NVIDIA GPU开源驱动编译学习&架构分析

时间:2023-02-08 11:51:26

2022年5月,社区终于等到了这一天,NVIDIA开源了他们的LINUX GPU 内核驱动, Linux 内核总设计师 Linus Torvalds 十年前说过的一句话,大概意思是英伟达是LINUX开发者遇到的硬件厂商中最麻烦的一个,说完这句话之后,祖师爷毫不客气的朝着镜头竖了中指并表达了对NVIDIA身体某些部分的亲切问候。关于祖师爷和NVIDIA那点恩怨咱不清楚,也没啥兴趣,不过单纯看开源这个行为还是喜闻乐见的。下面在UBUNTU系统上建立NVIDIA GPU驱动的编译和开发环境。

平台环境

PC装有NVIDIA GForce MX250显卡,是低端入门级的,不过用来跑跑CUDA,编译内核是足够了。

NVIDIA GPU开源驱动编译学习&架构分析

开源驱动下载

代码托管在github上,连接为:

https://github.com/NVIDIA/open-gpu-kernel-modules.git
NVIDIA GPU开源驱动编译学习&架构分析

查看提交记录发现,驱动是从515.43.04版本开始开源,当前最新的版本为525.85.12.

编译

执行命令

make -j8

进行编译

NVIDIA GPU开源驱动编译学习&架构分析

编译结果为:

./kernel-open/nvidia-uvm.ko
./kernel-open/nvidia-drm.ko
./kernel-open/nvidia.ko
./kernel-open/nvidia-peermem.ko
./kernel-open/nvidia-modeset.ko
NVIDIA GPU开源驱动编译学习&架构分析

安装

执行如下命令进行安装

sudo insmod nvidia.ko
NVIDIA GPU开源驱动编译学习&架构分析

提示检测不到设备,开始不得其解,后面查阅开源仓库的README,才发现MX250GPU不再支持列表,所以也就没有办法使用自己编译的NVIDIA内核驱动驱动GPU了。

LICENSE

查看代码中的LICENSE声明,发现开源代码使用双 GPL/MIT 许可。

NVIDIA GPU开源驱动编译学习&架构分析

而这个许可,是可以通过内核GPL兼容性检查的,不会污染内核。

NVIDIA GPU开源驱动编译学习&架构分析

NVIDIA GPU 公版内核

虽然开源仓库的代码不支持MX250,UBUNTU系统安装后,在/usr/src目录下,存在另一个GPU显卡驱动目录,以我当前的环境为例,它是/usr/src/nvidia-525.78.01/

NVIDIA GPU开源驱动编译学习&架构分析

编译方法有两种:

  1. 在目录下直接 make,结果产生和上面一样的几个KO文件。

  1. 通过dkms编译:

$ sudo dkms build -m nvidia -v 525.78.01
$ sudo dkms install -m nvidia -v 525.78.01
NVIDIA GPU开源驱动编译学习&架构分析
NVIDIA GPU开源驱动编译学习&架构分析

安装驱动,可以看到,UBUNTU系统自带的NVIDIA驱动源码编译出来的KO是可以正常加载的,加载nvidia.ko后,系统中出现了/dev/nvidia和/dev/nvidiactl两个节点。

NVIDIA GPU开源驱动编译学习&架构分析

安装nvidia-uvm.ko后,系统中又出现了两个新的节点/dev/nvidia-uvm-tools和/dev/nvidia-uvm

NVIDIA GPU开源驱动编译学习&架构分析

由于依赖关系,下一步需要首先安装nvidia-modeset.ko,否则,直接安装其它两个模块会报错,KMS没有产生新的设备节点。

NVIDIA GPU开源驱动编译学习&架构分析

nvidia-drm.ko貌似也没有创建新的设备节点

NVIDIA GPU开源驱动编译学习&架构分析

开源策略

至于为何存在两套发布方式目前还不得而知。但是经过分析,发现UBUNTU系统自带的代码并非完全开源,协议也非上面使用的双GPL/MIT。

NVIDIA GPU开源驱动编译学习&架构分析

并且存在两个闭源二进制库文件,后缀名为.o_binary的nv-kernel.o_binary和nv-modeset-kernel.o_binary

NVIDIA GPU开源驱动编译学习&架构分析
NVIDIA GPU开源驱动编译学习&架构分析

KMS:

NVIDIA GPU开源驱动编译学习&架构分析

编译时的连接过程

NVIDIA GPU开源驱动编译学习&架构分析

.o_binary中的符号甚至都进行了加密

NVIDIA GPU开源驱动编译学习&架构分析

并且安装KO后,/sys/module/nvidia/taint文件内容为POE,表示内核受到了非GPL协议的代码的污染。

NVIDIA GPU开源驱动编译学习&架构分析
NVIDIA GPU开源驱动编译学习&架构分析
A kernel problem occurred, but your kernel has been tainted (flags:POE). Explanation:
P - Proprietary module has been loaded.
O - Out-of-tree module has been loaded.
E - Unsigned module has been loaded.
Kernel maintainers are unable to diagnose tainted reports. Tainted modules: nvidia_drm,nvidia_modeset,nvidia_uvm,nvidia,vboxne tadp,vboxnetflt,vboxdrv. 

所以这样看起来,UBUNTU自带的驱动是闭源无疑的了,不符合开源协议。

另一些发现

后面查看开源代码的构建文件Makefile发现,关于.o_bianry的产生过程也存在于开源代码中,并且开源代码也可以产生.o_binary文件:

NVIDIA GPU开源驱动编译学习&架构分析
NVIDIA GPU开源驱动编译学习&架构分析
NVIDIA GPU开源驱动编译学习&架构分析

make kernel-open/nvidia/nv-kernel.o_binary

NVIDIA GPU开源驱动编译学习&架构分析

所以这样来看,在UBUNTU系统中没有开源的内容,在开源仓库中是能找到对应代码的,并且UBUNTU自带的驱动版本号为525.78.01,和开源仓库最新版非常接近。所以如果纠着闭源的部分不放可能有些吹毛求疵了,毕竟人家在开源仓库中是有开源的。除了部分显卡不支持外,开源仓库的代码没有什么毛病。

设备节点是如何创建的?

通过前面的实验可以看到NVIDA驱动并不神秘,它就是普通的字符设备或者DRM设备,而DRM设备本质上也是字符设备。

NVIDIA GPU开源驱动编译学习&架构分析
NVIDIA GPU开源驱动编译学习&架构分析
NVIDIA GPU开源驱动编译学习&架构分析
NVIDIA GPU开源驱动编译学习&架构分析

字符设备节点创建一般是通过UEVENT机制实现的,内核需要调用device_create和class_create,前者用于创建内核设备结构体,并提供设备节点名称,后者产生 /sys/class/xxxx目录下的一些列文件,用于用户态mdev或者udev查询并且创建设备节点之用。

但是经过grep代码发现,内核中并没有调用这两个接口。

NVIDIA GPU开源驱动编译学习&架构分析

而前面我们看到,在安装nvidia.ko之后,设备节点/dev/nvidia0立刻便出现了,这不可能是巧合,缺少了class_create和device_create的纽带,设备节点是如何产生的呢?

分析,首先我们用重新编译的内核,在内核中添加打印,反正我们基本确定一定是用户态调用mknod完成创建设备节点的操作,而mknod是通过系统调用实现的,我们在系统调用的必经之路上加入LOG,查看创建调用mknod创建节点的进程名,PID,父进程名,父进程ID。

NVIDIA GPU开源驱动编译学习&架构分析

运行加载后,dmesg发现果然拦截到了创建节点的操作。

NVIDIA GPU开源驱动编译学习&架构分析

原来,节点是一个名称被叫做ub-device-creat,PID为2859,父进程为systemd-udevd,PID为2853.的进程创建的。前者暂且不提,后者对熟悉内核启动的同学应该并不模式,它是systemv启动表中中的一个重要进程,专门负责监听系统中的UVENT事件,在捕捉到对应事件后,创建设备节点。所以看起来NVIDIA GPU设备节点的创建过程讲的通了。systemd-udevd监听到内核发出的设备驱动加载事件,创建进程ub-device-creat调用mknod创建设备节点。

口说无凭,究竟ub-device-creat是什么呢,我们locate一下,发现其是系统文件中的一个命令程序

NVIDIA GPU开源驱动编译学习&架构分析

并且并不是脚本程序,而是一个ELF文件,既然是ELF文件,就一定有对应的C源码。最终在GITHUBS行找到了,它是UBUNTU发行版的

https://github.com/NVIDIA/ubuntu-packaging-nvidia-driver/blob/main/debian/device-create/ub-device-create.c

It belongs to the device-create package of nvidia gpu driver release on ubuntu.

