OS: ubuntu 24.04

Install necessary packages

sudo apt update
sudo apt-get install -y build-essential chrpath cpio debianutils diffstat gawk git iputils-ping libdata-dumper-simple-perl liblz4-tool libsdl1.2-dev libthread-queue-any-perl locales python3 socat subversion texinfo wget zstd
sudo apt-get install -y uuid-dev acpica-tools

If want to compile it on x86 platform, it needs to install cross compiler gcc

sudo apt install gcc-aarch64-linux-gnu
export GCC_AARCH64_PREFIX=aarch64-linux-gnu-

Download git source code

export WORKSPACE=/nvme/tianocore
mkdir -p $WORKSPACE
cd $WORKSPACE
git clone https://github.com/tianocore/edk2.git
cd edk2
git submodule update --init
cd ..

git clone https://github.com/tianocore/edk2-platforms.git
cd edk2-platforms
git submodule update --init
cd ..
git clone https://github.com/tianocore/edk2-non-osi.git

git clone https://github.com/AmpereComputing/edk2-ampere-tools.git

git clone --depth 1 https://git.trustedfirmware.org/TF-A/trusted-firmware-a.git

Setup the environment, first time, it needs to run the script in the edk2 directory

make -C edk2/BaseTools
cd edk2
. edksetup.sh

then it should run it again on <WORKSPACE>

cd $WORKSPACE
. edk2/edksetup.sh

Build ARM ATF

cd $WORKSPACE
cd trusted-firmware-a                                                                        
make fiptool  
make certtool  

add those parameters to your environment file and source it.

export WORKSPACE=/nvme/tianocore
export PACKAGES_PATH=$PWD/edk2:$PWD/edk2-platforms:$PWD/edk2-non-osi:$PWD/edk2-platforms/Features
ATFPATH=$WORKSPACE
export MANUFACTURER=ASRockRack
export BOARD_NAME=Altra1L2T
export PATH=$PATH:$ATFPATH/AtfTools/tools/cert_create:$ATFPATH/AtfTools/tools/fiptool

Build the edk2

# build release version
./edk2-platforms/Platform/Ampere/buildfw.sh -m ASRockRack -p Altra1L2T -b RELEASE
# build debug version 
./edk2-platforms/Platform/Ampere/buildfw.sh -m ASRockRack -p Altra1L2T -b DEBUG
# Change default parameters
EDK2_X86_EMULATOR_ENABLE=FALSE EDK2_SHELL_ENABLE=TRUE ./edk2-platforms/Platform/Ampere/buildfw.sh -m ASRockRack -p Altra1L2T -b RELEASE

Detail parameres can be seen in the build_fw.sh file

./edk2-platforms/Platform/Ampere/buildfw.sh  --help
Usage:
  ./edk2-platforms/Platform/Ampere/buildfw.sh [options]

Options:
  -b <bldtype>, --build <bldtype>  Specify the build type: DEBUG or RELEASE
  -t <tc>, --toolchain <tc>        Specify the toolchain to use: GCC or CLANG
  -m <mfg>, --manufacturer <mfg>   Specify platform manufacturer (e.g. Ampere)
  -p <plat>, --platform <plat>     Specify platform to build (e.g. Jade)
  -l <kern>, --linuxboot <kern>    Build LinuxBoot firmware instead of full EDK2 with UEFI Shell, specifying path to flashkernel
  -f, --flash                      Copy firmware to BMC and flash firmware (keeping EFI variables and NVPARAMs) after building
  -F, --full-flash                 Copy firmware to BMC and flash full EEPROM (resetting EFI variables and NVPARAMs) after building

  Note: flash options require bmc.sh file with env vars BMC_HOST, BMC_USER and BMC_PASS defined

  Available manufacturers:
    ADLINK
    Ampere
    ASRockRack

  Available platforms:
    ADLINK     -> ComHpcAlt
    Ampere     -> Jade
    ASRockRack -> Altra1L2Q
    ASRockRack -> Altra1L2T

Environment Variables:
  SECUREBOOT_DIR       - directory to store SecureBoot keys, certs etc.
  USE_EXISTING_SB_KEYS - use existing Secure Boot Platform and Update keys
  DOWNLOAD_MS_SB_KEYS  - force re-download of Microsoft Secure Boot KEK and DB certificates
  CERT_PASSWORD        - password to use when generating Platform and Update Keys and certificates
                         defaults to "password" if not specified.

