View source for GPU passthrough to virtual machines

Using a GPU reduces the load on the CPUs and RAM.  I saw /dev/shm at 50% and load about 30-50% what it was before deploying a NVidia GTX 1050.  

==Nvidia GPU in VMware==
The versions shown here are essential because it did not work at all prior to some updates, crashed the host and the VM would not start.  The versions are the latest current at the present [[User:Gerdesj|Gerdesj]] ([[User talk:Gerdesj|talk]]) 17:29, 6 August 2020 (UTC).

* Host: Dell T320, 1 socket Xeon E5-2407 2.2 GHz CPU, BIOS 2.9.0
* VMware: ESXI 6.5.0 patch level 16576891
* GPU: MSI Geforce GTX 1050 Ti (this card does not require any host BIOS settings changing, nor Memory Mapped I/O settings on the VM)
* Cameras: Four Reolink RLC-520.  Encoding at 2048 x 1536, 10 fps, High H.264 profile
* VM: Ubuntu 20.04 LTS server with no extras. Four vCPUs, 6 GB RAM, 30GB root and EFI, 300GB XFS for /var
* Zoneminder: 1.34

===ESXi host===
ssh into the host and edit /etc/vmware/passthru.map.  Change the word bridge to link.  This avoids a PSOD on the host when restarting the VM with the GPU passed through to it. See: https://www.reddit.com/r/vmware/comments/f3xsgj/nvidia_gpu_esx_65_dell_t320_pci_passthrough_crash/

 # NVIDIA
 10de  ffff  link   false

Pass the GPU through to the host using the DirectPath I/O mechanism  and reboot, then connect both devices to the VM.  There will be an audio card and the video card itself.  see: https://blogs.vmware.com/apps/2018/09/using-gpus-with-virtual-machines-on-vsphere-part-2-vmdirectpath-i-o.html

===Ubuntu 20.04 VM===
The VM must use EFI so the install must use the Ubuntu server installer and not the minimal installer which will not work with efiboot.  VM type set to Ubuntu 64 bit.

In Advanced settings for the VM, set the following flag to false. This setting disables informing the VM it is a VM.  This avoids a problem where the GPU fails to initialise properly:

 hypervisor.cpuid.v0 = FALSE

====Nvidia drivers and CUDA====
These instructions stay within the drivers etc provided by Ubuntu 20.04 LTS. NVidia as upstream also provide drivers and these will be newer but may break something.  The OS provided ffmpeg has cuda support built in.

Use this command to decide which driver to install:

 # ubuntu-drivers devices

(Update: 450 version works as well. [[User:Gerdesj|Gerdesj]] ([[User talk:Gerdesj|talk]]) 14:55, 22 October 2020 (UTC))

Install the "headless" version of the driver and reboot:
 # apt install nvidia-headless-440

Run this to confirm it is working after rebooting:
 # nvidia-smi

If you just need decoding eg for Zoneminder - this provides ''libnvcuvid.so'':
 # apt install libnvidia-decode-440

===Testing===
Check ffmpeg has cuda support:
 # ffmpeg -hwaccels
 ffmpeg version 4.2.4-1ubuntu0.1 Copyright (c) 2000-2020 the FFmpeg developers
 ...
 Hardware acceleration methods:
 vdpau
 cuda
 vaapi
 drm
 opencl
 cuvid

There should be no error messages relating to libraries when you run something like this, which streams from a camera to /dev/null and uses CUDA:

 # ffmpeg -hwaccel cuda -i "rtmp://HOSTNAME_OR_IP/bcs/channel0_main.bcs?channel=0&stream=0&user=admin&password=PASSWORD"  -an -f rawvideo -y /dev/null

In another console, you could run nvidia-smi and see a process using the GPU.

== Camera Settings ==

Camera parameters for reference. Reolinks have three streams - main, sub and ext.  main is the clear stream and sub is the lowest quality one.  These cameras also have a RTSP stream but that appears to be pretty flakey compared to RTMP.  I want to watch these cameras so I monitor at high resolution.  If you are building a security system then monitor sub and record main.  Monitoring at say 640 x 480 will allow you to run a huge number of cameras.
{| class="wikitable"
!Parameter
!Value
|-
|Model
|Reolink RLC-520
|-
| colspan="2" |'''General'''
|-
|Source Type
|Ffmpeg
|-
| colspan="2" |'''Source'''
|-
|Method
|TCP
|-
|Options
|n/a
|-
|Source Path
|rtmp://HOSTNAME_OR_IP/bcs/channel0_'''main'''.bcs?channel=0&stream=0&user=admin&password=PASSWORD
|-
|DecoderHWAccelName
|cuda
|-
|Target colorspace
|32 bit colour
|-
|Capture Width
|2048
|-
|Capture Height
|1536
|-
| colspan="2" |'''Storage'''
|-
|Save JPEGs
|Frames + Analysis images (if available)
|-
|Video Writer
|H264 Camera Passthrough
|}