In the following example, we will use a function of PyOpenCL that allows us to enumerate the features of the GPU on which it will operate.

The code we implement is very simple and logical:

1. In the first step, we import the pyopencl library:

import pyopencl as cl

2. We build a function whose output will provide us with the characteristics of the GPU hardware in use:

def print_device_info() :
    print('
' + '=' * 60 + '
OpenCL Platforms and Devices')
    for platform in cl.get_platforms():
        print('=' * 60)
        print('Platform - Name: ' + platform.name)
        print('Platform - Vendor: ' + platform.vendor)
        print('Platform - Version: ' + platform.version)
        print('Platform - Profile: ' + platform.profile)

        for device in platform.get_devices():
            print(' ' + '-' * 56)
            print(' Device - Name: ' 
                  + device.name)
            print(' Device - Type: ' 
                  + cl.device_type.to_string(device.type))
            print(' Device - Max Clock Speed: {0} Mhz'
                  .format(device.max_clock_frequency))
            print(' Device - Compute Units: {0}'
                  .format(device.max_compute_units))
            print(' Device - Local Memory: {0:.0f} KB'
                  .format(device.local_mem_size/1024.0))
            print(' Device - Constant Memory: {0:.0f} KB'
                  .format(device.max_constant_buffer_size/1024.0))
            print(' Device - Global Memory: {0:.0f} GB'
                  .format(device.global_mem_size/1073741824.0))
            print(' Device - Max Buffer/Image Size: {0:.0f} MB'
                  .format(device.max_mem_alloc_size/1048576.0))
            print(' Device - Max Work Group Size: {0:.0f}'
                  .format(device.max_work_group_size))
    print('
')

3. So, we implement the main function, which calls the previously implemented print_device_info function:

if __name__ == "__main__":
    print_device_info()