  EDK2_SECURE_BOOT_ENABLE             (TRUE)
  EDK2_NETWORK_ENABLE                 (TRUE)
  EDK2_INCLUDE_TFTP_COMMAND           (TRUE)
  EDK2_NETWORK_IP6_ENABLE             (TRUE)
  EDK2_NETWORK_ALLOW_HTTP_CONNECTIONS (FALSE)
  EDK2_NETWORK_TLS_ENABLE             (TRUE)
  EDK2_REDFISH_ENABLE                 (TRUE)
  EDK2_PERFORMANCE_MEASUREMENT_ENABLE (FALSE)
  EDK2_TPM2_ENABLE                    (TRUE)
  EDK2_HEAP_GUARD_ENABLE              (FALSE)
  EDK2_X86_EMULATOR_ENABLE            (TRUE)
  EDK2_SHELL_ENABLE                   (TRUE)

If build_fw.sh run’s without any problem, it will generate a 10MB size BIOS image, but the stock ASRR image size is 32MB. Therefore, you needs to copy the EDK2 image into the stock image at offset 0x600000. You can download the Altrad8ud stock firmware from the Altrad8ud firmware download site.

dd if=edk2-uefi.bin of=stock-bios.bin bs=1MB seek=6 conv=notrunc

Here is a sample script to package it again. It will generate fw-altrad8ud.tar, which can be upgraded via the WebGUI.

cp ampere/bios.bin .
cp ampere/MANIFEST .

dd if=Build/Altra1L2T/altra1l2t_uefi.bin of=bios.bin bs=1M seek=6 conv=notrunc

tar cf fw-altrad8ud.tar bios.bin MANIFEST

Or you also can copy bios.bin(modified) to the BMC and update it directly from the BMC.
because scp or sftp didn’t work for me, I used the http to download the image.

# cd /tmp
# curl <your web>/bios.bin
# ampere_flash_bios.sh bios.bin

ref. EDK2: new support for ASRock Rack ALTRAD8UD-1L2T / ALTRAD8UD2-1L2Q and build improvements for Mt Jade and COM-HPC-ALT

The post Build Master EDK2 for Altrad8ud appeared first on richliu's blog.

System Specifications

Nvidia Driver: NVIDIA-Linux-aarch64-570.86.16.run
Host: Ampere Altra + ALTRAD8UD
Host OS: Ubuntu 22.04 with HWE kernel (6.8)
Guest OS: Ubuntu 22.04 (ubuntu-22.04-live-server-arm64.iso)
GPU: Nvidia RTX 4080 16GB

Assumptions

1. You are familiar with Ubuntu and its basic commands.
2. You have experience using Virt-manager.
3. All commands are executed as the root user.

If anything is unclear, you can refer to external resources for additional guidance.

Host Configuration

Enable IOMMU

To enable IOMMU, you need to enable the SR-IOV option in the BIOS and verify whether the Linux kernel has IOMMU enabled by default.

You can check if IOMMU is enabled by running:

$ dmesg | grep -i iommu

Example output:

[    0.000000] Kernel command line: BOOT_IMAGE=/boot/vmlinuz-6.8.0-52-generic root=UUID=6b78fa89-a575-432d-a445-1497c3467214 ro iommu=on
[    0.000000] Unknown kernel command line parameters "BOOT_IMAGE=/boot/vmlinuz-6.8.0-52-generic iommu=on", will be passed to user space.
[   11.561684] iommu: Default domain type: Translated
[   11.566470] iommu: DMA domain TLB invalidation policy: strict mode

If IOMMU is not enabled, add iommu=on to the Linux kernel boot parameters:

$ vim /etc/default/grub 

Modify the line:

GRUB_CMDLINE_LINUX_DEFAULT="iommu=on"

Then update GRUB and reboot:

$ update-grub2  
$ reboot  

Additionally, enable SR-IOV in the BIOS. The exact location of this setting varies depending on the BIOS, but it is typically found under the PCIe subsystem or related options.

