DVA3221 loader development thread

Orphée · March 13, 2022

Hello

Under @yanjun's control, here is a dedicated thread for the DVA3221 loader.

Here is the part you need to add to custom_config.json to handle this loader

              {
                    "id": "denverton-7.0.1-42218",
                    "platform_version": "denverton-7.0.1-42218",
                    "user_config_json": "denverton_user_config.json",
                    "docker_base_image": "debian:8-slim",
                    "redpill_lkm_make_target": "dev-v7",
                    "compile_with": "toolkit_dev",
                    "downloads": {
                            "kernel": {
          "url": "https://global.download.synology.com/download/ToolChain/Synology%20NAS%20GPL%20Source/7.0-41890/denverton/linux-4.4.x.txz",
                    "sha256": "7fe8e92ebf0a2fd30da10867d5165ae00b10b0a316286465ae9831ed3b598f0f"

                            },
                            "toolkit_dev": {
                                    "url": "https://sourceforge.net/projects/dsgpl/files/toolkit/DSM7.0/ds.denverton-7.0.dev.txz/download",
                                    "sha256": "6dc6818bad28daff4b3b8d27b5e12d0565b65ee60ac17e55c36d913462079f57"
                            }
                    },
                    "redpill_lkm": {
                            "source_url": "https://github.com/dogodefi/redpill-lkm.git",
                            "branch": "develop"
                    },
                    "redpill_load": {
                            "source_url": "https://github.com/dogodefi/redpill-load.git",
                            "branch": "develop"
                    }
            },

@yanjun and @pocopico updated their repository with fixes so it should currently work as long as you respect usual prerequisites.

The test I already made :

Surveillance Station Advanced AI features works with a Nvidia GTX1650 GPU (same as official DVA3221 GPU).

Some infos :

- I don't know if Surveillance Station AI features works without a real SN/mac. i don't know if it will work with another GPU than GTX 1650.

- Surveillance Station is able to run without any GPU and still work for standard camera features like normal NAS, but has 8 licences available instead of 2 (but logs will flood in /var/log/messages and /var/log/kern.log about missing GPU, maybe a risk of heavy log generation and disk space).

I was able to run the loader on Proxmox VE virtual machine with GPU passthrough working.

BUT there are some prerequisites : https://pve.proxmox.com/wiki/Pci_passthrough

I personnally had to configure GRUB boot menu like this : GRUB_CMDLINE_LINUX_DEFAULT="quiet intel_iommu=on iommu=pt pcie_acs_override=downstream,multifunction video=efifb:off"

Update :

With Proxmox 7.2 I had to change me GRUB boot menu like this : GRUB_CMDLINE_LINUX_DEFAULT="quiet intel_iommu=on iommu=pt pcie_acs_override=downstream,multifunction initcall_blacklist=sysfb_init"

I did not test on VMWare ESXi.

The loader also works on baremetal (currently running on my system)

On baremetal you may need to request to add DVA3221 for missing ext/modules here :

Until @buggy25200 is able to update his repo, or @pocopico to add acpi ext module, you will find it there :

./rploader.sh ext denverton-7.0.1-42218 add https://raw.githubusercontent.com/OrpheeGT/redpill-ext/master/acpid/rpext-index.json

Thanks to @yanjun @pocopico @buggy25200 @jumkey @IG-88 and all others I could miss/forget for their work on this loader

Edited November 14, 2022 by Orphée

PaulEvo · March 14, 2022

Hello all,

Thanks a lot to all who contributed to the work on a loader for the DVA3221, magnificient. I think I can answer some of the questions which where mentioned by Orphée.

In a Proxmox 7 environment I have a DVA3221 running for 2 days. Motherboard is an Asrock H370 with a i3 8th gen. The loader was build in Tinycore (and before that in TOSSP toolchain). The serial/mac was generated there as well.

My first test was with a GTX1050 card which was recognised in DSM7.0.1 u3. In the log file however was a continous fault message: segvault Synodvad, error 4 in libdvacore.dll. No AI functionality.

Replacing it with a GTX1650 works flawless. No fault messages anymore and AI (video deep learning) is working. It recognises peoples, cars, license plates. It has 8 camera licenses, and I have 2 camera's active at this moment. Both with AI. Hope this gives some answers.

