Host code - 2023.2 English

The following is the Host code for the canny edge detection example. The host code sets up the OpenCL platform with the FPGA of processing required data. In the case of Vitis Vision example, the data is an image. Reading and writing of images are enabled using called to functions from Vitis Vision.

// setting up device and platform
    std::vector<cl::Device> devices = xcl::get_xil_devices();
    cl::Device device = devices[0];
    cl::Context context(device);
    cl::CommandQueue q(context, device,CL_QUEUE_PROFILING_ENABLE);
    std::string device_name = device.getInfo<CL_PLATFORM_NAME>();

    // Kernel 1: Canny
    std::string binaryFile=xcl::find_binary_file(device_name,"krnl_canny");
    cl::Program::Binaries bins = xcl::import_binary_file(binaryFile);
    devices.resize(1);
    cl::Program program(context, devices, bins);
    cl::Kernel krnl(program,"canny_accel");

    // creating necessary cl buffers for input and output
    cl::Buffer imageToDevice(context, CL_MEM_READ_ONLY,(height*width));
    cl::Buffer imageFromDevice(context, CL_MEM_WRITE_ONLY,(height*width/4));


    // Set the kernel arguments
    krnl.setArg(0, imageToDevice);
    krnl.setArg(1, imageFromDevice);
    krnl.setArg(2, height);
    krnl.setArg(3, width);
    krnl.setArg(4, low_threshold);
    krnl.setArg(5, high_threshold);

    // write the input image data from host to device memory
    q.enqueueWriteBuffer(imageToDevice, CL_TRUE, 0,(height*(width)),img_gray.data);
    // Profiling Objects
    cl_ulong start= 0;
    cl_ulong end = 0;
    double diff_prof = 0.0f;
    cl::Event event_sp;

    // Launch the kernel
    q.enqueueTask(krnl,NULL,&event_sp);
    clWaitForEvents(1, (const cl_event*) &event_sp);

    // profiling
    event_sp.getProfilingInfo(CL_PROFILING_COMMAND_START,&start);
    event_sp.getProfilingInfo(CL_PROFILING_COMMAND_END,&end);
    diff_prof = end-start;
    std::cout<<(diff_prof/1000000)<<"ms"<<std::endl;

    // Kernel 2: edge tracing
    cl::Kernel krnl2(program,"edgetracing_accel");

    cl::Buffer imageFromDeviceedge(context, CL_MEM_WRITE_ONLY,(height*width));

    // Set the kernel arguments
    krnl2.setArg(0, imageFromDevice);
    krnl2.setArg(1, imageFromDeviceedge);
    krnl2.setArg(2, height);
    krnl2.setArg(3, width);

    // Profiling Objects
    cl_ulong startedge= 0;
    cl_ulong endedge = 0;
    double diff_prof_edge = 0.0f;
    cl::Event event_sp_edge;

    // Launch the kernel
    q.enqueueTask(krnl2,NULL,&event_sp_edge);
    clWaitForEvents(1, (const cl_event*) &event_sp_edge);

    // profiling
    event_sp_edge.getProfilingInfo(CL_PROFILING_COMMAND_START,&startedge);
    event_sp_edge.getProfilingInfo(CL_PROFILING_COMMAND_END,&endedge);
    diff_prof_edge = endedge-startedge;
    std::cout<<(diff_prof_edge/1000000)<<"ms"<<std::endl;


    //Copying Device result data to Host memory
    q.enqueueReadBuffer(imageFromDeviceedge, CL_TRUE, 0,(height*width),out_img_edge.data);
    q.finish();