Upgrade Host to HWE Kernel

I recommend using the Hardware Enablement (HWE) kernel on the host. While I’m unsure if the regular kernel works, the HWE kernel has been reliable in my experience. Install it with:

sudo apt install linux-generic-hwe-22.04

Configure VFIO on Host

The VM relies on the VFIO driver for GPU passthrough. To configure VFIO, you need to pass the PCIe device information to the VFIO driver.

First, identify the GPU’s PCIe device IDs:

$ lspci -nn

Example output:

0005:01:00.0 VGA compatible controller [0300]: NVIDIA Corporation Device [10de:2704] (rev a1)
0005:01:00.1 Audio device [0403]: NVIDIA Corporation Device [10de:22bb] (rev a1)

Here, 10de:2704 is the GPU’s PCIe device ID, and 10de:22bb is the audio device ID. At a minimum, you need to pass through the GPU device.

Next, edit the VFIO configuration file to include these IDs:

$ vim /etc/modprobe.d/vfio.conf

Add the following line:

options vfio-pci ids=10de:2704,10de:22bb

Disable Nvidia Driver on HOST

To prevent the host from loading the Nvidia driver, add the Nvidia modules to the kernel’s blocklist:

$ vim /etc/modprobe.d/blacklist.conf

Add the following lines:

blacklist nvidia
blacklist nvidia_drm
blacklist nvidia_modeset

Update the initramfs and reboot:

$ update-initramfs -u
$ reboot

Configure VM

Install Virt-manager

In this article, we used virt-manager as VM manager, first step is install virt-manager, suppose Ubuntu will install all relative packages.

$ apt install virt-manager 

If you’re using SSH with X11 forwarding (e.g., ssh -X host) or MobaXTerm on Windows, Virt-manager will display the remote X window. If neither method works, consider installing a KDE desktop on the host and accessing it via the BMC remote console.

(Optional) Install KDE Plasma Desktop:

(option)
$ apt install kde-plasma-desktop

Create VM image

Virt-manager creates fixed-size VM images by default. If you prefer dynamic allocation, create the image manually:

$ qemu-img create -f qcow2 ubuntu2204.qcow2 200G

Add Nvidia device to VM

If the host is configured correctly, Virt-manager will list all PCIe devices, including the Nvidia GPU. Add the GPU and its audio device (e.g., 0005:01:00.0 and 0005:01:00.1) to the VM’s hardware list.

After adding the devices, proceed with the Ubuntu 22.04 installation.

After add hardware

Now, it can run begin install to install ubuntu 22.04

Disable secure Boot in UEFI

By default, Virt-manager enables Secure Boot. However, Nvidia drivers may not work with Secure Boot enabled. Even though the Nvidia installer includes a driver signing feature, the driver may still fail to load. To avoid issues, disable Secure Boot in the VM’s UEFI settings.

During the VM’s boot process, press the DEL key to enter UEFI settings and uncheck the Secure Boot option.

Before installing the Nvidia driver, ensure the necessary development packages are installed:

$ apt install build-essential

Then, install the Nvidia driver and reboot the VM.

GPU Passthrough Test

If everything is set up correctly, running nvidia-smi should display the GPU’s status.

For testing, you can use Ollama with the Deepseek-R1 model. Install Ollama with:

curl -fsSL https://ollama.com/install.sh | sh

Pull the Deepseek-R1 model. Since the GPU has 16GB of memory, the 14B model is a good choice (it requires ~10GB):

ollama run deepseek-r1:14b

Ask a question like, “Why is the sky blue?” This will trigger the model’s Chain-of-Thought (CoT) reasoning.

Monitor the GPU’s status using nvidia-smi to ensure it’s functioning correctly.

The post GPU Passthrough on ARM64 with Libvirt/Virt-manager appeared first on richliu's blog.

The Dynatron W3 package comes in a standard case.

includes a tower heatsink, one 120mm 4-pin fan, and thermal paste.