Regards, Paul

Edited March 14, 2022 by PaulEvo
typo

Orphée · March 14, 2022

Hello all,

Thanks a lot to all who contributed to the work on a loader for the DVA3221, magnificient. I think I can answer some of the questions which where mentioned by Orphée.
In a Proxmox 7 environment I have a DVA3622 running for 2 days. Motherboard is an Asrock H370 with a i3 8th gen. The loader was build in Tinycore (and before that in TSSOP toolchain). The serial/mac was generated there as well.
My first test was with a GTX1050 card which was recognised in DSM7.0.1 u3. In the log file however was a continous fault message: segvault Synodvad, error 4 in libdvacore.dll. No AI functionality.
Replacing it with a GTX1650 works flawless. No fault messages anymore and AI (video deep learning) is working. It recognises peoples, cars, license plates. It has 8 camera licenses, and I have 2 camera's active at this moment. Both with AI. Hope this gives some answers.

Regards, Paul

Great !
You probably mistyped and wanted to refer to DVA3221 ? I don't know any DVA3622.

But from your statement :

- Generated SN/mac is not a problem with AI advanced features !
- Did not work with a GTX1050, so it may confirm it only works with a GTX1650, need more tests with other cards (like 2060/3080 etc...)

PaulEvo · March 14, 2022

Hello Orphée,

Indeed the right type is DVA3221 and I corrected it. And your conclusions are correct. Thanks for al your information like the passthrough for the GPU in Proxmox. That helped me a lot in getting it operational!

Orphée · March 14, 2022

Regarding the log flood without the Nvidia GPU, I remember @flyrides topic to suppress logs :

Maybe with some help we could apply the same kind of solution.

It would be helfull for those who only want the 8 camera licence availability and don't care about advanced AI features.

Orphée · March 14, 2022

New info :

DVA3221 loader is not compatible with CPU older than haswell (same as DS918+ loader).

I tried to run in on HP Gen8 Proxmox VM and just after boot, Hard lockup CPU.

I wanted to edit the first post to keep it up-to-date but it seems I can't... @nicoueron .. ? Thanks

Edited March 14, 2022 by Orphée

Orphée · March 14, 2022

Another news :

I tried to run nvidia-smi / cuda under docker.

I took this post as reference :

I downloaded only docker.tar.xz file and deployed it as described in the post above.

I updated the config.toml file :

# cat /etc/nvidia-container-runtime/config.toml 
disable-require = false
#swarm-resource = "DOCKER_RESOURCE_GPU"
#accept-nvidia-visible-devices-envvar-when-unprivileged = true
#accept-nvidia-visible-devices-as-volume-mounts = false

[nvidia-container-cli]
#root = "/var/services/homes/admin/nvidia/NVIDIA-Linux-x86_64-440.44"
path = "/usr/bin/nvidia-container-cli"
environment = []
debug = "/var/log/nvidia-container-toolkit.log"
ldcache = "/etc/ld.so.cache"
load-kmods = true
#no-cgroups = false
user = "root:videodriver"
ldconfig = "@/opt/bin/ldconfig"

[nvidia-container-runtime]
debug = "/var/log/nvidia-container-runtime.log"

restarted docker package and tried docker run command, first exec is from original DVA3221 nvidia system, second one is from docker :

root@DVA3221:/etc/nvidia-container-runtime# nvidia-smi 
Mon Mar 14 22:46:02 2022       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.44       Driver Version: 440.44       CUDA Version: 10.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 1650    On   | 00000000:01:00.0 Off |                  N/A |
| 40%   56C    P0    41W /  75W |   1957MiB /  3908MiB |     45%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|    0     18969      C   ...anceStation/target/synodva/bin/synodvad  1004MiB |
|    0     18970      C   ...ceStation/target/synoface/bin/synofaced   942MiB |
+-----------------------------------------------------------------------------+
root@DVA3221:/etc/nvidia-container-runtime# docker run --gpus all nvidia/cuda:10.2-runtime nvidia-smi
Mon Mar 14 21:46:09 2022       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.44       Driver Version: 440.44       CUDA Version: 10.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 1650    On   | 00000000:01:00.0 Off |                  N/A |
| 40%   57C    P0    31W /  75W |   1957MiB /  3908MiB |     43%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
+-----------------------------------------------------------------------------+

