码迷,mamicode.com
首页 > 其他好文 > 详细

NMVL查询显卡信息

时间:2017-05-15 23:43:36      阅读:583      评论:0      收藏:0      [点我收藏+]

标签:环境变量   打开   format   let   pci   str   版本   comm   enum   

        前段时间做英伟达硬解得时候,显卡总是莫名挂掉,后来发现是因为显卡温度过高掉了。这几天找到CUDA中有NVML工具可以查看显卡信息,nvidia-smi也是基于这个工具包。

        使用的CUDA版本为CUDA 8.0 。

1.给程序添加NVML

        安装CUDA之后可以找到如下:

技术分享

图1.NVML的例子

这里面包含的是NVML的一个例子。我的系统是64位的,可以找到NVML的lib和头文件如下:

技术分享

图2.NVML的lib文件

技术分享

图3.NVML头文件

在工程中包含NVML。我是新建的CUDA 8.0 Runtime工程,因为NVML包含在CUDA中,建CUDA 8.0 Runtime工程可以省去CUDA的配置工作,工程建立方法参见VS2013 VC++的.cpp文件调用CUDA的.cu文件中的函数

,CUDA 8.0为默认安装,系统为win10 64位。

        在程序中直接包含NVML的头文件和lib文件即可:

#include "nvml.h"

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

注意64位系统应该建立x64工程,因为在安装的CUDA中没有win32的nvml.lib。

2.NVML查询显卡信息

        常用函数:

        ·nvmlInit()函数初始化NVML;

        ·nvmlDeviceGetCount(unsigned int *deviceCount)函数可以获得显卡数;

        ·nvmlDeviceGetHandleByIndex(unsigned int index, nvmlDevice_t *device)获取设备;

        ·nvmlDeviceGetName(nvmlDevice_t device, char *name, unsigned int length)查询设备的名称;

        ·nvmlDeviceGetPciInfo(nvmlDevice_t device, nvmlPciInfo_t *pci)获取PCI信息,对这个函数的重要性,例子中是这么说的

            // pci.busId is very useful to know which device physically you‘re talking to
            // Using PCI identifier you can also match nvmlDevice handle to CUDA device.

        ·nvmlDeviceGetComputeMode(nvmlDevice_t device, nvmlComputeMode_t *mode)得到显卡当前所处的模式,模式由以下:

typedef enum nvmlComputeMode_enum
{
    NVML_COMPUTEMODE_DEFAULT           = 0,  //!< Default compute mode -- multiple contexts per device
    NVML_COMPUTEMODE_EXCLUSIVE_THREAD  = 1,  //!< Support Removed
    NVML_COMPUTEMODE_PROHIBITED        = 2,  //!< Compute-prohibited mode -- no contexts per device
    NVML_COMPUTEMODE_EXCLUSIVE_PROCESS = 3,  //!< Compute-exclusive-process mode -- only one context per device, usable from multiple threads at a time
   
    // Keep this last
    NVML_COMPUTEMODE_COUNT
} nvmlComputeMode_t;

        ·nvmlDeviceSetComputeMode(nvmlDevice_t device, nvmlComputeMode_t mode)可以修改显卡的模式;

        ·nvmlDeviceGetTemperatureThreshold(nvmlDevice_t device, nvmlTemperatureThresholds_t thresholdType, unsigned int *temp)查询温度阈值,具体有两种:

typedef enum nvmlTemperatureThresholds_enum
{
    NVML_TEMPERATURE_THRESHOLD_SHUTDOWN = 0,    // Temperature at which the GPU will shut down for HW protection
    NVML_TEMPERATURE_THRESHOLD_SLOWDOWN = 1,    // Temperature at which the GPU will begin slowdown
    // Keep this last
    NVML_TEMPERATURE_THRESHOLD_COUNT
} nvmlTemperatureThresholds_t;

当温度达到NVML_TEMPERATURE_THRESHOLD_SHUTDOWN 参数获取的温度时,显卡将自动关闭以保护硬件;当温度达到NVML_TEMPERATURE_THRESHOLD_SLOWDOWN参数获取的温度时,显卡的性能将下降。

        ·nvmlDeviceGetTemperature(nvmlDevice_t device, nvmlTemperatureSensors_t sensorType, unsigned int *temp)获取显卡当前温度;

