‘nvidia-smi is not recognized as an internal or external command, operable program or batch file

Solution ‘nvidia-smi’ is not recognized as an internal or external command, operable program or batch file

Problem description

On computers using NVIDIA GPU acceleration, you may encounter the following error message when trying to execute the command ??nvidia-smi??:

plaintextCopy code'nvidia-smi' is not recognized as an internal or external command, operable program or batch file

Solution

1. Check whether the NVIDIA driver is installed correctly

First, make sure that the NVIDIA graphics driver is installed correctly on your computer and that the driver version is compatible with the GPU. You can download the driver suitable for your graphics card model from the NVIDIA official website and install it.

2. Add environment variables

??nvidia-smi?? is a command line tool provided by NVIDIA official driver for viewing GPU status and performance information. When running this command, the system needs to know the path where it is located. If the NVIDIA installation directory is not added to the system’s environment variables, the above error will occur. To solve this problem, you need to add the NVIDIA installation directory to the system’s environment variable ??PATH??. Here are the specific steps on Windows and Linux systems:

Windows system
  1. Right-click the My Computer (or This PC) icon and select Properties.
  2. In the left panel, click Advanced system settings.
  3. In the “System Properties” window, click the “Environment Variables” button.
  4. In the “Environment Variables” window, find the ??PATH?? variable in the system variables and click the “Edit” button.
  5. In the pop-up editing environment variable window, click the “New” button.
  6. In the New Variable input box, enter the full path to the NVIDIA installation directory, for example, ??C:\Program Files\\
    VIDIA Corporation\\
    VSMI?    ?.
  7. Confirm all windows and restart your computer.
Linux system
  1. Open a terminal.
  2. Edit the ??.bashrc?? file, for example, open it with the ??vi?? or ??nano?? editor:
bashCopy codevi ~/.bashrc
  1. Add the following lines at the end of the file, save and exit:
bashCopy codeexport PATH=$PATH:/usr/local/nvidia/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/nvidia/lib64
  1. Execute the following command in the terminal to make the environment variables take effect immediately:
bashCopy codesource ~/.bashrc

3. Restart the computer

After completing the above steps, it is recommended to restart the computer to ensure that the changes to the environment variables take effect.

Conclusion

By checking the installation of the NVIDIA driver and adding its installation directory to the system’s environment variables, you can solve the problem that ‘nvidia-smi’ is not an internal or external command. This will allow you to successfully run the ??nvidia-smi?? command from the command line and view GPU status and performance information.

Example code

The following is a simple sample code that shows how to use the ??subprocess?? module in Python to execute the ??nvidia-smi?? command and get the GPU’s Status and performance information.

pythonCopy codeimport subprocess
def get_gpu_info():
    try:
        output = subprocess.check_output('nvidia-smi', shell=True)
        gpu_info = output.decode('utf-8')
        return gpu_info
    except subprocess.CalledProcessError as e:
        print(f"Error executing command: {e}")
        return None
# Call the function in the main program and print GPU information
gpu_info = get_gpu_info()
if gpu_info:
    print(gpu_info)
else:
    print("Failed to get GPU information.")

In the above example, we defined a function named ??get_gpu_info()?? to execute the ??nvidia-smi?? command. You can execute commands in Python and get the output by calling the ??subprocess.check_output()?? method. We then convert the output into a string format and return the GPU information. In the main program, we call the ??get_gpu_info()?? function and print the result. If the GPU information is successfully obtained, the information is printed; otherwise, an error message is printed. Please note that before running this sample code, please ensure that the NVIDIA driver has been installed correctly and the environment variables have been added.

Introduction to NVIDIA System Management Interface (nvidia-smi)

The NVIDIA System Management Interface (nvidia-smi) is a command-line tool included with the NVIDIA graphics driver for managing and monitoring NVIDIA GPUs (graphics processor units). It provides a simple and convenient way to view the status of the GPU, performance information, and manage some functions related to configuring the GPU. nvidia-smi can be used in operating systems such as Windows, Linux or macOS.

Function

The following are commonly used functions of nvidia-smi:

  1. Show GPU information: nvidia-smi can provide detailed information about the NVIDIA GPUs installed in your system. This includes the name of the GPU, driver version, temperature, power consumption, memory usage, and a list of currently running processes.
  2. Monitoring GPU performance: nvidia-smi provides the function of real-time monitoring and recording of GPU performance indicators. It can display GPU usage, temperature, power consumption and other information, and you can set options to save these statistics regularly.
  3. Adjust GPU parameters: nvidia-smi allows users to adjust some parameters of the GPU, such as power consumption limits, temperature limits, and fan speeds, through the command line interface. This is useful for optimizing the balance between GPU performance and power consumption.
  4. Manage GPU processes: nvidia-smi can list the processes currently running on the GPU and provide some options for managing and controlling the processes. Users can use nvidia-smi to terminate processes running on the GPU, or find processes that occupy more GPU resources.

Usage

In the command line, you can directly enter the ??nvidia-smi?? command to use the nvidia-smi tool. By default, it displays real-time GPU information, including GPU usage, temperature, power consumption, etc. Different options are available to obtain more detailed or specific information. For example:

  • ??nvidia-smi -a??: Displays all available GPU information, including driver version, PCIe bus information, etc.
  • ??nvidia-smi -l??: Monitor and display GPU performance indicators such as usage, temperature, and power consumption in real time. On Windows, monitoring can be terminated using Ctrl + C.
  • ??nvidia-smi -q??: Displays the detailed properties and status information of the GPU, such as performance status, video memory usage, core frequency, etc.
  • ??nvidia-smi -gpu-reset??: Resets the GPU, clears allocated GPU memory, and reinitializes the GPU.

Application scenarios

nvidia-smi can be used for GPU management and monitoring in many application scenarios. Here are some common application scenarios:

  1. Machine Learning and Deep Learning: nvidia-smi can be used to monitor and manage GPU resources used during training. You can use it to view GPU usage and performance information and ensure that your GPU is functioning properly.
  2. Scientific computing: When performing large-scale scientific computing, using nvidia-smi can help users monitor GPU usage and optimize algorithms for better performance.
  3. Password Cracking and Data Mining: nvidia-smi can be used to monitor GPU usage and temperature. In password cracking or data mining tasks, nvidia-smi can be used to monitor GPU load to ensure full utilization of GPU resources.
  4. Virtualized environment: In a virtualized environment, nvidia-smi can be used to monitor and manage the allocation of GPU resources in multiple virtual machines. In summary, nvidia-smi is a powerful command line tool that can be used to manage and monitor NVIDIA GPUs. By using nvidia-smi, users can understand the status and performance information of the GPU, and perform some configuration and management operations to optimize GPU usage and performance.

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