It seems to work, if you have a better/real test to confirm HW acceleration works on docker, please tell me (I don't have plex pass account, I can't test Plex HW acceleration)

Logs from nvidia-toolkit :

# cat nvidia-container-toolkit.log 

-- WARNING, the following logs are for debugging purposes only --

I0314 21:55:13.260863 28027 nvc.c:372] initializing library context (version=1.5.1, build=)
I0314 21:55:13.260881 28027 nvc.c:346] using root /
I0314 21:55:13.260885 28027 nvc.c:347] using ldcache /etc/ld.so.cache
I0314 21:55:13.260887 28027 nvc.c:348] using unprivileged user 0:937
I0314 21:55:13.260898 28027 nvc.c:389] attempting to load dxcore to see if we are running under Windows Subsystem for Linux (WSL)
I0314 21:55:13.260935 28027 nvc.c:391] dxcore initialization failed, continuing assuming a non-WSL environment
I0314 21:55:13.263206 28034 nvc.c:274] loading kernel module nvidia
I0314 21:55:13.263314 28034 nvc.c:278] running mknod for /dev/nvidiactl
I0314 21:55:13.263335 28034 nvc.c:282] running mknod for /dev/nvidia0
I0314 21:55:13.263348 28034 nvc.c:286] running mknod for all nvcaps in /dev/nvidia-caps
I0314 21:55:13.263353 28034 nvc.c:292] loading kernel module nvidia_uvm
I0314 21:55:13.263405 28034 nvc.c:296] running mknod for /dev/nvidia-uvm
I0314 21:55:13.263433 28034 nvc.c:301] loading kernel module nvidia_modeset
E0314 21:55:13.266258 28034 nvc.c:303] could not load kernel module nvidia_modeset
I0314 21:55:13.266397 28036 driver.c:101] starting driver service
I0314 21:55:13.267357 28027 nvc_container.c:388] configuring container with 'compute utility supervised'
I0314 21:55:13.267493 28027 nvc_container.c:236] selecting /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/local/cuda-10.2/compat/libcuda.so.440.118.02  
I0314 21:55:13.267516 28027 nvc_container.c:236] selecting /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/local/cuda-10.2/compat/libnvidia-fatbinaryloader.so.440.118.02
I0314 21:55:13.267528 28027 nvc_container.c:236] selecting /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/local/cuda-10.2/compat/libnvidia-ptxjitcompiler.so.440.118.02
I0314 21:55:13.267588 28027 nvc_container.c:408] setting pid to 28021
I0314 21:55:13.267591 28027 nvc_container.c:409] setting rootfs to /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549
I0314 21:55:13.267594 28027 nvc_container.c:410] setting owner to 0:0
I0314 21:55:13.267597 28027 nvc_container.c:411] setting bins directory to /usr/bin
I0314 21:55:13.267599 28027 nvc_container.c:412] setting libs directory to /usr/lib/x86_64-linux-gnu
I0314 21:55:13.267602 28027 nvc_container.c:413] setting libs32 directory to /usr/lib/i386-linux-gnu
I0314 21:55:13.267605 28027 nvc_container.c:414] setting cudart directory to /usr/local/cuda
I0314 21:55:13.267607 28027 nvc_container.c:415] setting ldconfig to @/opt/bin/ldconfig (host relative)
I0314 21:55:13.267610 28027 nvc_container.c:416] setting mount namespace to /proc/28021/ns/mnt
I0314 21:55:13.267613 28027 nvc_container.c:418] setting devices cgroup to /sys/fs/cgroup/devices/docker/665bd7b6e7f2c9f452b1b9edf9bad588a2ba5b3ffcb349d35bf62cb6452af411
I0314 21:55:13.267617 28027 nvc_info.c:758] requesting driver information with ''
I0314 21:55:13.268274 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libvdpau_nvidia.so.440.44
I0314 21:55:13.268485 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-tls.so.440.44
I0314 21:55:13.268570 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-ptxjitcompiler.so.440.44
I0314 21:55:13.268648 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-opencl.so.440.44
I0314 21:55:13.268698 28027 nvc_info.c:171] selecting /usr/lib/libnvidia-ml.so.440.44
I0314 21:55:13.268751 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-ifr.so.440.44
I0314 21:55:13.268849 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-glsi.so.440.44
I0314 21:55:13.268930 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-glcore.so.440.44
I0314 21:55:13.269014 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-fbc.so.440.44
I0314 21:55:13.269094 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-fatbinaryloader.so.440.44
I0314 21:55:13.269172 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-encode.so.440.44
I0314 21:55:13.269250 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-eglcore.so.440.44
I0314 21:55:13.269329 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-compiler.so.440.44
I0314 21:55:13.269406 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-cfg.so.440.44
I0314 21:55:13.269484 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvcuvid.so.440.44
I0314 21:55:13.269632 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libcuda.so.440.44