NVIDIA GPU开源驱动编译学习&架构分析
NVIDIA GPU开源驱动编译学习&架构分析
NVIDIA GPU开源驱动编译学习&架构分析

可以看到,其逻辑就是创建设备节点,设备节点好是写死的,不需要event传,所以EVENT只是起到一个通知的作用。

NVIDIA GPU开源驱动编译学习&架构分析

The makefile of this project will compile the ub-device-create.c to elf binary ub-device-tree tool.

NVIDIA GPU开源驱动编译学习&架构分析

我们可以写一个获取EVENT的应用,看一下插入瞬间,内核发出的EVENT长什么样子。

#include <stdio.h>  
#include <stdlib.h>  
#include <string.h>  
#include <ctype.h>  
#include <sys/un.h>  
#include <sys/ioctl.h>  
#include <sys/socket.h>  
#include <linux/types.h>  
#include <linux/netlink.h>  
#include <errno.h>  
#include <unistd.h>  
#include <arpa/inet.h>  
#include <netinet/in.h>  

#ifndef NEWLINE
#define NEWLINE "\r\n"
#endif

#define UEVENT_BUFFER_SIZE 2048  

static int init_hotplug_sock()  
{  
  const int buffersize = 1024;  
  int ret;  

  struct sockaddr_nl snl;  
  bzero(&snl, sizeof(struct sockaddr_nl));  
  snl.nl_family = AF_NETLINK;  
  snl.nl_pid = getpid();  
  snl.nl_groups = 1;  

  int s = socket(PF_NETLINK, SOCK_DGRAM, NETLINK_KOBJECT_UEVENT);  
  if (s == -1)   
  {  
      perror("socket");  
      return -1;  
  }  
  setsockopt(s, SOL_SOCKET, SO_RCVBUF, &buffersize, sizeof(buffersize));  

  ret = bind(s, (struct sockaddr *)&snl, sizeof(struct sockaddr_nl));  
  if (ret < 0)   
  {  
      perror("bind");  
      close(s);  
      return -1;  
  }  

  return s;  
}  

char *truncate_nl(char *s) {

        s[strcspn(s, NEWLINE)] = 0;
        return s;
}

int device_new_from_nulstr(uint8_t *nulstr, size_t len) {
        int i = 0;
        int r;

        while (i < len) {
                char *key;
                const char *end;

                key = (char*)&nulstr[i];
                end = memchr(key, '\0', len - i);
                if (!end)
                    return 0;

                i += end - key + 1;
                truncate_nl(key);
                printf("%s\n", key);    
        }
}    

int main(int argc, char* argv[])  
{  
    int hotplug_sock = init_hotplug_sock();  
    int bufpos;

      while(1)  
      {  
        int len;
          /* Netlink message buffer */  
          char buf[UEVENT_BUFFER_SIZE * 2];

        memset(&buf, 0x00, sizeof(buf));    
          len = recv(hotplug_sock, &buf, sizeof(buf), 0);
        
        if (len <= 0)
            continue;
        
        printf("\nnew message:\n");
        bufpos = strlen(buf) + 1;
        
        printf("%s\n", buf);

        device_new_from_nulstr((uint8_t*)&buf[bufpos], len - bufpos);
      }
      return 0;  
 }

上面程序抓去到insmod时的EVENT MSG如下:

NVIDIA GPU开源驱动编译学习&架构分析

UEVENT在内核中的发送堆栈

[   73.389413] kobject_uevent_net_broadcast line 414, action_String = add.
[   73.389419] CPU: 6 PID: 2906 Comm: insmod Tainted: P           OE     5.15.90+ #5
[   73.389422] Hardware name: TIMI RedmiBook 14/TM1814, BIOS RMRWL400P0503 11/13/2019
[   73.389423] Call Trace:
[   73.389426]  <TASK>
[   73.389429]  dump_stack_lvl+0x4a/0x6b
[   73.389436]  dump_stack+0x10/0x18
[   73.389440]  kobject_uevent_env+0x5c1/0x820
[   73.389446]  kobject_uevent+0xb/0x20
[   73.389449]  driver_register+0xd7/0x110
[   73.389453]  __pci_register_driver+0x68/0x80
[   73.389458]  nvswitch_init.cold+0xef/0x17d [nvidia]
[   73.389822]  nvidia_init_module+0x33b/0x63f [nvidia]
[   73.390055]  ? nvidia_init_module+0x63f/0x63f [nvidia]
[   73.390292]  nvidia_frontend_init_module+0x53/0xa7 [nvidia]
[   73.390523]  ? nvidia_init_module+0x63f/0x63f [nvidia]
[   73.390753]  do_one_initcall+0x46/0x1f0
[   73.390757]  ? kmem_cache_alloc_trace+0x19e/0x2f0
[   73.390762]  do_init_module+0x52/0x260
[   73.390765]  load_module+0x2b87/0x2c40
[   73.390767]  ? ima_post_read_file+0xea/0x110
[   73.390773]  __do_sys_finit_module+0xc2/0x130
[   73.390775]  ? __do_sys_finit_module+0xc2/0x130
[   73.390778]  __x64_sys_finit_module+0x18/0x30
[   73.390780]  do_syscall_64+0x59/0x90
[   73.390784]  ? do_syscall_64+0x69/0x90
[   73.390786]  ? do_syscall_64+0x69/0x90
[   73.390789]  entry_SYSCALL_64_after_hwframe+0x61/0xcb
[   73.390792] RIP: 0033:0x7fb1e23bba3d
[   73.390795] Code: 5b 41 5c c3 66 0f 1f 84 00 00 00 00 00 f3 0f 1e fa 48 89 f8 48 89 f7 48 89 d6 48 89 ca 4d 89 c2 4d 89 c8 4c 8b 4c 24 08 0f 05 <48> 3d 01 f0 ff ff 73 01 c3 48 8b 0d c3 a3 0f 00 f7 d8 64 89 01 48
[   73.390797] RSP: 002b:00007ffde1c29128 EFLAGS: 00000246 ORIG_RAX: 0000000000000139
[   73.390800] RAX: ffffffffffffffda RBX: 0000563d89599770 RCX: 00007fb1e23bba3d
[   73.390801] RDX: 0000000000000000 RSI: 0000563d88b7bcd2 RDI: 0000000000000003
[   73.390802] RBP: 0000000000000000 R08: 0000000000000000 R09: 0000000000000000
[   73.390804] R10: 0000000000000003 R11: 0000000000000246 R12: 0000563d88b7bcd2
[   73.390805] R13: 0000563d8959cab0 R14: 0000563d88b7a888 R15: 0000563d89599880
[   73.390808]  </TASK>
[   73.391955] nvidia 0000:02:00.0: enabling device (0106 -> 0107)
[   73.508328] kobject_uevent_net_broadcast line 414, action_String = bind.
[   73.508331] CPU: 6 PID: 2906 Comm: insmod Tainted: P           OE     5.15.90+ #5
[   73.508333] Hardware name: TIMI RedmiBook 14/TM1814, BIOS RMRWL400P0503 11/13/2019
[   73.508334] Call Trace:
[   73.508336]  <TASK>
[   73.508338]  dump_stack_lvl+0x4a/0x6b
[   73.508345]  dump_stack+0x10/0x18
[   73.508348]  kobject_uevent_env+0x5c1/0x820
[   73.508352]  ? insert_work+0x8a/0xb0
[   73.508356]  ? __queue_work+0x211/0x4a0
[   73.508359]  ? __cond_resched+0x1a/0x60
[   73.508362]  kobject_uevent+0xb/0x20
[   73.508364]  driver_bound+0xb0/0x100
[   73.508393]  really_probe+0x2d3/0x430
[   73.508394]  __driver_probe_device+0x12a/0x1b0
[   73.508396]  driver_probe_device+0x23/0xd0
[   73.508398]  __driver_attach+0x10f/0x210
[   73.508399]  ? __device_attach_driver+0x160/0x160
[   73.508401]  bus_for_each_dev+0x80/0xe0
