[HN Gopher] A PCIe Coral TPU Finally Works on Raspberry Pi 5 ___________________________________________________________________ A PCIe Coral TPU Finally Works on Raspberry Pi 5 Author : mikece Score : 52 points Date : 2023-11-17 19:16 UTC (3 hours ago) (HTM) web link (www.jeffgeerling.com) (TXT) w3m dump (www.jeffgeerling.com) | jauntywundrkind wrote: | Coral is 4 years old, and it's both shocking & not that there | aren't many competitors out there today. | | Also a bit sad PyCoral requires python 3.9! Yikes! | filterfiber wrote: | Especially since it only has like 8 MB of memory I think? | geerlingguy wrote: | Some SoCs even have competent built in NPUs, too, but | software support is severely lacking. | | PyCoral and Coral hardware development seems glacial lately | :( | | They have enjoyed a lot of momentum... I wish they could | release a follow-up version and get some longstanding | software issues resolved. | gymbeaux wrote: | I think companies prefer to develop AI stuff and then sell it, | rather than sell the hardware. | nmstoker wrote: | However keeping the Python version up to date shouldn't be | that hard though, should it? | westurner wrote: | An HBM3E HAT would or would not yet make TPUs more useful with a | Raspberry Pi 5? | | Jetson Nano (~$149) | | Orin Nano (~$499, 32 tensor cores, 40 TOPS) | | AGX Orin (200-275 TOPS) | | NVIDIA Jetson > Origins: | https://en.wikipedia.org/wiki/Nvidia_Jetson#Versions | | TOPS for NVIDIA [Orin] Nano [AGX] | https://connecttech.com/jetson/jetson-module-comparison/ | | Coral Mini-PCIe ($25; ? tensor cores, 4 TOPS (int8); 2 TOPS per | watt) | | TPUv5 (393 TOPS) | | Tensor Processing Unit (TPU) | https://en.wikipedia.org/wiki/Tensor_Processing_Unit | | AI Accelerator > Nomenclature: | https://en.wikipedia.org/wiki/AI_accelerator | | NVIDIA DLSS > Architecture: | https://en.wikipedia.org/wiki/Deep_learning_super_sampling#A... : | | > _DLSS is only available on GeForce RTX 20, GeForce RTX 30, | GeForce RTX 40, and Quadro RTX series of video cards, using | dedicated AI accelerators called Tensor Cores. [23][28] Tensor | Cores are available since the Nvidia Volta GPU microarchitecture, | which was first used on the_ Tesla _V100 line of products.[29] | They are used for doing fused multiply-add (FMA) operations that | are used extensively in neural network calculations for applying | a large series of multiplications on weights, followed by the | addition of a bias. Tensor cores can operate on FP16, INT8, INT4, | and INT1 data types._ | | Vision processing unit: | https://en.wikipedia.org/wiki/Vision_processing_unit | | Versatile Processor Unit (VPU) ___________________________________________________________________ (page generated 2023-11-17 23:00 UTC)