I0314 21:55:13.269735 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libGLX_nvidia.so.440.44
I0314 21:55:13.269816 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libGLESv2_nvidia.so.440.44
I0314 21:55:13.269894 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libGLESv1_CM_nvidia.so.440.44
I0314 21:55:13.269974 28027 nvc_info.c:171] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libEGL_nvidia.so.440.44
W0314 21:55:13.270022 28027 nvc_info.c:397] missing library libnvidia-nscq.so
W0314 21:55:13.270026 28027 nvc_info.c:397] missing library libnvidia-allocator.so
W0314 21:55:13.270029 28027 nvc_info.c:397] missing library libnvidia-ngx.so
W0314 21:55:13.270031 28027 nvc_info.c:397] missing library libnvidia-opticalflow.so
W0314 21:55:13.270034 28027 nvc_info.c:397] missing library libnvidia-rtcore.so
W0314 21:55:13.270037 28027 nvc_info.c:397] missing library libnvoptix.so
W0314 21:55:13.270039 28027 nvc_info.c:397] missing library libnvidia-glvkspirv.so
W0314 21:55:13.270042 28027 nvc_info.c:397] missing library libnvidia-cbl.so
W0314 21:55:13.270044 28027 nvc_info.c:401] missing compat32 library libnvidia-ml.so
W0314 21:55:13.270047 28027 nvc_info.c:401] missing compat32 library libnvidia-cfg.so
W0314 21:55:13.270050 28027 nvc_info.c:401] missing compat32 library libnvidia-nscq.so
W0314 21:55:13.270052 28027 nvc_info.c:401] missing compat32 library libcuda.so
W0314 21:55:13.270055 28027 nvc_info.c:401] missing compat32 library libnvidia-opencl.so
W0314 21:55:13.270058 28027 nvc_info.c:401] missing compat32 library libnvidia-ptxjitcompiler.so
W0314 21:55:13.270060 28027 nvc_info.c:401] missing compat32 library libnvidia-fatbinaryloader.so
W0314 21:55:13.270063 28027 nvc_info.c:401] missing compat32 library libnvidia-allocator.so
W0314 21:55:13.270066 28027 nvc_info.c:401] missing compat32 library libnvidia-compiler.so
W0314 21:55:13.270068 28027 nvc_info.c:401] missing compat32 library libnvidia-ngx.so
W0314 21:55:13.270071 28027 nvc_info.c:401] missing compat32 library libvdpau_nvidia.so
W0314 21:55:13.270073 28027 nvc_info.c:401] missing compat32 library libnvidia-encode.so
W0314 21:55:13.270076 28027 nvc_info.c:401] missing compat32 library libnvidia-opticalflow.so
W0314 21:55:13.270079 28027 nvc_info.c:401] missing compat32 library libnvcuvid.so
W0314 21:55:13.270081 28027 nvc_info.c:401] missing compat32 library libnvidia-eglcore.so
W0314 21:55:13.270084 28027 nvc_info.c:401] missing compat32 library libnvidia-glcore.so
W0314 21:55:13.270086 28027 nvc_info.c:401] missing compat32 library libnvidia-tls.so
W0314 21:55:13.270089 28027 nvc_info.c:401] missing compat32 library libnvidia-glsi.so
W0314 21:55:13.270092 28027 nvc_info.c:401] missing compat32 library libnvidia-fbc.so
W0314 21:55:13.270094 28027 nvc_info.c:401] missing compat32 library libnvidia-ifr.so
W0314 21:55:13.270097 28027 nvc_info.c:401] missing compat32 library libnvidia-rtcore.so
W0314 21:55:13.270102 28027 nvc_info.c:401] missing compat32 library libnvoptix.so
W0314 21:55:13.270105 28027 nvc_info.c:401] missing compat32 library libGLX_nvidia.so
W0314 21:55:13.270107 28027 nvc_info.c:401] missing compat32 library libEGL_nvidia.so
W0314 21:55:13.270110 28027 nvc_info.c:401] missing compat32 library libGLESv2_nvidia.so
W0314 21:55:13.270112 28027 nvc_info.c:401] missing compat32 library libGLESv1_CM_nvidia.so
W0314 21:55:13.270115 28027 nvc_info.c:401] missing compat32 library libnvidia-glvkspirv.so
W0314 21:55:13.270118 28027 nvc_info.c:401] missing compat32 library libnvidia-cbl.so
I0314 21:55:13.270159 28027 nvc_info.c:297] selecting /usr/bin/nvidia-smi
I0314 21:55:13.270342 28027 nvc_info.c:297] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/bin/nvidia-debugdump
I0314 21:55:13.270378 28027 nvc_info.c:297] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/bin/nvidia-persistenced
I0314 21:55:13.270421 28027 nvc_info.c:297] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/bin/nvidia-cuda-mps-control
I0314 21:55:13.270459 28027 nvc_info.c:297] selecting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/bin/nvidia-cuda-mps-server
W0314 21:55:13.270462 28027 nvc_info.c:423] missing binary nv-fabricmanager
W0314 21:55:13.270472 28027 nvc_info.c:347] missing firmware path /lib/firmware/nvidia/440.44
I0314 21:55:13.270482 28027 nvc_info.c:520] listing device /dev/nvidiactl
I0314 21:55:13.270485 28027 nvc_info.c:520] listing device /dev/nvidia-uvm
I0314 21:55:13.270488 28027 nvc_info.c:520] listing device /dev/nvidia-uvm-tools
I0314 21:55:13.270491 28027 nvc_info.c:520] listing device /dev/nvidia-modeset
W0314 21:55:13.270501 28027 nvc_info.c:347] missing ipc path /var/run/nvidia-persistenced/socket
W0314 21:55:13.270509 28027 nvc_info.c:347] missing ipc path /var/run/nvidia-fabricmanager/socket