        ·nvmlDeviceGetUtilizationRates(nvmlDevice_t device, nvmlUtilization_t *utilization)获取设备的使用率(原注释:Retrieves the current utilization rates for the device‘s major subsystems。不知道理解错了没有),使用率包括以下:

typedef struct nvmlUtilization_st
{
    unsigned int gpu;                //!< Percent of time over the past sample period during which one or more kernels was executing on the GPU
    unsigned int memory;             //!< Percent of time over the past sample period during which global (device) memory was being read or written
} nvmlUtilization_t;

        ·nvmlDeviceGetMemoryInfo(nvmlDevice_t device, nvmlMemory_t *memory)    Retrieves the amount of used, free and total memory available on the device, in bytes。

        ·nvmlDeviceGetBAR1MemoryInfo(nvmlDevice_t device, nvmlBAR1Memory_t *bar1Memory)   Gets Total, Available and Used size of BAR1 memory.(不知道这种与上一种有什么区别,有待后续学习)

       ·nvmlDeviceGetComputeRunningProcesses(nvmlDevice_t device, unsigned int *infoCount, nvmlProcessInfo_t *infos)    Get information about processes with a compute context on a device。应该是获取当前在使用显卡的程序信息。

        ·nvmlDeviceGetMaxClockInfo(nvmlDevice_t device, nvmlClockType_t type, unsigned int *clock)   Retrieves the maximum clock speeds for the device。包括以下:

typedef enum nvmlClockType_enum
{
    NVML_CLOCK_GRAPHICS  = 0,        //!< Graphics clock domain
    NVML_CLOCK_SM        = 1,        //!< SM clock domain
    NVML_CLOCK_MEM       = 2,        //!< Memory clock domain
    NVML_CLOCK_VIDEO     = 3,        //!< Video encoder/decoder clock domain
   
    // Keep this last
    NVML_CLOCK_COUNT //<! Count of clock types
} nvmlClockType_t;

        ·nvmlDeviceGetClockInfo(nvmlDevice_t device, nvmlClockType_t type, unsigned int *clock)   Retrieves the current clock speeds for the device.上面是获取最大的,这个是获取当前的。

代码示例:

#include "cuda_kernels.h"

#include "nvml.h"

#include <stdio.h>  
#include <windows.h>  
#include <winbase.h>  
#include <tlhelp32.h>  
#include <psapi.h>   #pragma comment(lib,"kernel32.lib")  
#pragma comment(lib,"advapi32.lib")  

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

const char * convertToComputeModeString(nvmlComputeMode_t mode)
{
    switch (mode)
    {
    case NVML_COMPUTEMODE_DEFAULT:
        return "Default";
    case NVML_COMPUTEMODE_EXCLUSIVE_THREAD:
        return "Exclusive_Thread";
    case NVML_COMPUTEMODE_PROHIBITED:
        return "Prohibited";
    case NVML_COMPUTEMODE_EXCLUSIVE_PROCESS:
        return "Exclusive Process";
    default:
        return "Unknown";
    }
}

int main()
{
    cuAdd();

    nvmlReturn_t result;
    unsigned int device_count, i;

    // First initialize NVML library
    result = nvmlInit();
    if (NVML_SUCCESS != result)
    {
        printf("Failed to initialize NVML: %s\n", nvmlErrorString(result));

        printf("Press ENTER to continue...\n");
        getchar();
        return 1;
    }

    result = nvmlDeviceGetCount(&device_count);
    if (NVML_SUCCESS != result)
    {
        printf("Failed to query device count: %s\n", nvmlErrorString(result));
        goto Error;
    }
    printf("Found %d device%s\n\n", device_count, device_count != 1 ? "s" : "");

    printf("Listing devices:\n");
    while (true)
    {
        for (i = 0; i < device_count; i++)
        {
            nvmlDevice_t device;
            char name[NVML_DEVICE_NAME_BUFFER_SIZE];
            nvmlPciInfo_t pci;
            nvmlComputeMode_t compute_mode;