The base is not entirely copper, and its area seems somewhat small

other parts

While no documentation is provided, installation is straightforward for those familiar with DIY PC building

There is a gap between the DDR slots and the CPU fan, but larger DIMMs might require disassembling and reinstalling the tower fan.

In a preliminary test using stress-ng with 128 threads on an AltraMax 128-30 CPU and ASRock Rack ALTRAD8UD-1L2T.

Test command is

stress-ng --cpu 128 --vm 128 --vm-bytes 128M --timeout 180s --metrics-brief

the fan operated at 1400 RPM and maintained a quiet profile. The CPU temperature reached 64°C, staying below 70°C, with power consumption around 178W.

This performance suggests the tower fan is suitable for general purposes.

Notice: The CPU’s TDP is rated at 250W, this maximum power draw is only achievable under full system stress, such as utilizing all 8 DRAM controllers and all PCIe root controllers. Therefore, this figure should be considered as a reference rather than a precise measurement.

The post Dynatron W3 for Ampere AltraMax appeared first on richliu's blog.

In previous article on How to Install Stable Diffusion GUI on ARM64 Nvidia RTX platform , we installed the Nvidia driver and ran PyTorch on the platform. Now, this platform has Nvidia RTX gaming card, can we use it to play game?

The answer is yes, there are some windows x86 or x64 emulators on Linux, but the most stable solution comes from Ampere’s official release solution. Other emulators might not work as well on this combination, such as FEX, but I don’t know whether it is a driver issue or another issue.

Basically, following Ampere’s documentation makes it easy to install the driver and play games. Let’s combine both documents into one and simplify it in this article.

Hardware
CPU: Ampere Altra
Board: AsRock ALTRAD8UD
GPU: Nvidia RTX 4080

Reference Ampere’s document
NVIDIA GPU Accelerated Linux Desktop on Ampere
Steam-on-Ampere

Install Nvidia Driver

All the conditions are similar to those outlined in the article How to Install Stable Diffusion GUI on ARM64 Nvidia RTX platform, using Ubuntu 22.04 with a general kernel (not the HWE kernel, which Nvidia may address in the future).

I haven’t utilized the original document’s script; instead, I’ve copied some necessary commands from it.

sudo apt-get install build-essential
# Install Nvidia driver here
sudo rmmod nouveau
cat << EOF | sudo tee /etc/modprobe.d/blacklist-nouveau.conf
blacklist nouveau
options nouveau modeset=0
EOF

sudo nvidia-xconfig -a --cool-bits=31 --allow-empty-initial-configuration

# Install Desktop, personally I like kde. 
sudo apt install kde-plasma-desktop
# or it can install regular ubuntu desktop 
# sudo apt install ubuntu-desktop

Download Nvidia ARM64 (aarch64) Display Driver ; the current version, 535.154.05, is acceptable. After installing the Nvidia driver, simply reboot the system. You can then use the following command to check the driver status.

nvidia-smi

Disable aspm from kernel

I didn’t apply this option. Most of the time, it’s only necessary to do so if the system encounters the massive AER error issue. Here’s an example command from the original document:

sudo nano /etc/default/grub
# Add pcie_aspm=off to kernel parameters
# GRUB_CMDLINE_LINUX_DEFAULT="pcie_aspm=off"
sudo update-grub

Install Box86

Following commands show how to install Box86

sudo wget https://itai-nelken.github.io/weekly-box86-debs/debian/box86.list -O /etc/apt/sources.list.d/box86.list
wget -qO- https://itai-nelken.github.io/weekly-box86-debs/debian/KEY.gpg | sudo gpg --dearmor -o /etc/apt/trusted.gpg.d/box86-debs-archive-keyring.gpg
sudo dpkg --add-architecture armhf
sudo apt update
sudo apt install box86:armhf -y

Install Box64

Following command show how to install Box64, but original instruction have update , a package name was changed.

sudo wget https://ryanfortner.github.io/box64-debs/box64.list -O /etc/apt/sources.list.d/box64.list
wget -qO- https://ryanfortner.github.io/box64-debs/KEY.gpg | sudo gpg --dearmor -o /etc/apt/trusted.gpg.d/box64-debs-archive-keyring.gpg
sudo apt update 
sudo apt install box64-arm64 -y
sudo systemctl restart systemd-binfmt

Installing Steam

Because I am using the Ubuntu 22.04 ARM64 server version with minimal, so, some packages might not be installed, Before Install Steam, install necessary packages

sudo apt install lsof

sudo apt install zenity
sudo apt install alsa

Use the following to install steam.

git clone https://github.com/ptitSeb/box86
cd box86
./install_steam.sh

Now, it can use steam now.