W0314 21:55:13.270517 28027 nvc_info.c:347] missing ipc path /tmp/nvidia-mps
I0314 21:55:13.270520 28027 nvc_info.c:814] requesting device information with ''
I0314 21:55:13.275986 28027 nvc_info.c:705] listing device /dev/nvidia0 (GPU-1e98e62a-69f7-80ee-a2d2-ea047ddb96d2 at 00000000:01:00.0)
I0314 21:55:13.276022 28027 nvc_mount.c:344] mounting tmpfs at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/proc/driver/nvidia
I0314 21:55:13.276256 28027 nvc_mount.c:112] mounting /usr/bin/nvidia-smi at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/bin/nvidia-smi
I0314 21:55:13.276293 28027 nvc_mount.c:112] mounting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/bin/nvidia-debugdump at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/bin/nvidia-debugdump
I0314 21:55:13.276329 28027 nvc_mount.c:112] mounting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/bin/nvidia-persistenced at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/bin/nvidia-persistenced
I0314 21:55:13.276390 28027 nvc_mount.c:112] mounting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/bin/nvidia-cuda-mps-control at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/bin/nvidia-cuda-mps-control
I0314 21:55:13.276428 28027 nvc_mount.c:112] mounting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/bin/nvidia-cuda-mps-server at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/bin/nvidia-cuda-mps-server
I0314 21:55:13.276496 28027 nvc_mount.c:112] mounting /usr/lib/libnvidia-ml.so.440.44 at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/lib/x86_64-linux-gnu/libnvidia-ml.so.440.44
I0314 21:55:13.276531 28027 nvc_mount.c:112] mounting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-cfg.so.440.44 at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/lib/x86_64-linux-gnu/libnvidia-cfg.so.440.44
I0314 21:55:13.276577 28027 nvc_mount.c:112] mounting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libcuda.so.440.44 at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/lib/x86_64-linux-gnu/libcuda.so.440.44
I0314 21:55:13.276610 28027 nvc_mount.c:112] mounting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-opencl.so.440.44 at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/lib/x86_64-linux-gnu/libnvidia-opencl.so.440.44
I0314 21:55:13.276643 28027 nvc_mount.c:112] mounting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-ptxjitcompiler.so.440.44 at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/lib/x86_64-linux-gnu/libnvidia-ptxjitcompiler.so.440.44
I0314 21:55:13.276676 28027 nvc_mount.c:112] mounting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-fatbinaryloader.so.440.44 at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/lib/x86_64-linux-gnu/libnvidia-fatbinaryloader.so.440.44
I0314 21:55:13.276724 28027 nvc_mount.c:112] mounting /volume1/@appstore/NVIDIARuntimeLibrary/nvidia/lib/libnvidia-compiler.so.440.44 at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/lib/x86_64-linux-gnu/libnvidia-compiler.so.440.44
I0314 21:55:13.276740 28027 nvc_mount.c:524] creating symlink /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/usr/lib/x86_64-linux-gnu/libcuda.so -> libcuda.so.1
I0314 21:55:13.276798 28027 nvc_mount.c:208] mounting /dev/nvidiactl at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/dev/nvidiactl
I0314 21:55:13.276815 28027 nvc_mount.c:499] whitelisting device node 195:255
I0314 21:55:13.276836 28027 nvc_mount.c:208] mounting /dev/nvidia-uvm at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/dev/nvidia-uvm
I0314 21:55:13.276847 28027 nvc_mount.c:499] whitelisting device node 246:0
I0314 21:55:13.276866 28027 nvc_mount.c:208] mounting /dev/nvidia-uvm-tools at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/dev/nvidia-uvm-tools
I0314 21:55:13.276878 28027 nvc_mount.c:499] whitelisting device node 246:1
I0314 21:55:13.276900 28027 nvc_mount.c:208] mounting /dev/nvidia0 at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/dev/nvidia0
I0314 21:55:13.276940 28027 nvc_mount.c:412] mounting /proc/driver/nvidia/gpus/0000:01:00.0 at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549/proc/driver/nvidia/gpus/0000:01:00.0
I0314 21:55:13.276954 28027 nvc_mount.c:499] whitelisting device node 195:0
I0314 21:55:13.276963 28027 nvc_ldcache.c:354] executing /opt/bin/ldconfig from host at /volume1/@docker/btrfs/subvolumes/8bbb7889d383ef416dd4f81b0e02627dcbb71050b87c3161dd15ebd62b235549
W0314 21:55:13.288949 1 nvc_ldcache.c:324] seccomp is disabled, all syscalls are allowed
I0314 21:55:14.574998 28027 nvc.c:423] shutting down library context
I0314 21:55:14.575440 28036 driver.c:163] terminating driver service
I0314 21:55:14.575656 28027 driver.c:203] driver service terminated successfully

