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获取显卡状态信息

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使用 NVIDIA 管理库 NVML 获取 GPU 利用率

简介

NVIDIA Management Library (NVML) 随 CUDA 一起发布，是一个基于 C 代码的 API，用于兼用和管理 NVIDIA GPU 设备的各种状态。简单的使用获取显示显卡利用率。

代码

命令行

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:: 查询显卡使用情况信息
nvidia-smi
:: 查询可用设备
nvidia-smi -L

C++

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#include "nvml.h"

#pragma comment(lib,"nvml.lib")

int main()
{
	nvmlReturn_t result;
	unsigned int device_count, i;
	// First initialize NVML library
	result = nvmlInit();

	result = nvmlDeviceGetCount(&device_count);
	if (NVML_SUCCESS != result)
	{
		std::cout << "Failed to query device count: " << nvmlErrorString(result);
	}
	std::cout << "Found" << device_count << " device" << endl;

	std::cout << "Listing devices:";
	while (true)
	{
		for (i = 0; i < device_count; i++)
		{
			nvmlDevice_t device;
			result = nvmlDeviceGetHandleByIndex(i, &device);
			if (NVML_SUCCESS != result) {
				std::cout << "get device failed " << endl;
				continue;
			}

			char name[NVML_DEVICE_NAME_BUFFER_SIZE];
			result = nvmlDeviceGetName(device, name, NVML_DEVICE_NAME_BUFFER_SIZE);
			if (NVML_SUCCESS == result) {
				std::cout << "GPU name： " << name << endl;
			}

			char uuid[NVML_DEVICE_UUID_BUFFER_SIZE];
			result = nvmlDeviceGetUUID(device, uuid, NVML_DEVICE_UUID_BUFFER_SIZE);
			if (NVML_SUCCESS == result) {
				std::cout << "GPU uuid： " << uuid << endl;
			}

			//使用率
			nvmlUtilization_t utilization;
			result = nvmlDeviceGetUtilizationRates(device, &utilization);
			if (NVML_SUCCESS == result)
			{
				std::cout << "----- 使用率 ----- " << endl;
				std::cout << "GPU 使用率： " << utilization.gpu << endl;
				std::cout << "显存使用率 " << utilization.memory << endl;
			}
		}
		Sleep(1000);
	}
	return 0;
}

C#

使用 C# 调用 NVML 需要额外封装 nvml.dll 库。
参考 nvml-csharp 库封装一个简单的帮助类，仅用于获取 GPU 与显存使用率。

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/// <summary>
/// 显卡利用率统计
/// </summary>
public class NvmlStateHelper
{
    /// <summary>
    /// NVML 库名称
    /// </summary>
    const string NVML_SHARED_LIBRARY_STRING = "nvml.dll";

    /// <summary>
    /// Buffer size guaranteed to be large enough for \ref nvmlDeviceGetName
    /// </summary>
    const int NVML_DEVICE_NAME_BUFFER_SIZE = 64;

    /// <summary>
    /// Buffer size guaranteed to be large enough for \ref nvmlDeviceGetUUID
    /// </summary>
    const int NVML_DEVICE_UUID_BUFFER_SIZE = 80;

    /// <summary>
    /// 初始化 NVML 库
    /// </summary>
    /// <returns></returns>
    [DllImport(NVML_SHARED_LIBRARY_STRING, EntryPoint = "nvmlInit_v2")]
    internal static extern NvmlReturn NvmlInitV2();

    /// <summary>
    /// 获取显卡数量
    /// </summary>
    /// <param name="deviceCount"></param>
    /// <returns></returns>
    [DllImport(NVML_SHARED_LIBRARY_STRING, CharSet = CharSet.Ansi, EntryPoint = "nvmlDeviceGetCount_v2")]
    internal static extern NvmlReturn NvmlDeviceGetCount_v2(out uint deviceCount);

    /// <summary>
    /// 获取显卡句柄
    /// </summary>
    /// <param name="index"></param>
    /// <param name="device"></param>
    /// <returns></returns>
    [DllImport(NVML_SHARED_LIBRARY_STRING, EntryPoint = "nvmlDeviceGetHandleByIndex")]
    internal static extern NvmlReturn NvmlDeviceGetHandleByIndex(uint index, out IntPtr device);

    /// <summary>
    /// 获取显卡名称
    /// </summary>
    /// <param name="device"></param>
    /// <param name="name"></param>
    /// <param name="length"></param>
    /// <returns></returns>
    [DllImport(NVML_SHARED_LIBRARY_STRING, CharSet = CharSet.Ansi, EntryPoint = "nvmlDeviceGetName")]
    internal static extern NvmlReturn NvmlDeviceGetName(IntPtr device, [Out, MarshalAs(UnmanagedType.LPArray)] byte[] name, uint length);

    /// <summary>
    /// 获取显卡 UUID
    /// </summary>
    /// <param name="device"></param>
    /// <param name="uuid"></param>
    /// <param name="length"></param>
    /// <returns></returns>
    [DllImport(NVML_SHARED_LIBRARY_STRING, CharSet = CharSet.Ansi, EntryPoint = "nvmlDeviceGetUUID")]
    internal static extern NvmlReturn NvmlDeviceGetUUID(IntPtr device, [Out, MarshalAs(UnmanagedType.LPArray)] byte[] uuid, uint length);

