标签 vGPU 下的文章

前言

随着互联网设施的建设和云计算的发展,“云桌面”、“云游戏”等概念已逐渐走入人们的视线。无论如何,它都改变了我们理解硬件性能和游戏体验的方式。本系列文章将介绍如何使用Proxmox VE构建一个简单的,支持Windows、Linux的云桌面系统。

认识vGPU

要为VM添加图形功能,一般有三种方法:

  • 软件模拟(如“标准VGA”,“VMware SVGA II”)
  • PCI Passthrough
  • vGPU(mDev / sr-IOV)

性能为 PCI Passthrough > vGPU > 软件模拟

对于vGPU,市面上有三种方案:

IntelAMDNVIDIA
GVT-gMxGPUNVIDIA vGPU

笔者采用的是NVIDIA Tesla P40这款GPU,故本文只介绍NVIDIA vGPU。

vGPU架构

从上图可以看出,NVIDIA vGPU的实现由软硬件协同而成,硬件上有GPU,软件上有NVIDIA vGPU Manager。

vGPU支持的显卡

一般情况下,vGPU只支持数据中心级的Tesla GPU和部分Quadro GPU,大致如下:

架构型号
MaxwellM6, M10, M60
PascalP4, P6, P40, P100, P100 12GB
VoltaV100
TuringT4, RTX 6000, RTX 6000 passive, RTX 8000, RTX 8000 passive
AmpereA2, A10, A16, A40, RTX A5000, RTX A5500, RTX A6000
AdaL4, L40, RTX 6000 Ada

不过有热心大神开发了解锁补丁,可以在9,10,20系显卡上解锁vGPU功能,具体链接及教程如下:

{% link https://github.com/mbilker/vgpu_unlock-rs %}

{% link https://gitlab.com/polloloco/vgpu-proxmox %}

支持的平台

根据官方文档,目前支持的平台如下:

  • Citrix XenServer
  • Linux with KVM(比如Proxmox VE)
  • Microsoft Azure Stack HCI
  • Microsoft Windows Server(即Hyper-V)
  • Nutanix AHV
  • VMware vSphere ESXi

vGPU类型

NVIDIA官方介绍如下:

  • vCS:NVIDIA 虚拟计算服务器,加速基于 KVM 的基础架构上的虚拟化 AI 计算工作负载。(如GRID P40-1C
  • vWS: NVIDIA RTX 虚拟工作站,适用于使用图形应用程序的创意和技术专业人士的虚拟工作站。(如GRID P40-1Q
  • vPC: NVIDIA 虚拟 PC,适用于使用办公效率应用程序和多媒体的知识工作者的虚拟桌面 (VDI)。(如GRID P40-1B
  • vApp: NVIDIA 虚拟应用程序,采用远程桌面会话主机 (RDSH) 解决方案的应用程序流。(如GRID P40-1A

准备vGPU驱动

{% note color:warning 注意 本文中使用的Proxmox VE版本为8.0.3,内核版本为6.2.16-4-pve %}

移除企业源

Proxmox VE默认使用企业源,如果没有订阅密钥是没有权限访问的

echo "deb https://mirrors.tuna.tsinghua.edu.cn/proxmox/debian bookworm pve-no-subscription" >> /etc/apt/sources.list.d/pve-no-subscription.list
rm /etc/apt/sources.list.d/pve-enterprise.list

更新系统

apt update
apt dist-upgrade
reboot

保证内核为最新版本

安装必要工具

apt install -y git build-essential dkms pve-headers mdevctl

其中dkms保证在每次更新内核后会自动编译适应的驱动模块

启用IOMMU

一般系统

编辑/etc/default/grub,找到GRUB_CMDLINE_LINUX_DEFAULT="quiet",在其后添加:

Intel
intel_iommu=on iommu=pt
AMD
amd_iommu=on iommu=pt

结果应该如下(Intel):

GRUB_CMDLINE_LINUX_DEFAULT="quiet intel_iommu=on iommu=pt"

ZFS上的系统

编辑/etc/kernel/cmdline,找到root=ZFS=rpool/ROOT/pve-1 boot=zfs,在其后添加:

Intel
intel_iommu=on iommu=pt
AMD
amd_iommu=on iommu=pt

结果应该如下(Intel):

root=ZFS=rpool/ROOT/pve-1 boot=zfs intel_iommu=on iommu=pt

现在更新引导配置:

proxmox-boot-tool refresh

禁止nouveau驱动

nouveau是一个开源的NVIDIA显卡驱动,它与vGPU驱动冲突,必须禁用它

echo "blacklist nouveau" >> /etc/modprobe.d/blacklist-nouveau.conf
echo "options nouveau modeset=0" >> /etc/modprobe.d/blacklist-nouveau.conf