/usr/local/bin/steam

Okay, log in and enjoy it. However, in my experience, when installing other emulators, it might damage the box86+Steam setup, necessitating a system reinstallation to fix it.

Furthermore, the game’s performance seems not as good as expected, possibly due to my choice of Vampire Survivors and enabling high performance

Xbox JoyStick controller

I have an Xbox controller, and ALTRAD8UD doesn’t have Bluetooth capability, so I cannot use wireless conntions. However, it can connect via USB.

There are several Xbox drivers available for Linux. After testing, I found that xpadano is compatible with this platform. Simply follow their instruction guide to install the Xbox driver.

# Install DKMS package
sudo apt-get install dkms linux-headers-`uname -r`

# download source code
git clone https://github.com/atar-axis/xpadneo.git
cd xpadneo
# use DKMS to compile the driver
sudo ./install.sh

The Xbox controller driver will be installed automatically, and it works well in my tests. You can install the jstest package to perform a joystick test.

The Xbox controller functions seamlessly on Steam and Vampire Survivors. I can easily use the Xbox controller to play Vampire Survivors.

The post Play Game On Ampere Altra ARM64 Platform appeared first on richliu's blog.

In this article, it will walk through the process of installiung Stable Diffusion WebUI on ARM64 + Nvidia RTX platform.
For such as hardware combinarion, it needs to solve some compatiability issues, so, here will describe how to install it and fix those issues.

Platform

CPU: Ampere Altra ARM64 CPU
Board: AsRock ALTRAD8UD
OS: Ubuntu 22.04

The platform is the most powerful ARM64 platform for a homelab that we can obtain today. There are some server models available, but they come with high-speed cooling fans that are not suitable for home use.

Nvidia has provided comprehensive library support for the ARM64 platform, including drivers, CUDA, and cuDNN. However, despite these efforts, there are still gaps in support. Even Nvidia’s Jetson product line lacks adequate support for ARM64 platforms in certain applications such as PyTorch. While there exists an individual PyTorch accelerator package for direct download on x64 platforms, the same cannot be said for ARM64 platforms. Although there is technically one package available, its availability is severely limited, rendering it practically useless.

The only viable solution to overcome these limitations is to utilize Nvidia’s Docker service to install Stable Diffusion.

Installation

Install Ubuntu 22.04 without selecting the HWE (Hardware Enablement) support. It appears that the current Nvidia driver version has issues, leading to potential soft-lock bugs. A general kernel version (5.15) is preferable for stability.

Next, install the necessary Ubuntu packages.

sudo apt-get install build-essential

Download Nvidia ARM64 (aarch64) Display Driver , current version is ok, when I write this article, current version is 535.154.05

Docker

Install Docker by following the Docker guide Install Docker Engine on Ubuntu,”. Also provide the necessary installation steps here. If already installed Docker or if these steps don’t work, please refer to the original website for updated instructions.

# Add Docker's official GPG key:
sudo apt-get update
sudo apt-get install ca-certificates curl
sudo install -m 0755 -d /etc/apt/keyrings
sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.asc

# Add the repository to Apt sources:
echo \
  "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \
  $(. /etc/os-release && echo "$VERSION_CODENAME") stable" | \
  sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
sudo apt-get update

sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

Nvidia Container Toolkit

Follow the instructions for installing the NVIDIA Container Toolit. It can modify the Docker configuration using this toolkit. Alternatively, modifying the daemon.json file might achieve the same result, although I haven’t personally tested it. Below are the instructions:

curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
  && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
    sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
    sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

sudo sed -i -e '/experimental/ s/^#//g' /etc/apt/sources.list.d/nvidia-container-toolkit.list

sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit

sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker

It can check the file /etc/docker/daemon.json file, the configuration should be like this.

