How to kill process on GPUs with PID in nvidia-smi using keyword in python?

How to kill process on GPUs with PID in nvidia-smi using keyword in python?

To kill a process running on a specific GPU using its PID and the nvidia-smi command-line tool, you can execute the appropriate command using Python's subprocess module. Here's how you can do it:

import subprocess def kill_process_on_gpu(gpu_id, pid): command = f"nvidia-smi --gpu={gpu_id} --kill {pid}" subprocess.run(command, shell=True) # Replace 'gpu_id' and 'pid' with the actual GPU ID and PID values gpu_id = 0 # Replace with the GPU ID pid_to_kill = 12345 # Replace with the PID of the process you want to kill kill_process_on_gpu(gpu_id, pid_to_kill)

In this example, the kill_process_on_gpu function takes the GPU ID and PID as arguments, constructs the nvidia-smi command with the appropriate arguments, and then uses subprocess.run() to execute the command. The --gpu flag specifies the GPU to target, and the --kill flag indicates that you want to kill a process. The pid parameter specifies the process ID you want to terminate.

Please note that this approach requires that you have the nvidia-smi tool installed and accessible in your system's PATH. Additionally, this method relies on running the command-line tool from Python, so it might have limitations compared to using native GPU management libraries like NVIDIA's nvidia-ml-py (NVIDIA Management Library Python Bindings). Using native libraries provides more control and capabilities for managing GPU processes programmatically.

Examples

  1. How to list processes running on GPUs using nvidia-smi in Python?

    Description: This query aims to find a method to list processes currently running on GPUs using Nvidia's System Management Interface (nvidia-smi) in Python.

    import subprocess def list_gpu_processes(): result = subprocess.run(['nvidia-smi', 'pmon', '-c', '1'], capture_output=True, text=True) return result.stdout print(list_gpu_processes())

    Code Description: This Python code utilizes the subprocess module to execute the 'nvidia-smi pmon -c 1' command, which lists the processes running on GPUs once. The captured output is then returned, displaying GPU processes.

  2. How to get PID of a process on GPU using nvidia-smi in Python?

    Description: This query seeks a method to retrieve the Process ID (PID) of a specific process running on the GPU using nvidia-smi in Python.

    import subprocess def get_pid_by_name(process_name): result = subprocess.run(['nvidia-smi', '--query-compute-apps=pid,process_name', '--format=csv,noheader'], capture_output=True, text=True) processes = result.stdout.strip().split('\n') for process in processes: pid, name = process.split(', ') if name.strip() == process_name: return int(pid) return None # Example usage process_name = "your_process_name" pid = get_pid_by_name(process_name) print(pid)

    Code Description: This Python code utilizes nvidia-smi with specified options to query GPU processes and their PIDs. It then parses the output to find the PID corresponding to a given process name.

  3. How to kill a process on GPU with PID using nvidia-smi in Python?

    Description: This query aims to find a method to terminate a specific process running on a GPU using nvidia-smi in Python.

    import subprocess def kill_process_by_pid(pid): subprocess.run(['nvidia-smi', '--gpu', '0', '--kill', str(pid)]) print(f"Process with PID {pid} killed successfully.") # Example usage process_pid = 1234 # Replace with the actual PID kill_process_by_pid(process_pid)

    Code Description: This Python code utilizes nvidia-smi with the '--kill' option to terminate a process running on the GPU with a specified PID.

  4. How to iterate over GPU processes in Python using nvidia-smi?

    Description: This query looks for a way to iterate over processes running on GPUs using nvidia-smi in Python.

    import subprocess def iterate_gpu_processes(): result = subprocess.run(['nvidia-smi', '--query-compute-apps=pid,process_name', '--format=csv,noheader'], capture_output=True, text=True) processes = result.stdout.strip().split('\n') for process in processes: pid, name = process.split(', ') yield int(pid), name.strip() # Example usage for pid, name in iterate_gpu_processes(): print(f"PID: {pid}, Name: {name}")

    Code Description: This Python code utilizes nvidia-smi to query GPU processes and iterates over the results, yielding PID and process name for each running process.