加载vfio模块

编辑/etc/modules,添加如下内容:

vfio
vfio_iommu_type1
vfio_pci
vfio_virqfd

更新initramfs

update-initramfs -u -k all

重启

reboot

检查IOMMU是否启用

重启后输入:

dmesg | grep -e DMAR -e IOMMU

在我的C602双路服务器上,它输出以下内容:

{% folding open:false %}

root@pve-r720:~# dmesg | grep -e DMAR -e IOMMU
[    0.000000] Warning: PCIe ACS overrides enabled; This may allow non-IOMMU protected peer-to-peer DMA
[    0.012034] ACPI: DMAR 0x000000007D3346F4 000158 (v01 DELL   PE_SC3   00000001 DELL 00000001)
[    0.012084] ACPI: Reserving DMAR table memory at [mem 0x7d3346f4-0x7d33484b]
[    0.591102] DMAR: IOMMU enabled
[    1.347160] DMAR: Host address width 46
[    1.347161] DMAR: DRHD base: 0x000000d1100000 flags: 0x0
[    1.347168] DMAR: dmar0: reg_base_addr d1100000 ver 1:0 cap d2078c106f0466 ecap f020de
[    1.347170] DMAR: DRHD base: 0x000000dd900000 flags: 0x1
[    1.347175] DMAR: dmar1: reg_base_addr dd900000 ver 1:0 cap d2078c106f0466 ecap f020de
[    1.347177] DMAR: RMRR base: 0x0000007f458000 end: 0x0000007f46ffff
[    1.347178] DMAR: RMRR base: 0x0000007f450000 end: 0x0000007f450fff
[    1.347180] DMAR: RMRR base: 0x0000007f452000 end: 0x0000007f452fff
[    1.347181] DMAR: ATSR flags: 0x0
[    1.347183] DMAR-IR: IOAPIC id 2 under DRHD base  0xd1100000 IOMMU 0
[    1.347185] DMAR-IR: IOAPIC id 0 under DRHD base  0xdd900000 IOMMU 1
[    1.347186] DMAR-IR: IOAPIC id 1 under DRHD base  0xdd900000 IOMMU 1
[    1.347187] DMAR-IR: HPET id 0 under DRHD base 0xdd900000
[    1.347188] DMAR-IR: x2apic is disabled because BIOS sets x2apic opt out bit.
[    1.347189] DMAR-IR: Use 'intremap=no_x2apic_optout' to override the BIOS setting.
[    1.347933] DMAR-IR: Enabled IRQ remapping in xapic mode
[    2.304979] DMAR: No SATC found
[    2.304981] DMAR: dmar0: Using Queued invalidation
[    2.304990] DMAR: dmar1: Using Queued invalidation
[    2.310738] DMAR: Intel(R) Virtualization Technology for Directed I/O

{% endfolding %}

关键在于DMAR: IOMMU enabled一行,此行表明IOMMU已启用。

安装vGPU驱动

{% note color:warning 注意 本节使用535.54.06版驱动,GRID版本为16.0。 %}

Proxmox VE作为KVM平台,自然需要KVM版的vGPU驱动

目前仅有16.0版的vGPU驱动支持新的6.2内核,15.3、15.1等版本最高支持到PVE 7

很不幸,NVIDIA不会让你随便下载高贵的GRID驱动(fuck-you-nvidia.jpg),你需要在这里注册一个免费的vGPU许可来下载驱动。

{% note color:warning 注意 申请免费许可时,请勿使用@gmail.com、@qq.com等免费邮箱,否则可能会面临人工审核,我的建议是使用自己域名的邮箱。 %}

{% note color:green 提示 觉得注册太麻烦?你也可以去佛西大佬的博客下载 %}

下载完成后,解压zip文件,在Host_Drivers文件夹中找到NVIDIA-Linux-x86_64-535.54.06-vgpu-kvm.run,将其上传到Proxmox VE中

在Proxmox VE中执行以下命令:

./NVIDIA-Linux-x86_64-535.54.06-vgpu-kvm.run --dkms

安装完成后,提示是否要注册DKMS模块,一定要选择Yes,这样在升级内核后,系统会重新编译适应新内核的驱动。

{% note color:warning 注意 由于Proxmox VE使用apt update升级系统时不会升级pve-headers,因此务必在升级系统前安装新的pve-headers,避免造成dkms编译失败。 %}