            // Query for device handle to perform operations on a device
            // You can also query device handle by other features like:
            // nvmlDeviceGetHandleBySerial
            // nvmlDeviceGetHandleByPciBusId
            result = nvmlDeviceGetHandleByIndex(i, &device);
            if (NVML_SUCCESS != result)
            {
                printf("Failed to get handle for device %i: %s\n", i, nvmlErrorString(result));
                goto Error;
            }

            result = nvmlDeviceGetName(device, name, NVML_DEVICE_NAME_BUFFER_SIZE);
            if (NVML_SUCCESS != result)
            {
                printf("Failed to get name of device %i: %s\n", i, nvmlErrorString(result));
                goto Error;
            }

            // pci.busId is very useful to know which device physically you‘re talking to
            // Using PCI identifier you can also match nvmlDevice handle to CUDA device.
            result = nvmlDeviceGetPciInfo(device, &pci);
            if (NVML_SUCCESS != result)
            {
                printf("Failed to get pci info for device %i: %s\n", i, nvmlErrorString(result));
                goto Error;
            }

            printf("%d. %s [%s]\n", i, name, pci.busId);

            // This is a simple example on how you can modify GPU‘s state
            result = nvmlDeviceGetComputeMode(device, &compute_mode);
            if (NVML_ERROR_NOT_SUPPORTED == result)
                printf("\t This is not CUDA capable device\n");
            else if (NVML_SUCCESS != result)
            {
                printf("Failed to get compute mode for device %i: %s\n", i, nvmlErrorString(result));
                goto Error;
            }
            else
            {
                // try to change compute mode
                printf("\t Changing device‘s compute mode from ‘%s‘ to ‘%s‘\n",
                    convertToComputeModeString(compute_mode),
                    convertToComputeModeString(NVML_COMPUTEMODE_PROHIBITED));

                result = nvmlDeviceSetComputeMode(device, NVML_COMPUTEMODE_PROHIBITED);
                if (NVML_ERROR_NO_PERMISSION == result)
                    printf("\t\t Need root privileges to do that: %s\n", nvmlErrorString(result));
                else if (NVML_ERROR_NOT_SUPPORTED == result)
                    printf("\t\t Compute mode prohibited not supported. You might be running on\n"
                    "\t\t windows in WDDM driver model or on non-CUDA capable GPU.\n");
                else if (NVML_SUCCESS != result)
                {
                    printf("\t\t Failed to set compute mode for device %i: %s\n", i, nvmlErrorString(result));
                    goto Error;
                }
                else
                {
                    printf("\t Restoring device‘s compute mode back to ‘%s‘\n",
                        convertToComputeModeString(compute_mode));
                    result = nvmlDeviceSetComputeMode(device, compute_mode);
                    if (NVML_SUCCESS != result)
                    {
                        printf("\t\t Failed to restore compute mode for device %i: %s\n", i, nvmlErrorString(result));
                        goto Error;
                    }
                }
            }

            printf("\n");
            printf("----- 温度 ----- \n");
            unsigned int temperature_threshold = 100;
            result = nvmlDeviceGetTemperatureThreshold(device, NVML_TEMPERATURE_THRESHOLD_SHUTDOWN, &temperature_threshold);
            if (NVML_SUCCESS != result)
            {
                printf("device %i Failed to get NVML_TEMPERATURE_THRESHOLD_SHUTDOWN: %s\n", i, nvmlErrorString(result));
            }
            else
                printf("截止温度: %d 摄氏度  (Temperature at which the GPU will shut down for HW protection)\n", temperature_threshold);

            result = nvmlDeviceGetTemperatureThreshold(device, NVML_TEMPERATURE_THRESHOLD_SLOWDOWN, &temperature_threshold);
            if (NVML_SUCCESS != result)
            {
                printf("device %i Failed NVML_TEMPERATURE_THRESHOLD_SLOWDOWN: %s\n", i, nvmlErrorString(result));
            }
            else
                printf("上限温度: %d 摄氏度  (Temperature at which the GPU will begin slowdown)\n", temperature_threshold);

            unsigned int temperature = 0;
            result = nvmlDeviceGetTemperature(device, NVML_TEMPERATURE_GPU, &temperature);
            if (NVML_SUCCESS != result)
            {
                printf("device %i NVML_TEMPERATURE_GPU Failed: %s\n", i, nvmlErrorString(result));
            }
            else
                printf("当前温度: %d 摄氏度 \n", temperature);