{
    "runtimes": {
        "nvidia": {
            "args": [],
            "path": "nvidia-container-runtime"
        }
    }
}

Run Nvidia pytorch docker image

Following is example command to run the Nvidia pytorch docker image

sudo docker run --gpus all -it --rm \
        -v /host/work:/container/work \
        -p 7860:7860 \
        nvcr.io/nvidia/pytorch:XX.XX-py3

/host/work means work directory on host, /container/work means work directory in container(docker). -p 7860 mean gui default port, it needs to forward to host machine. XX.XX means container versiom please see tags to get container version, or this URL . [NGC Pytorch]. Following is example command.

sudo docker run --gpus all -it --rm \
        -v /work:/work \
        -p 7860:7860 \
        nvcr.io/nvidia/pytorch:24.01-py3

Stable Diffustion WebUI

First steps clone Stable Diffustion WebUI source code.

git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git

Then, it needs to modify the settings file. Edit webui.sh, and adjust the parameters to the following numbers.

use_venv=0
can_run_as_root=1

As we are operating within a container, there’s no need for a virtual environment (venv), and the script can be run as root. Modify the file webui-user.sh and add COMMANDLINE_ARGS accordingly.

export COMMANDLINE_ARGS="--no-half --precision full --listen"

or run it directly

export COMMANDLINE_ARGS="--no-half --precision full --listen" ; bash webui.sh

Currently, Stable Diffusion will download some packages, but errors may occur during the installation process. We’ll address and fix these errors in the next few steps.

CV2

Error message :

    if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
  File "/usr/local/lib/python3.10/dist-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
    py_module = importlib.import_module(module_name)
  File "/usr/lib/python3.10/importlib/__init__.py", line 126, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "/usr/local/lib/python3.10/dist-packages/cv2/typing/__init__.py", line 168, in <module>
    LayerId = cv2.dnn.DictValue
AttributeError: module 'cv2.dnn' has no attribute 'DictValue'

Modify file “/usr/local/lib/python3.10/dist-packages/cv2/typing/__init__.py”, comment out line 169 like following.[ref]

# LayerId = cv2.dnn.DictValue

CodeFormer

Error message:

"/work/stable-diffusion-webui/repositories/CodeFormer/facelib/utils/face_restoration_helper.py", line 7, in <module>
        from facelib.detection import init_detection_model
      File "/work/stable-diffusion-webui/repositories/CodeFormer/facelib/detection/__init__.py", line 11, in <module>
        from .yolov5face.face_detector import YoloDetector
      File "/work/stable-diffusion-webui/repositories/CodeFormer/facelib/detection/yolov5face/face_detector.py", line 20, in <module>
        IS_HIGH_VERSION = tuple(map(int, torch.__version__.split('+')[0].split('.'))) >= (1, 9, 0)
    ValueError: invalid literal for int() with base 10: '0a0'

This issue caused by pytorch.version will return illegeal number like 2.2.0a0+81ea7a4, so it will fail to parse this mesage, temperory solution is to remove the version number, edit file “stable-diffusion-webui/repositories/CodeFormer/facelib/detection/yolov5face/face_detector.py”. and modify line 20, IS_HIGH_VERSION to following version to following:[ref]

version_string = torch.version.split('+')[0]
version_string = ''.join(filter(str.isdigit, version_string))
IS_HIGH_VERSION = tuple(map(int, version_string.split('.'))) >= (1, 9, 0)

Now, the Stable Diffusion GUI should be working as well as expected

The post How to Install Stable Diffusion GUI on ARM64 Nvidia RTX platform appeared first on richliu's blog.

What truly impresses me is the board’s specifications. Not only does it boast a compact Micro-ATX form factor, but it also packs a powerful punch with four PCIe 4.0 x16 lanes, easily handling even demanding homelab tasks. The dual M.2 slots and dual OCULink port can enable software RAID for your NVMe disks. As a server board, it offers a BMC for remote control and system management. While the x64 platform remains popular, this board is an exceptional choice for those who prefer the non-x64 architecture, considering the limited choices with high speed fan options in server platforms.

