Just received my new ArmSoM Sige7 and started testing the provided Ubuntu 22.04 image and Rockchip loader. Flashed the board, set up the system, and ran initial CPU stress tests. Power usage looks great: ~7.5W under full load and ~2.5W idle, with temps staying cool and the fan barely audible. Promising start for this RK3588-based board!

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ArmSoM Sige7 — First Impressions & Setup Notes

Today, I received my ArmSoM Sige7 single-board computer, and I couldn’t wait to dive into setting it up and testing its performance. This post details my first impressions, the setup process, and the results of some early benchmarking.

Unboxing & Setup

The ArmSoM Sige7 came with a few essential files, available for download from ArmSoM's manual page. These files included the Ubuntu 22.04 preinstalled server image and the Rockchip firmware loader. Here’s what I downloaded:

Preparing the Image

Before flashing the image onto the device, I decided to mount it locally on my computer to set the root password and make a few changes. Here’s how I did it:

losetup -f -P ubuntu-22.04-preinstalled-server-arm64-armsom-sige7.img
losetup -l
mount /dev/loop23p2 /mnt/armsom/

After saving the changes, I unmounted the image and prepared to load the firmware and flash the image to the MMC.

Flashing the Image

To flash the OS image, I used rkdeveloptool, a tool for working with Rockchip-based devices. Here’s the process:

snap install --edge rkdeveloptool
snap connect rkdeveloptool:raw-usb
rkdeveloptool db rk3588_spl_loader_v1.15.113.bin
rkdeveloptool wl 0 ubuntu-22.04-preinstalled-server-arm64-armsom-sige7.img

Once the flashing process was complete, the board was ready to boot into Ubuntu!

CPU Stress Test & Power Usage

I ran a quick CPU stress test to evaluate the board's performance under load. Here’s what I found:

During the stress test, the fan remained completely silent, which suggests that the cooling solution is effective at handling the heat dissipation at this load.

Stress Test Output

Here’s the output from the stress test, using the stress-ng tool:

michiel@node1:~$ stress-ng --cpu 8 --timeout 60s --metrics-brief --timeout 60s
stress-ng: info:  [2477] setting to a 60 second run per stressor
stress-ng: info:  [2477] dispatching hogs: 8 cpu
stress-ng: info:  [2477] successful run completed in 60.13s (1 min, 0.13 secs)
stress-ng: info:  [2477] stressor       bogo ops real time  usr time  sys time   bogo ops/s     bogo ops/s
stress-ng: info:  [2477]                           (secs)    (secs)    (secs)   (real time) (usr+sys time)
stress-ng: info:  [2477] cpu               66276     60.03    479.56      0.00      1104.12         138.20

What's Next: GPU & NPU Testing

While the initial setup and CPU stress test have been promising, there’s a lot more to explore with the ArmSoM Sige7, especially the GPU and NPU.

The RK3588 chip includes a powerful Mali-G610 GPU and a dedicated NPU for AI and machine learning tasks. These features open up exciting possibilities for high-performance graphics rendering, AI inference, and edge computing applications.

In the coming weeks, I’ll be diving deeper into these capabilities:

GPU Testing: I plan to run graphics benchmarks, 3D rendering tests, and maybe even some gaming or multimedia applications to explore how well the Mali-G610 performs.

NPU Testing: I'll also look at utilizing the NPU for AI workloads, such as neural network inference or image processing. This could be a great way to speed up machine learning tasks on the edge.

Stay tuned as I continue to push the limits of this board — I’m excited to see how these advanced features perform under real-world conditions!

Conclusion

My first impressions of the ArmSoM Sige7 are very positive. The flashing process was straightforward, and the board is running smoothly with minimal power consumption. The temperature and noise levels are also impressive — even under load, the fan remains silent, and the temperature stays well within safe limits.

I’m excited to explore this board further, especially in the context of self-hosting and homelab setups. Stay tuned for more detailed posts as I continue to test and explore the possibilities with this device.

Tags: #ArmSoM #Sige7 #RK3588 #GPU #NPU #MaliG610 #AI #MachineLearning #EdgeComputing #SingleBoardComputer #SBC #Linux #Ubuntu #TechReview #Graphics #Homelab