            //使用率
            printf("\n");
            nvmlUtilization_t utilization;
            result = nvmlDeviceGetUtilizationRates(device, &utilization);
            if (NVML_SUCCESS != result)
            {
                printf(" device %i nvmlDeviceGetUtilizationRates Failed : %s\n", i, nvmlErrorString(result));
            }
            else
            {
                printf("----- 使用率 ----- \n");
                printf("GPU 使用率: %lld %% \n", utilization.gpu);
                printf("显存使用率: %lld %% \n", utilization.memory);
            }

            //FB memory
            printf("\n");
            nvmlMemory_t memory;
            result = nvmlDeviceGetMemoryInfo(device, &memory);
            if (NVML_SUCCESS != result)
            {
                printf("device %i nvmlDeviceGetMemoryInfo Failed : %s\n", i, nvmlErrorString(result));
            }
            else
            {
                printf("------ FB memory ------- \n");
                printf("Total installed FB memory: %lld bytes \n", memory.total);
                printf("Unallocated FB memory: %lld bytes \n", memory.free);
                printf("Allocated FB memory: %lld bytes \n", memory.used);
            }

            //BAR1 memory
            printf("\n");
            nvmlBAR1Memory_t bar1Memory;
            result = nvmlDeviceGetBAR1MemoryInfo(device, &bar1Memory);
            if (NVML_SUCCESS != result)
            {
                printf("device %i  nvmlDeviceGetBAR1MemoryInfo Failed : %s\n", i, nvmlErrorString(result));
            }
            else
            {
                printf("------ BAR1 memory ------- \n");
                printf("Total BAR1 memory: %lld bytes \n", bar1Memory.bar1Total);
                printf("Unallocated BAR1 memory: %lld bytes \n", bar1Memory.bar1Free);
                printf("Allocated BAR1 memory: %lld bytes \n", bar1Memory.bar1Used);
            }

            //Information about running compute processes on the GPU
            printf("\n");
            unsigned int infoCount;
            nvmlProcessInfo_t infos[999];
            result = nvmlDeviceGetComputeRunningProcesses(device, &infoCount, infos);
            if (NVML_SUCCESS != result)
            {
                printf("Failed to get ComputeRunningProcesses for device %i: %s\n", i, nvmlErrorString(result));
            }
            else
            {
                HANDLE handle; //定义CreateToolhelp32Snapshot系统快照句柄       
                handle = CreateToolhelp32Snapshot(TH32CS_SNAPPROCESS, 0);//获得系统快照句柄     
                PROCESSENTRY32 *info; //定义PROCESSENTRY32结构字指     
                //PROCESSENTRY32 结构的 dwSize 成员设置成 sizeof(PROCESSENTRY32)      
                info = new PROCESSENTRY32;
                info->dwSize = sizeof(PROCESSENTRY32);
                //调用一次     Process32First 函数,从快照中获取进程列表     
                Process32First(handle, info);
                //重复调用 Process32Next,直到函数返回 FALSE 为止    

                printf("------ Information about running compute processes on the GPU ------- \n");
                for (int i = 0; i < infoCount; i++)
                {
                    printf("PID: %d  显存占用:%lld bytes   ", infos[i].pid, infos[i].usedGpuMemory);

                    while (Process32Next(handle, info) != FALSE)
                    {
                        if (info->th32ProcessID == infos[i].pid)
                        {
                            //printf("  %s\n", info->szExeFile);

                            HANDLE hProcess = NULL;
                            //打开目标进程  
                            hProcess = OpenProcess(PROCESS_QUERY_INFORMATION | PROCESS_VM_READ, FALSE, info->th32ProcessID);
                            if (hProcess == NULL) {
                                printf("\nOpen Process fAiled:%d\n", GetLastError());
                                break;
                            }

                            char strFilePath[MAX_PATH];
                            GetModuleFileNameEx(hProcess, NULL, strFilePath, MAX_PATH);
                            printf(" %s\n", strFilePath);

                            CloseHandle(hProcess);

