You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: gpuinfo.m
    path of file: ./repos/StiffMa/Utils
    
    the code of the file until where you have to start completion: function info = gpuinfo()
%GPUINFO  get basic details about the GPU being used
%
%   GPUINFO() gets hold of some basic info about the GPU device being used.
%
%   See also: CPUINFO
% 
%   For more information, see the <a href="matlab:
%   web('https://www.mathworks.com/matlabcentral/fileexchange/34080-gpubench')"
%   >Matlab Central</a> web site.

%   Copyright 2011-2014 The MathWorks, Inc.

if parallel.gpu.GPUDevice.isAvailable()
    gpu = gpuDevice();
    info = struct( ...
        'Name', gpu.Name, ...
        'Clock', sprintf( '%u MHz', gpu.ClockRateKHz/1e3 ), ...
        'NumProcessors', gpu.MultiprocessorCount, ...
        'ComputeCapability', gpu.ComputeCapability, ...
        'TotalMemory', sprintf( '%1.2f GB', gpu.TotalMemory/2^30 ), ...
        'CUDAVersion', gpu.DriverVersion, ...
        'DriverVersion', parallel.internal.gpu.CUDADriverVersion );

    
function info = gpuinfo()
%GPUINFO  get basic details about the GPU being used
%
%   GPUINFO() gets hold of some basic info about the GPU device being used.
%
%   See also: CPUINFO
% 
%   For more information, see the <a href="matlab:
%   web('https://www.mathworks.com/matlabcentral/fileexchange/34080-gpubench')"
%   >Matlab Central</a> web site.

%   Copyright 2011-2014 The MathWorks, Inc.

if parallel.gpu.GPUDevice.isAvailable()
    gpu = gpuDevice();
    info = struct( ...
        'Name', gpu.Name, ...
        'Clock', sprintf( '%u MHz', gpu.ClockRateKHz/1e3 ), ...
        'NumProcessors', gpu.MultiprocessorCount, ...
        'ComputeCapability', gpu.ComputeCapability, ...
        'TotalMemory', sprintf( '%1.2f GB', gpu.TotalMemory/2^30 ), ...
        'CUDAVersion', gpu.DriverVersion, ...
        'DriverVersion', parallel.internal.gpu.CUDADriverVersion );
else
    % No GPU, so create an empty structure
    info = struct( ...
        'Name', '<no GPU available>', ...
        'Clock', '', ...
        'NumProcessors', 0, ...
        'ComputeCapability', '', ...
        'TotalMemory', 0, ...
        'CUDAVersion', '', ...
        'DriverVersion', '' );
end