My ARM fleet

[Dirk Broer]

How's the 32-bit squad doing on Universe@Home, and how do their results compare to the converted 64-bit 'heavies'?

• BeagleBone-AI (dual core Cortex-A15): 4,035 credits/day
• Asus Tinker Board (quad core Cortex-A17): 8,086 credits/day
• Odroid-XU4 (quad core Cortex-A15/quad core Cortex-A7): 8,923 credits/day

These values hover a bit for the Tinker Board and the XU4 (between 7800 and 9100), but the BeagleBone-AI is still climbing slowly.
I quitted crunching Asteroids@Home on the Odroid-XU4, so it only crunches SiDock@Home and Universe@Home now.

Longer crunching 64-bitters, still on the rise and climbing a tad faster than the BeagleBone-AI (especially the Odroid-M1)

• Raspberry Pi 3 (quad core Cortex-A53): 2,772 credits/day
• Raspberry Pi three (quad core Cortex-A53): 4,421 credits/day
• Odroid-M1 (quad core Cortex-A55): 9,354 credits/day

The Raspberry Pi 3 previously crunched SiDock@Home but the Odroid-XU4 is much better in that, so the Pi 3 went to Universe@Home.

and here for the last converted 64-bitters, that began later with Universe@Home and climb still faster:

• Raspberry Pi 400 (quad core Cortex-A72): 3,409 credits/day
• Raspberry Pi 4 8GB (quad core Cortex-A72): 3,480 credits/day
• Jetson Nano 2GB (quad core Cortex-A57): 4,059 credits/day
• Jetson Nano 4GB (quad core Cortex-A57): 6,680 credits/day

The 2GB Jetson Nano was the lastly converted and much celebrated at the experimental department, as it now combines -thanks to Muhammad Yunus,
IoT Engineer, Software Developer & Machine Learning Enthusiast- both CUDA and OpenCL for its GPU.
For the time being it is as useful as a 100 TOPS NPU/TPU for BOINC running Linux/ARM (or even Windows), but who knows....
The two Raspberry Pi 4's are the latest additions to the Universe task force