Edited March 14, 2022 by Orphée

Orphée · March 15, 2022

Following @Zowlverein 's posts regarding HW acceleration/transcoding :

I installed ffmpeg SynoCommunity package.

Took his modified package and extracted it.

I overwritten default /var/packages/ffmpeg/target/ with his modified package.

Installed jellyfin portable, installed ASP dotnet runtime

And I launched a movie from my Firefox Browser :

As you can see, 6 CPU cores are quite low, and the flow is transcoded, and ffmpeg shown in nvidia-smi !

I will probably never use it, but I wanted to confirm if it was possible.

Edited March 15, 2022 by Orphée

jahsoul · March 15, 2022

19 hours ago, PaulEvo said:

Hello all,

Thanks a lot to all who contributed to the work on a loader for the DVA3221, magnificient. I think I can answer some of the questions which where mentioned by Orphée.

In a Proxmox 7 environment I have a DVA3221 running for 2 days. Motherboard is an Asrock H370 with a i3 8th gen. The loader was build in Tinycore (and before that in TOSSP toolchain). The serial/mac was generated there as well.

My first test was with a GTX1050 card which was recognised in DSM7.0.1 u3. In the log file however was a continous fault message: segvault Synodvad, error 4 in libdvacore.dll. No AI functionality.

Replacing it with a GTX1650 works flawless. No fault messages anymore and AI (video deep learning) is working. It recognises peoples, cars, license plates. It has 8 camera licenses, and I have 2 camera's active at this moment. Both with AI. Hope this gives some answers.

Regards, Paul

I wonder if the GTX1050 failed on the basis of having Pascal cores and the 1650 having Turing or if it is a case where they somehow hardcoded the 1650 into the code.

