to set argument 2\n");

After this, we are ready to launch the kernel function to execute at the computing device.

  // Launch Kernel
  local_size = 128;
  global_size = /***???***/;
  err = clEnqueueNDRangeKernel(/***???***/, 1, NULL, &global_size, &local_size, 0, NULL, NULL);
  cel_error(err, "Failed to launch kernel to the device\n");

Completely read the results of the calculations from the output device memory object and copy them to host memory output array.

  // Read data form device memory back to host memory
  err = clEnqueueReadBuffer(/***???***/, CL_TRUE, 0, /***???***/, 0, NULL, NULL);
  cl_error(err, "Failed to enqueue a read command\n");

Write code to check the correctness of the execution.
Release all the OpenCL memory objects allocated along this program.

  clReleaseMemObject(/***???***/);
  clReleaseMemObject(/***???***/);
  clReleaseProgram(/***???***/);
  clReleaseKernel(/***???***/);
  clReleaseCommandQueue(/***???***/);
  clReleaseContext(/***???***/);

Basic kernel programming

In this section we propose three basic problems[^1] to be implemented by launchig an OpenCL kernel with the core computations for each one. As a result and in order to check correctness of each problem, plot on the screen the corresponding results, either numerical or transformed images.

Image flip. Transform an image by flipping it over a central vertical axis. That is, it achieves the same effect as seeing that image reflected in a mirror. This transformation should be done in-place, this is the same source buffer for the former image should hold the transformed image after kernel execution.
Histogram. Process a given image and calculate the histogram per each color channel: red, green and blue. Each histogram has 256 entries to classify any possible value of the given image.
Image rotation. Transform an image by rotating it over the center of the image. The rotation angle should be given as an argument to the kernel. The resulting rotated image should be stored in a new output buffer. Remmember the following equations:

x₂ = cos(angle) * (x₁ - x₀) - sin(angle) * (y₁ - y₀) + x₀

y₂ = sin(angle) * (x₁ - x₀) - cos(angle) * (y₁ - y₀) + y₀

In this equations, (x₀, y₀) stands for the coordinates of the center point of the rotation transformation. (x₁, y₁) stands for the source point in the image and (x₂, y₂) the destination point after the rotation tranformations for the former point (x₁, y₁). More information at https://homepages.inf.ed.ac.uk/rbf/HIPR2/rotate.htm

[^1]: Feel free to implement any other problem of your consideration as far as the complexity is similar.

Overall Task. For this last part of the lab script, measure or elaborate the following metrics for the three different previous exercises.

Execution time of the overall program
Execution time of the kernel
Bandwidth to/from memory to/from kernel
Throughput of the kernel
Footprint of the program

Programming and Architecture of Computing Systems

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