Information

Important Spec

AsRock ALTRAD8UD-1L2T Spec web site

Where To Buy

US/Newegg

ASRock Rack ALTRAD8UD-1L2T Deep Micro-ATX Server Motherboard Single Socket (LGA 4926) Ampere Altra Max/Ampere Altra processors Dual 10G & 1G Without CPU,
Mother board only
USD$849.-

Asrock Rack Bundle ALTRAD8UD-1L2T Deep Micro-ATX Server Motherboard Single Socket (LGA 4926) with Ampere Altra Q64-22 64 cores & 2U passive cooler, Dual 10G – Integrated by Asrock Rack with CPU and heatsink
Mother board + Altra Q64-22 + 2U passive cooler(heatsink)
USD$1,500.-

UK/Server Factory Ltd

ASRock ALTRAD8UD-1L2T: Board only, Inc VAT: £870.00.

News

ASRock Rack ALTRAD8UD-1L2T Review This is the Ampere Arm Motherboard You Want

Cooling solution

Making Arm Desktops Viable Ampere Altra Noctua NH-D9 AMP-4926 4U and NH-U14S AMP-4926 (Preview tower fan system)
Ampere Altra/AltraMax AsRock ALTRAD8UD-1L2T Liquid Cooling System (my homemake Liquid/Water cooling system)

Other reference URL

ASRock Rack ALTRAD8UD Getting Started : A good note to start up to use the board.

Tricks for ALTRAD8UD

This chapter aims to guide users through using the ALTRAD8UD board, addressing potential information gaps left by the official ALTRAD8UD manual.

For memory compatibility reference, AsRock offers its own DRAM AVL (Approved Vendor List). Alternatively, users can access the Ampere Altra family device document, freely available without registration.

OpenBMC default username password

User: root
Pass: 0penBmc (first word is zero, not O).
both BMC console and GUI’s default username password are the same.

Serial Console over LAN Port

The board support Serial Port Header (9-pin COM1), it needs to use this serial port or VGA port to enter BIOS and get BMC IP.
After get the BMC IP, it can get more information from serial console over LAN port
Port 2201: ATF console
Port 2202: SCP console
Port 2203: Host console
Port 22: ssh console

Here is my script to run the sol and make it more easy to use

# It can put following two lines to bashrc
alias oit='ipmitool -U root -P 0penBmc -I lanplus -C 17'
alias ossh="sshpass -p 0penBmc ssh -o GlobalKnownHostsFile=/dev/null -o UserKnownHostsFile=/dev/null -oStrictHostKeyChecking=no"

# get host console 
ossh root@<bmc ip> -p 2203 
# get in bmc ssh console 
ossh root@<bmc ip> 

Serial Console Output To VGA

If you cannot see the serial console output to console port, probably it bacuase this option was enabled[ref], just turn it off and add console=tty0 or console=ttyAMA0 to grub.conf, ex:

GRUB_CMDLINE_LINUX_DEFAULT="console=ttyAMA0"

Ipmitool Fan Control [ref]

Manual Full speed
ipmitool raw 0x3a 0x01 0x64 0x64 0x64 0x64 0x64 0x64 0x64 0x64

Manual Half speed
ipmitool raw 0x3a 0x01 0x32 0x32 0x32 0x32 0x32 0x32 0x32 0x32

Auto fan control
ipmitool raw 0x3a 0x01 0x0 0x0 0x0 0x0 0x0 0x0 0x0 0x0

NC-SI Port

In the user manual, NC-SI port is typo, the NC-SI port location is 5, in the document which marked as IPMI LAN port. if use this port, both host and BMC can use the same network cable to connect to the same ethernet.

Known Issues

Intel X550 massive AER error messages[ref1][ref2]

Seems that Intel NICs have compatibility issues with non-Intel platform systems. This can cause some server safety systems, like Advanced Error Reporting (AER), to generate many alerts and experience interface problems. A temporary solution is to add aspi_aspm=off to the Linux kernel parameters, ex:

GRUB_CMDLINE_LINUX_DEFAULT="console=ttyAMA0 pcie_aspm=off"

It will fix the AER issue.

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