Orphée · March 15, 2022

@Polanskiman would it be possible for me to edit / keep up-to-date the first post of this topic ?

Thanks

sango · March 16, 2022

Hello,
I have successfully launched the DVA3221

sudo ./rploader.sh update now

"pid": "0x0001",
"vid": "0x46f4",
./rploader.sh serialgen DVA3221
./rploader.sh ext denverton-7.0.1-42218 add https://raw.githubusercontent.com/OrpheeGT/redpill-ext/master/acpid/rpext-index.json
sudo ./rploader.sh build denverton-7.0.1-42218
Generation OK recovery from Loader and send to proxmox

image.png.2cfc5cf8896e6e449d7e7045ad617613.png
Only I have no network
In theory it must be based on a Virtio driver from those I understood.
However none of works:

image.png.9eb4eebe87faf3cc174d95a39424860f.png

No DHCP request works

I managed to install a DS3615xs

image.png.c0ad425319d204537fb9586bbee36a07.png

An idea for the DVA network?

Thank you

Orphée · March 16, 2022

Edit : let me check what I did.

Here it is : https://raw.githubusercontent.com/OrpheeGT/redpill-load/develop/redpill-virtio/rpext-index.json

Edited March 16, 2022 by Orphée

sango · March 16, 2022

I have already look at him however I have not seen the normal Virtio for denverton-7.0.1-42218?

Edited March 16, 2022 by sango

Orphée · March 16, 2022

Just now, sango said:

j'ai regarder déjà lui cependant j'ai pas vu le Virtio pour denverton-7.0.1-42218 normal ?

I edited my post, in english please.

sango · March 16, 2022

il y a 2 minutes, Orphée a dit :

I edited my post, in english please.

Yes Sorry

sango · March 16, 2022

./rploader.sh ext denverton-7.0.1-42218 add https://raw.githubusercontent.com/OrpheeGT/redpill-ext/master/acpid/rpext-index.json
./rploader.sh ext denverton-7.0.1-42218 add https://raw.githubusercontent.com/OrpheeGT/redpill-ext/master/virtio/rpext-index.json

sudo ./rploader.sh build denverton-7.0.1-42218

Orphée · March 16, 2022

Did you take a look to my edit, or did you choose to ignore it ?

sango · March 16, 2022

About GRUB? for the moment I can't reboot the server, so I didn't make the change.
Is it really mandatory?

custom_config.json

Edited March 16, 2022 by sango

Orphée · March 16, 2022

41 minutes ago, Orphée said:

Edit : let me check what I did.

Here it is : https://raw.githubusercontent.com/OrpheeGT/redpill-load/develop/redpill-virtio/rpext-index.json

I can't do better than this...

sango · March 16, 2022

il y a 59 minutes, Orphée a dit :

I can't do better than this...

Sorry I didn't see this message

Here are the commands I typed:

./rploader.sh ext denverton-7.0.1-42218 add https://raw.githubusercontent.com/OrpheeGT/redpill-ext/master/acpid/rpext-index.json

./rploader.sh ext denverton-7.0.1-42218 add https://raw.githubusercontent.com/OrpheeGT/redpill-ext/master/virtio/rpext-index.json

sudo ./rploader.sh build denverton-7.0.1-42218

thanks for your help

Orphée · March 16, 2022

Dude, open your eyes.

sango · March 16, 2022

Yes I saw at the same time the meal is heavy ouppss ... I test with "develop"

sango · March 16, 2022

il y a 14 minutes, Orphée a dit :

Dude, open your eyes.

it's good ...

CPU(s)

My CPU : 4 x Intel(R) Core(TM) i5-4570S CPU @ 2.90GHz
Proxmox Virtual Environment 7.1-10

very big thank you to you! @Orphée

Edited March 16, 2022 by sango

Dvalin21 · March 16, 2022

Hey guys, I did a quick search on the GPU, kinda expensive. However I did find this link used and on sale for the moment. https://www.stomizef.com/product/portanyz-msi-nvidia-geforce-gtx-1650-super-4gb-gddr6-pci-express-3-0-graphics-card-black-gray/ use at your own risk. Just trying to pass on a good deal as I may be looking for myself at some point

Orphée · March 16, 2022

No one currently knows is the SUPER edition works.
Be carefull.

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