    /// <summary>
    /// 获取显卡使用率信息
    /// </summary>
    /// <param name="device"></param>
    /// <param name="utilization"></param>
    /// <returns></returns>
    [DllImport(NVML_SHARED_LIBRARY_STRING, CharSet = CharSet.Ansi, EntryPoint = "nvmlDeviceGetUtilizationRates")]
    internal static extern NvmlReturn NvmlDeviceGetUtilizationRates(IntPtr device, out NvmlUtilization utilization);

    /// <summary>
    /// 关闭调用
    /// </summary>
    /// <returns></returns>
    [DllImport(NVML_SHARED_LIBRARY_STRING, EntryPoint = "nvmlShutdown")]
    internal static extern NvmlReturn NvmlShutdown();

    /// <summary>
    /// 获取显卡全局使用率
    /// </summary>
    /// <param name="gpuCount"></param>
    /// <exception cref="SystemException"></exception>
    public NvmlStateHelper(uint gpuCount = 0)
    {
        Task.Run(() =>
        {
            NvmlReturn res = NvmlInitV2();
            if (NvmlReturn.NVML_SUCCESS != res)
            {
                //throw new SystemException(res.ToString());
                return;
            }

            var device = IntPtr.Zero;
            res = NvmlDeviceGetHandleByIndex(gpuCount, out device);
            if (NvmlReturn.NVML_SUCCESS != res)
            {
                //throw new SystemException(res.ToString());
                return;
            }

            // 获取显卡名称
            byte[] bufferName = new byte[NVML_DEVICE_NAME_BUFFER_SIZE];
            res = NvmlDeviceGetName(device, bufferName, NVML_DEVICE_NAME_BUFFER_SIZE);
            if (NvmlReturn.NVML_SUCCESS == res)
            {
                var gpuName = Encoding.Default.GetString(bufferName).Replace("\0", "");
            }

            // 获取显卡 UUID
            byte[] bufferUUID = new byte[NVML_DEVICE_UUID_BUFFER_SIZE];
            res = NvmlDeviceGetUUID(device, bufferUUID, NVML_DEVICE_UUID_BUFFER_SIZE);
            if (NvmlReturn.NVML_SUCCESS == res)
            {
                var gpuUUID = Encoding.Default.GetString(bufferUUID).Replace("\0", "");
            }

            // 获取 GPU 与显存使用率
            while (true)
            {
                try
                {
                    NvmlUtilization nvmlUtilization;
                    res = NvmlDeviceGetUtilizationRates(device, out nvmlUtilization);
                    if (NvmlReturn.NVML_SUCCESS != res)
                    {
                        //throw new SystemException(res.ToString());
                        return;
                    }

                    GpuChange?.Invoke(nvmlUtilization.gpu);
                    MemoryChange?.Invoke(nvmlUtilization.memory);
                }
                catch (Exception)
                {
                    // 获取信息失败
                }

                Thread.Sleep(1000);
            }
        });
    }

    /// <summary>
    /// Gpu 使用率
    /// </summary>
    public event Action<uint> GpuChange;

    /// <summary>
    /// 显存使用率
    /// </summary>
    public event Action<uint> MemoryChange;
}

/// <summary>
/// NVML 返回值类型
/// </summary>
public enum NvmlReturn
{
    NVML_SUCCESS = 0,
    NVML_ERROR_UNINITIALIZED,
    NVML_ERROR_INVALID_ARGUMENT,
    NVML_ERROR_NOT_SUPPORTED,
    NVML_ERROR_NO_PERMISSION,
    NVML_ERROR_ALREADY_INITIALIZED,
    NVML_ERROR_NOT_FOUND,
    NVML_ERROR_INSUFFICIENT_SIZE,
    NVML_ERROR_INSUFFICIENT_POWER,
    NVML_ERROR_DRIVER_NOT_LOADED,
    NVML_ERROR_TIMEOUT,
    NVML_ERROR_IRQ_ISSUE,
    NVML_ERROR_LIBRARY_NOT_FOUND,
    NVML_ERROR_FUNCTION_NOT_FOUND,
    NVML_ERROR_CORRUPTED_INFOROM,
    NVML_ERROR_GPU_IS_LOST,
    NVML_ERROR_RESET_REQUIRED,
    NVML_ERROR_OPERATING_SYSTEM,
    NVML_ERROR_LIB_RM_VERSION_MISMATCH,
    NVML_ERROR_IN_USE,
    NVML_ERROR_MEMORY,
    NVML_ERROR_NO_DATA,
    NVML_ERROR_VGPU_ECC_NOT_SUPPORTED,
    NVML_ERROR_INSUFFICIENT_RESOURCES,
    NVML_ERROR_UNKNOWN = 999
}

/// <summary>
/// 显卡使用率信息模型
/// </summary>
public struct NvmlUtilization
{
    public uint gpu { get; }
    public uint memory { get; }
}