Coral Npu: a Full-Stack Platform for Edge AI
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Edge AIHardware AccelerationGoogle Coral Npu
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Edge AI
Hardware Acceleration
Google Coral Npu
Google announces Coral NPU, a full-stack platform for Edge AI, sparking discussion on its potential, security, and Google's track record.
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The architecture seems to be RISC-V array with standard RVV vector instruction set. That is a quite familiar environment for software developers compared to custom systolic arrays.
The original Google Coral lineup offered a 4TOPS accelerator back in 2018-2020.[3][4]
The original (4 TOPS) Coral used ~1 watt while this new Coral TPU is designed for 10mW/0.5 TOPS.[5] That power budget fits well alongside low power MCU's.
It doesn't appear to include any hardware accelerated video encoding[6] for H264/etc, which was also a massive limitation of the original google coral (improved slightly in the Dev Board Mini). There's a lot of documentation on consuming WebRTC content, and while streaming out is mentioned ... any encoding would have to be performed on one of the A55 cores at dubious performance levels. The RK3588, for example, includes a VPU for hardware accelerated video encoding (H264/HEVC encoding @ 8k30fps).
0: https://cdn.bfldr.com/ZU41R0OK/at/tjm5s8hrmz5mgqrjtsrc5c4/sl...
1: https://www.synaptics.com/products/embedded-processors/sl261...
2: https://cdn.bfldr.com/ZU41R0OK/at/ks4thp8bw9n3bt2ktms3k34s/s...
3: https://abopen.com/news/google-launches-coral-edge-tpu-devel...
4: https://developers.googleblog.com/en/new-coral-products-for-...
5: https://developers.google.com/coral/guides/power
6: https://synaptics-astra.github.io/doc/v/latest/linux/index.h...
What's upsetting about the state? Continued development?
however, to your point : being google affiliated is a huge red-flag for longevity.
Agreed that that no hardware video encode is pretty damned deflating.
Having such a low power device is incredibly enticing. Thanks for the good details. One random thing I'm kind of excited over, there's 3x I2S audio connections, which has some weird fun use cases (ideally a little field recorder?).
One curious thing, Google's post says they are still trying to finalize the matrix extensions for RISC-V. I'm assuming those simply aren't on these Synaptics chips?
Please language troll somewhere else.
someone at ycombinator should create a "github for silicon IP" company. that would be awesome.
I've been experimenting with the BeagleY-AI to build a little edge AI gizmo with a camera (Texas Insturments SoC + 4 TOPS NPU in RPi 5 form factor)
https://docs.beagleboard.org/boards/beagley/ai/demos/using-e...
I've only heard of people using Coral PCIe / USB for edge image AI processing tasks like classifying subjects in a stream. Curious if you have the same use case or something different!
The TI SDK makes it easy to run demos but making any custom apps quickly gets complicated unless you are familiar with embedded Linux dev, Yocto, etc. Certainly much more complex than iOS/Android.
Hopefully over time the tools for embedded can catch up to mobile.
When I went to see if anyone is selling the boards or their "Partners" page regarding manufacturing design I got 404 even after signing in: https://developers.google.com/coral/guides/coral/resource
> Hardware-enforced privacy
> A core principle of Coral NPU is building user trust through hardware-enforced security. Our architecture is being designed to support emerging technologies like CHERI, which provides fine-grained memory-level safety and scalable software compartmentalization. With this approach, we hope to enable sensitive AI models and personal data to be isolated in a hardware-enforced sandbox, mitigating memory-based attacks.