                            break;
                        }
                    }
                }
                
                delete info;
                CloseHandle(handle);
            }

            //BAR1 memory
            printf("\n");
            printf("------ Clocks ------- \n"); 
            unsigned int max_clock;
            result = nvmlDeviceGetMaxClockInfo(device, NVML_CLOCK_GRAPHICS, &max_clock);
            if (NVML_SUCCESS != result)
            {
                printf("device %i   nvmlDeviceGetMaxClockInfo Failed : %s\n", i, nvmlErrorString(result));
            }

            unsigned int clock;
            result = nvmlDeviceGetClockInfo(device, NVML_CLOCK_GRAPHICS, &clock);
            if (NVML_SUCCESS != result)
            {
                printf("Failed to get NVML_CLOCK_GRAPHICS info for device %i: %s\n", i, nvmlErrorString(result));
            }
            else
            {
                printf("GRAPHICS: %6d Mhz   max clock :%d  \n", clock, max_clock);
            }

            result = nvmlDeviceGetMaxClockInfo(device, NVML_CLOCK_SM, &max_clock);
            if (NVML_SUCCESS != result)
            {
                printf("Failed to get max NVML_CLOCK_SM for device %i: %s\n", i, nvmlErrorString(result));
            }

            result = nvmlDeviceGetClockInfo(device, NVML_CLOCK_SM, &clock);
            if (NVML_SUCCESS != result)
            {
                printf("Failed to get current NVML_CLOCK_SM for device %i: %s\n", i, nvmlErrorString(result));
            }
            else
            {
                printf("      SM: %6d Mhz   max clock :%d   \n", clock, max_clock);
            }

            result = nvmlDeviceGetMaxClockInfo(device, NVML_CLOCK_MEM, &max_clock);
            if (NVML_SUCCESS != result)
            {
                printf("Failed to get max NVML_CLOCK_MEM for device %i: %s\n", i, nvmlErrorString(result));
            }

            result = nvmlDeviceGetClockInfo(device, NVML_CLOCK_MEM, &clock);
            if (NVML_SUCCESS != result)
            {
                printf("Failed to get current NVML_CLOCK_MEM for device %i: %s\n", i, nvmlErrorString(result));
            }
            else
            {
                printf("     MEM: %6d Mhz   max clock :%d   \n", clock, max_clock);
            }

            result = nvmlDeviceGetMaxClockInfo(device, NVML_CLOCK_VIDEO, &max_clock);
            if (NVML_SUCCESS != result)
            {
                printf("Failed to get max NVML_CLOCK_VIDEO for device %i: %s\n", i, nvmlErrorString(result));
            }

            result = nvmlDeviceGetClockInfo(device, NVML_CLOCK_VIDEO, &clock);
            if (NVML_SUCCESS != result)
            {
                printf("Failed to get current NVML_CLOCK_VIDEO for device %i: %s\n", i, nvmlErrorString(result));
            }
            else
            {
                printf("   VIDEO: %6d Mhz   max clock :%d   \n", clock, max_clock);
            }
        }

        printf("-------------------------------------------------------------------- \n");

        Sleep(1000);
    }

Error:
    result = nvmlShutdown();
    if (NVML_SUCCESS != result)
        printf("Failed to shutdown NVML: %s\n", nvmlErrorString(result));

    system("pause");

    return 0;
}

虽然我已经把nvml.dll拷贝到运行目录,程序应该是可以正常运行了。也做一下nvidia-smi的环境配置,参考NVIDIA 显卡信息(CUDA信息的查看),我把他的复制到下面来:

1. nvidia-smi 查看显卡信息

nvidia-smi 指的是 NVIDIA System Management Interface;

在安装完成 NVIDIA 显卡驱动之后,对于 windows 用户而言,cmd 命令行界面还无法识别 nvidia-smi 命令,需要将相关环境变量添加进去。如将 NVIDIA 显卡驱动安装在默认位置,nvidia-smi 命令所在的完整路径应当为:

C:\Program Files\NVIDIA Corporation\NVSMI

也即将上述路径添加进 Path 系统环境变量中。

2. 查看 CUDA 信息

  • CUDA 的版本:
    • 进入命令行:nvcc -V

3.运行结果

技术分享

图4.GeForce 940M查询结果

技术分享

图5.Tesla P4查询结果

        NVML对GeForce 940M的支持不怎么好,对Tesla P4支持得比较好。

 

工程源码:http://download.csdn.net/download/qq_33892166/9841800

NMVL查询显卡信息

标签:环境变量   打开   format   let   pci   str   版本   comm   enum   

原文地址:http://www.cnblogs.com/betterwgo/p/6858806.html

(0)
(0)
   
举报
评论 一句话评论(0
登录后才能评论!
© 2014 mamicode.com 版权所有  联系我们:gaon5@hotmail.com
迷上了代码!