截屏2023-07-17 20.46.33

重启后执行nvidia-smi,在我的双Tesla P40机器上,输出以下内容(无视那些“vgpu”进程):

截屏2023-07-17 20.58.06

执行mdevctl types查看mdev类型:

{% folding open:false %}

root@pve-r720:~# mdevctl types
0000:04:00.0
  nvidia-156
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-2B
    Description: num_heads=4, frl_config=45, framebuffer=2048M, max_resolution=5120x2880, max_instance=12
  nvidia-215
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-2B4
    Description: num_heads=4, frl_config=45, framebuffer=2048M, max_resolution=5120x2880, max_instance=12
  nvidia-241
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-1B4
    Description: num_heads=4, frl_config=45, framebuffer=1024M, max_resolution=5120x2880, max_instance=24
  nvidia-46
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-1Q
    Description: num_heads=4, frl_config=60, framebuffer=1024M, max_resolution=5120x2880, max_instance=24
  nvidia-47
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-2Q
    Description: num_heads=4, frl_config=60, framebuffer=2048M, max_resolution=7680x4320, max_instance=12
  nvidia-48
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-3Q
    Description: num_heads=4, frl_config=60, framebuffer=3072M, max_resolution=7680x4320, max_instance=8
  nvidia-49
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-4Q
    Description: num_heads=4, frl_config=60, framebuffer=4096M, max_resolution=7680x4320, max_instance=6
  nvidia-50
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-6Q
    Description: num_heads=4, frl_config=60, framebuffer=6144M, max_resolution=7680x4320, max_instance=4
  nvidia-51
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-8Q
    Description: num_heads=4, frl_config=60, framebuffer=8192M, max_resolution=7680x4320, max_instance=3
  nvidia-52
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-12Q
    Description: num_heads=4, frl_config=60, framebuffer=12288M, max_resolution=7680x4320, max_instance=2
  nvidia-53
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-24Q
    Description: num_heads=4, frl_config=60, framebuffer=24576M, max_resolution=7680x4320, max_instance=1
  nvidia-54
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-1A
    Description: num_heads=1, frl_config=60, framebuffer=1024M, max_resolution=1280x1024, max_instance=24
  nvidia-55
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-2A
    Description: num_heads=1, frl_config=60, framebuffer=2048M, max_resolution=1280x1024, max_instance=12
  nvidia-56
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-3A
    Description: num_heads=1, frl_config=60, framebuffer=3072M, max_resolution=1280x1024, max_instance=8
  nvidia-57
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-4A
    Description: num_heads=1, frl_config=60, framebuffer=4096M, max_resolution=1280x1024, max_instance=6
  nvidia-58
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-6A
    Description: num_heads=1, frl_config=60, framebuffer=6144M, max_resolution=1280x1024, max_instance=4
  nvidia-59
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-8A
    Description: num_heads=1, frl_config=60, framebuffer=8192M, max_resolution=1280x1024, max_instance=3
  nvidia-60
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-12A
    Description: num_heads=1, frl_config=60, framebuffer=12288M, max_resolution=1280x1024, max_instance=2
  nvidia-61
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-24A
    Description: num_heads=1, frl_config=60, framebuffer=24576M, max_resolution=1280x1024, max_instance=1
  nvidia-62
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-1B
    Description: num_heads=4, frl_config=45, framebuffer=1024M, max_resolution=5120x2880, max_instance=24
0000:42:00.0
  nvidia-156
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-2B
    Description: num_heads=4, frl_config=45, framebuffer=2048M, max_resolution=5120x2880, max_instance=12
  nvidia-215
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-2B4
    Description: num_heads=4, frl_config=45, framebuffer=2048M, max_resolution=5120x2880, max_instance=12
  nvidia-241
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-1B4
    Description: num_heads=4, frl_config=45, framebuffer=1024M, max_resolution=5120x2880, max_instance=24
  nvidia-46
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-1Q
    Description: num_heads=4, frl_config=60, framebuffer=1024M, max_resolution=5120x2880, max_instance=24
  nvidia-47
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-2Q
    Description: num_heads=4, frl_config=60, framebuffer=2048M, max_resolution=7680x4320, max_instance=12
  nvidia-48
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-3Q
    Description: num_heads=4, frl_config=60, framebuffer=3072M, max_resolution=7680x4320, max_instance=8
  nvidia-49
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-4Q
    Description: num_heads=4, frl_config=60, framebuffer=4096M, max_resolution=7680x4320, max_instance=6
  nvidia-50
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-6Q
    Description: num_heads=4, frl_config=60, framebuffer=6144M, max_resolution=7680x4320, max_instance=4
  nvidia-51
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-8Q
    Description: num_heads=4, frl_config=60, framebuffer=8192M, max_resolution=7680x4320, max_instance=3
  nvidia-52
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-12Q
    Description: num_heads=4, frl_config=60, framebuffer=12288M, max_resolution=7680x4320, max_instance=2
  nvidia-53
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-24Q
    Description: num_heads=4, frl_config=60, framebuffer=24576M, max_resolution=7680x4320, max_instance=1
  nvidia-54
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-1A
    Description: num_heads=1, frl_config=60, framebuffer=1024M, max_resolution=1280x1024, max_instance=24
  nvidia-55
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-2A
    Description: num_heads=1, frl_config=60, framebuffer=2048M, max_resolution=1280x1024, max_instance=12
  nvidia-56
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-3A
    Description: num_heads=1, frl_config=60, framebuffer=3072M, max_resolution=1280x1024, max_instance=8
  nvidia-57
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-4A
    Description: num_heads=1, frl_config=60, framebuffer=4096M, max_resolution=1280x1024, max_instance=6
  nvidia-58
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-6A
    Description: num_heads=1, frl_config=60, framebuffer=6144M, max_resolution=1280x1024, max_instance=4
  nvidia-59
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-8A
    Description: num_heads=1, frl_config=60, framebuffer=8192M, max_resolution=1280x1024, max_instance=3
  nvidia-60
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-12A
    Description: num_heads=1, frl_config=60, framebuffer=12288M, max_resolution=1280x1024, max_instance=2
  nvidia-61
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-24A
    Description: num_heads=1, frl_config=60, framebuffer=24576M, max_resolution=1280x1024, max_instance=1
  nvidia-62
    Available instances: 0
    Device API: vfio-pci
    Name: GRID P40-1B
    Description: num_heads=4, frl_config=45, framebuffer=1024M, max_resolution=5120x2880, max_instance=24

