Hey fellow opi 5 owner! iirc some ppl back then managed to run newer ubuntu rk3588 aswell but what makes me quit was the gpu support (Rockchip’s android image have better driver performance and linux neglected which sucks). Also saw that collabora and panfrost stuff but I moved back to x86 mini pc bcuz I need gpu stuff, thought to repurposing them as media server & emulator setup but didn’t worked with linux.
Owned orange pi 5 back then for college project, their NPU really packs a punch but sadly the good story ends there. After finished the project sold mine to friend who need them for computer vision and NN stuffs.
GPU and overall firmware support is always better on x86 systems, so makes sense that you switched to that for your application. Performance is also usually better if you don’t explicitly need low power. In my use case I use the Orange Pi 5 Plus for running an astrophotography rig, so I needed something that was low power, could run Linux easily, had USB 3, reasonable single core performance, and preferably had the possibility of an upgradable A key WiFi card and a full speed NVMe E key slot for storage (preferably PCIe 3.0x4 or better). Having hardware serial ports was a plus too. x86 boxes would’ve been preferable but a lot of the cheaper stuff are older Intel mini PCs which have pretty poor battery life, and the newer power efficient stuff (N100 based) is more expensive and the cheaper ones I found tended to have onboard soldered WiFi cards unfortunately. Accordingly the Orange Pi 5 Plus ended up being my cheapest option that ticked all my boxes. If only software support was as good as x86!
Interesting to hear about the NPU. I work in CV and I’ve wondered how usable the NPU was. How did you integrate deep learning models with it? I presume there’s some conversion from runtime frameworks like ONNX to the NPU’s toolkit, but I’d love to learn more.
I’m also aware that Collabora has gotten the NPU drivers upstreamed, but I don’t know how NPUs are traditionally interfaced with on Linux.
Hey fellow opi 5 owner! iirc some ppl back then managed to run newer ubuntu rk3588 aswell but what makes me quit was the gpu support (Rockchip’s android image have better driver performance and linux neglected which sucks). Also saw that collabora and panfrost stuff but I moved back to x86 mini pc bcuz I need gpu stuff, thought to repurposing them as media server & emulator setup but didn’t worked with linux.
Owned orange pi 5 back then for college project, their NPU really packs a punch but sadly the good story ends there. After finished the project sold mine to friend who need them for computer vision and NN stuffs.
GPU and overall firmware support is always better on x86 systems, so makes sense that you switched to that for your application. Performance is also usually better if you don’t explicitly need low power. In my use case I use the Orange Pi 5 Plus for running an astrophotography rig, so I needed something that was low power, could run Linux easily, had USB 3, reasonable single core performance, and preferably had the possibility of an upgradable A key WiFi card and a full speed NVMe E key slot for storage (preferably PCIe 3.0x4 or better). Having hardware serial ports was a plus too. x86 boxes would’ve been preferable but a lot of the cheaper stuff are older Intel mini PCs which have pretty poor battery life, and the newer power efficient stuff (N100 based) is more expensive and the cheaper ones I found tended to have onboard soldered WiFi cards unfortunately. Accordingly the Orange Pi 5 Plus ended up being my cheapest option that ticked all my boxes. If only software support was as good as x86!
Interesting to hear about the NPU. I work in CV and I’ve wondered how usable the NPU was. How did you integrate deep learning models with it? I presume there’s some conversion from runtime frameworks like ONNX to the NPU’s toolkit, but I’d love to learn more.
I’m also aware that Collabora has gotten the NPU drivers upstreamed, but I don’t know how NPUs are traditionally interfaced with on Linux.