[   73.508404]  driver_attach+0x1e/0x30
[   73.508405]  bus_add_driver+0x153/0x220
[   73.508406]  driver_register+0x95/0x110
[   73.508408]  __pci_register_driver+0x68/0x80
[   73.508411]  nv_pci_register_driver+0x3a/0x50 [nvidia]
[   73.508842]  nvidia_init_module+0x4bf/0x63f [nvidia]
[   73.509020]  ? nvidia_init_module+0x63f/0x63f [nvidia]
[   73.509196]  nvidia_frontend_init_module+0x53/0xa7 [nvidia]
[   73.509372]  ? nvidia_init_module+0x63f/0x63f [nvidia]
[   73.509547]  do_one_initcall+0x46/0x1f0
[   73.509550]  ? kmem_cache_alloc_trace+0x19e/0x2f0
[   73.509554]  do_init_module+0x52/0x260
[   73.509556]  load_module+0x2b87/0x2c40
[   73.509558]  ? ima_post_read_file+0xea/0x110
[   73.509562]  __do_sys_finit_module+0xc2/0x130
[   73.509564]  ? __do_sys_finit_module+0xc2/0x130
[   73.509566]  __x64_sys_finit_module+0x18/0x30
[   73.509568]  do_syscall_64+0x59/0x90
[   73.509571]  ? do_syscall_64+0x69/0x90
[   73.509572]  ? do_syscall_64+0x69/0x90
[   73.509574]  entry_SYSCALL_64_after_hwframe+0x61/0xcb
[   73.509577] RIP: 0033:0x7fb1e23bba3d
[   73.509579] Code: 5b 41 5c c3 66 0f 1f 84 00 00 00 00 00 f3 0f 1e fa 48 89 f8 48 89 f7 48 89 d6 48 89 ca 4d 89 c2 4d 89 c8 4c 8b 4c 24 08 0f 05 <48> 3d 01 f0 ff ff 73 01 c3 48 8b 0d c3 a3 0f 00 f7 d8 64 89 01 48
[   73.509581] RSP: 002b:00007ffde1c29128 EFLAGS: 00000246 ORIG_RAX: 0000000000000139
[   73.509583] RAX: ffffffffffffffda RBX: 0000563d89599770 RCX: 00007fb1e23bba3d
[   73.509584] RDX: 0000000000000000 RSI: 0000563d88b7bcd2 RDI: 0000000000000003
[   73.509585] RBP: 0000000000000000 R08: 0000000000000000 R09: 0000000000000000
[   73.509586] R10: 0000000000000003 R11: 0000000000000246 R12: 0000563d88b7bcd2
[   73.509587] R13: 0000563d8959cab0 R14: 0000563d88b7a888 R15: 0000563d89599880
[   73.509589]  </TASK>
[   73.509602] kobject_uevent_net_broadcast line 414, action_String = add.
[   73.509603] CPU: 6 PID: 2906 Comm: insmod Tainted: P           OE     5.15.90+ #5
[   73.509606] Hardware name: TIMI RedmiBook 14/TM1814, BIOS RMRWL400P0503 11/13/2019
[   73.509607] Call Trace:
[   73.509608]  <TASK>
[   73.509609]  dump_stack_lvl+0x4a/0x6b
[   73.509632]  dump_stack+0x10/0x18
[   73.509635]  kobject_uevent_env+0x5c1/0x820
[   73.509638]  kobject_uevent+0xb/0x20
[   73.509640]  driver_register+0xd7/0x110
[   73.509643]  __pci_register_driver+0x68/0x80
[   73.509646]  nv_pci_register_driver+0x3a/0x50 [nvidia]
[   73.509794]  nvidia_init_module+0x4bf/0x63f [nvidia]
[   73.510072]  ? nvidia_init_module+0x63f/0x63f [nvidia]
[   73.510295]  nvidia_frontend_init_module+0x53/0xa7 [nvidia]
[   73.510484]  ? nvidia_init_module+0x63f/0x63f [nvidia]
[   73.510671]  do_one_initcall+0x46/0x1f0
[   73.510675]  ? kmem_cache_alloc_trace+0x19e/0x2f0
[   73.510677]  do_init_module+0x52/0x260
[   73.510680]  load_module+0x2b87/0x2c40
[   73.510681]  ? ima_post_read_file+0xea/0x110
[   73.510685]  __do_sys_finit_module+0xc2/0x130
[   73.510687]  ? __do_sys_finit_module+0xc2/0x130
[   73.510690]  __x64_sys_finit_module+0x18/0x30
[   73.510691]  do_syscall_64+0x59/0x90
[   73.510693]  ? do_syscall_64+0x69/0x90
[   73.510695]  ? do_syscall_64+0x69/0x90