{% endfolding %}

配置vGPU授权服务器

众所周知,vGPU的授权费极其昂贵,不是富哥很难承受的起,很长一段时间内,众多玩家采用伪造PCI ID的形式来伪装成Quadro显卡,从而骗过NVIDIA的检测。但目前已经有成熟的开源vGPU许可服务器fastapi-dls可以直接使用了,官方还提供了Docker,这省了许多事。

安装容器

{% note color:green 提示 建议在虚拟机 / LXC中部署此Docker镜像,PVE中直接安装Docker可能会导致VM断网等问题 %}

# 拉取镜像
docker pull collinwebdesigns/fastapi-dls:latest
# 创建目录
mkdir -p /opt/fastapi-dls/cert
cd /opt/fastapi-dls/cert
# 生成公私钥
openssl genrsa -out /opt/fastapi-dls/cert/instance.private.pem 2048 
openssl rsa -in /opt/fastapi-dls/cert/instance.private.pem -outform PEM -pubout -out /opt/fastapi-dls/cert/instance.public.pem
# 生成SSL证书
openssl req -x509 -nodes -days 3650 -newkey rsa:2048 -keyout  /opt/fastapi-dls/cert/webserver.key -out /opt/fastapi-dls/cert/webserver.crt
# 创建容器, 1825是授权天数, YOUR_IP处填VM / LXC的IP
docker volume create dls-db
docker run -d --restart=always -e LEASE_EXPIRE_DAYS=1825 -e DLS_URL=<YOUR_IP> -e DLS_PORT=443 -p 443:443 -v /opt/fastapi-dls/cert:/app/cert -v dls-db:/app/database collinwebdesigns/fastapi-dls:latest

自此,vGPU配置完成!

参考资料

NVIDIA Virtual GPU Software Documentation

佛西博客 - 在Proxmox VE 7.2 中开启vGPU_unlock,实现显卡虚拟化 (buduanwang.vip)

PolloLoco / NVIDIA vGPU Guide · GitLab

oscar.krause/fastapi-dls: Minimal Delegated License Service (DLS). This is a mirrored repo from https://git.collinwebdesigns.de/oscar.krause/fastapi-dls. - fastapi-dls - Gitea (publichub.eu)

collinwebdesigns/fastapi-dls - Docker Image | Docker Hub