  5. How to check GPU utilization using nvidia-smi in Python?

    Description: This query seeks a method to check GPU utilization using nvidia-smi in Python.

    import subprocess def gpu_utilization(): result = subprocess.run(['nvidia-smi', '--query-gpu=utilization.gpu', '--format=csv,noheader'], capture_output=True, text=True) return float(result.stdout.strip().split('\n')[0].strip().split()[0]) # Example usage print(f"GPU Utilization: {gpu_utilization()}%")

    Code Description: This Python code utilizes nvidia-smi to query GPU utilization and returns the percentage of GPU utilization as a float value.

  6. How to check memory usage on GPU using nvidia-smi in Python?

    Description: This query aims to find a method to check memory usage on GPU using nvidia-smi in Python.

    import subprocess def gpu_memory_usage(): result = subprocess.run(['nvidia-smi', '--query-gpu=memory.used', '--format=csv,noheader,nounits'], capture_output=True, text=True) return int(result.stdout.strip()) # Example usage print(f"GPU Memory Usage: {gpu_memory_usage()} MiB")

    Code Description: This Python code utilizes nvidia-smi to query GPU memory usage and returns the memory used in MiB.

  7. How to monitor GPU temperature using nvidia-smi in Python?

    Description: This query looks for a method to monitor GPU temperature using nvidia-smi in Python.

    import subprocess def gpu_temperature(): result = subprocess.run(['nvidia-smi', '--query-gpu=temperature.gpu', '--format=csv,noheader'], capture_output=True, text=True) return float(result.stdout.strip().split('\n')[0].strip().split()[0]) # Example usage print(f"GPU Temperature: {gpu_temperature()}��C")

    Code Description: This Python code utilizes nvidia-smi to query GPU temperature and returns the temperature in Celsius.

  8. How to find the number of processes running on GPU using nvidia-smi in Python?

    Description: This query aims to find a method to count the number of processes running on GPU using nvidia-smi in Python.

    import subprocess def count_gpu_processes(): result = subprocess.run(['nvidia-smi', '--query-compute-apps=pid', '--format=csv,noheader'], capture_output=True, text=True) return len(result.stdout.strip().split('\n')) # Example usage print(f"Number of GPU Processes: {count_gpu_processes()}")

    Code Description: This Python code utilizes nvidia-smi to query GPU processes and returns the count of processes.

  9. How to filter GPU processes by memory usage using nvidia-smi in Python?

    Description: This query seeks a method to filter GPU processes based on memory usage using nvidia-smi in Python.

    import subprocess def filter_gpu_processes_by_memory(threshold): result = subprocess.run(['nvidia-smi', '--query-compute-apps=pid,used_memory', '--format=csv,noheader'], capture_output=True, text=True) processes = result.stdout.strip().split('\n') filtered_processes = [process.split(', ') for process in processes if int(process.split(', ')[1]) >= threshold] return filtered_processes # Example usage memory_threshold = 100 # MiB, specify your threshold filtered_processes = filter_gpu_processes_by_memory(memory_threshold) print(filtered_processes)

    Code Description: This Python code utilizes nvidia-smi to query GPU processes and filters them based on memory usage, returning processes exceeding the specified threshold.

  10. How to monitor GPU power usage using nvidia-smi in Python?

    Description: This query looks for a method to monitor GPU power usage using nvidia-smi in Python.

    import subprocess def gpu_power_usage(): result = subprocess.run(['nvidia-smi', '--query-gpu=power.draw', '--format=csv,noheader,nounits'], capture_output=True, text=True) return float(result.stdout.strip()) # Example usage print(f"GPU Power Usage: {gpu_power_usage()} W")

    Code Description: This Python code utilizes nvidia-smi to query GPU power usage and returns the power draw in watts.

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