[   73.510697]  entry_SYSCALL_64_after_hwframe+0x61/0xcb
[   73.510699] RIP: 0033:0x7fb1e23bba3d
[   73.510701] Code: 5b 41 5c c3 66 0f 1f 84 00 00 00 00 00 f3 0f 1e fa 48 89 f8 48 89 f7 48 89 d6 48 89 ca 4d 89 c2 4d 89 c8 4c 8b 4c 24 08 0f 05 <48> 3d 01 f0 ff ff 73 01 c3 48 8b 0d c3 a3 0f 00 f7 d8 64 89 01 48
[   73.510702] RSP: 002b:00007ffde1c29128 EFLAGS: 00000246 ORIG_RAX: 0000000000000139
[   73.510705] RAX: ffffffffffffffda RBX: 0000563d89599770 RCX: 00007fb1e23bba3d
[   73.510707] RDX: 0000000000000000 RSI: 0000563d88b7bcd2 RDI: 0000000000000003
[   73.510708] RBP: 0000000000000000 R08: 0000000000000000 R09: 0000000000000000
[   73.510709] R10: 0000000000000003 R11: 0000000000000246 R12: 0000563d88b7bcd2
[   73.510710] R13: 0000563d8959cab0 R14: 0000563d88b7a888 R15: 0000563d89599880
[   73.510712]  </TASK>
[   73.510724] NVRM: loading NVIDIA UNIX x86_64 Kernel Module  525.78.01  Mon Dec 26 05:58:42 UTC 2022
[   73.510737] kobject_uevent_net_broadcast line 414, action_String = add.
[   73.510739] CPU: 6 PID: 2906 Comm: insmod Tainted: P           OE     5.15.90+ #5
[   73.510742] Hardware name: TIMI RedmiBook 14/TM1814, BIOS RMRWL400P0503 11/13/2019
[   73.510743] Call Trace:
[   73.510744]  <TASK>
[   73.510745]  dump_stack_lvl+0x4a/0x6b
[   73.510750]  dump_stack+0x10/0x18
[   73.510753]  kobject_uevent_env+0x5c1/0x820
[   73.510755]  ? mutex_lock+0x13/0x50
[   73.510758]  kobject_uevent+0xb/0x20
[   73.510759]  do_init_module+0x88/0x260
[   73.510761]  load_module+0x2b87/0x2c40
[   73.510762]  ? ima_post_read_file+0xea/0x110
[   73.510766]  __do_sys_finit_module+0xc2/0x130
[   73.510768]  ? __do_sys_finit_module+0xc2/0x130
[   73.510771]  __x64_sys_finit_module+0x18/0x30
[   73.510772]  do_syscall_64+0x59/0x90
[   73.510774]  ? do_syscall_64+0x69/0x90
[   73.510776]  ? do_syscall_64+0x69/0x90
[   73.510779]  entry_SYSCALL_64_after_hwframe+0x61/0xcb
[   73.510782] RIP: 0033:0x7fb1e23bba3d
[   73.510783] Code: 5b 41 5c c3 66 0f 1f 84 00 00 00 00 00 f3 0f 1e fa 48 89 f8 48 89 f7 48 89 d6 48 89 ca 4d 89 c2 4d 89 c8 4c 8b 4c 24 08 0f 05 <48> 3d 01 f0 ff ff 73 01 c3 48 8b 0d c3 a3 0f 00 f7 d8 64 89 01 48
[   73.510785] RSP: 002b:00007ffde1c29128 EFLAGS: 00000246 ORIG_RAX: 0000000000000139
[   73.510786] RAX: ffffffffffffffda RBX: 0000563d89599770 RCX: 00007fb1e23bba3d
[   73.510787] RDX: 0000000000000000 RSI: 0000563d88b7bcd2 RDI: 0000000000000003
[   73.510788] RBP: 0000000000000000 R08: 0000000000000000 R09: 0000000000000000
[   73.510789] R10: 0000000000000003 R11: 0000000000000246 R12: 0000563d88b7bcd2
[   73.510790] R13: 0000563d8959cab0 R14: 0000563d88b7a888 R15: 0000563d89599880
[   73.510792]  </TASK>
[   73.521876] do_mknodat line 3848, node name /dev/nvidiactl, dev = 0xc3ff, comm ub-device-creat, pid 2915.
[   73.521883] do_mknodat line 3850, node name /dev/nvidiactl, dev = 0xc3ff, comm ub-device-creat, pid 2915, parent comm systemd-udevd, parent pid 2910.
[   73.521937] do_mknodat line 3848, node name /dev/nvidia0, dev = 0xc300, comm ub-device-creat, pid 2915.
[   73.521940] do_mknodat line 3850, node name /dev/nvidia0, dev = 0xc300, comm ub-device-creat, pid 2915, parent comm systemd-udevd, parent pid 2910.

结束