Test Google Coral TPU M.2 Accelerator A+E key

[geerlingguy]

I just bought a Coral M.2 Accelerator A+E key after seeing a lot of buzz about this little 'IoT' TensorFlow-compatible AI accelerator.

I also just received an M.2 A key to PCIe 1x slot adapter card (see https://github.com/geerlingguy/raspberry-pi-pcie-devices/issues/38), and I will pop the Coral board into there.

I haven't done much with AI/ML, but apparently one of the big holdups for using this board with the Pi may be overcome soon—see: https://github.com/google-coral/edgetpu/issues/280

(And I don't want to step on @timonsku's toes here either—he was the original inspiration for me getting this particular card, after seeing his Piunora; just figured now is as good a time as ever to take a quick stab at TensorFlow.)

See related, in the Pi Forums: https://www.raspberrypi.org/forums/viewtopic.php?p=1772610&sid=4833ac3f714618282207affca2bcd846#p1772610

And the patch advertising MSI-X support in the Pi Kernel (currently only on 5.10.y branch): https://github.com/raspberrypi/linux/commit/6bf63f7711b550de8c803a4c4ad792ecfbe721df

(Note that it may be incorporated into Ubuntu for Pi too... https://twitter.com/m_wimpress/status/1345077692568367105

[r3po-1s-Tr3e]

Blog post with full summary: A PCIe Coral TPU FINALLY works on Raspberry Pi 5.

@geerlingguy , amazing guide. But we have been facing a problem, we are not able to install pcie gasket drivers after changing the device tree settings. Rpi is not able to update its kernel headers after changing the drive tree settings. I have tried downgrading rpi os from 6.6 to 6.1, but still it dosent work. if i dont change the device tree settings, the gasket drivers are installing correctly, but then the image classification sample thorws an error that it cant access dev/apex_0

Harwdare: Raspberry pi 5 4gb, nvme base for rpi, coral m.2 tpu b+m key

any insight will be appreciated, thanks!

[mikegapinski]

@r3po-1s-Tr3e follow this thread, it has all the info for Coral. I have not tested the B+M recently but A+E works ok so this one should too

https://gist.github.com/dataslayermedia/714ec5a9601249d9ee754919dea49c7e?permalink_comment_id=4989560#gistcomment-4989560

[r3po-1s-Tr3e]

@mikegapinski It worked! I changed a few things, if anyone is intrested, here are the details:

Hardware: Raspberry pi 5 4gb Coral TPU M.2 Accelerator B+M key NVMe Base PCIe extension HAT for Raspberry pi 5 OS: 6.1.0-rpi4-rpi

Procedure which i followed (I ommited a few steps from Jeff Geerling's guide and changed sequence of action):

echo "deb https://packages.cloud.google.com/apt coral-edgetpu-stable main" | sudo tee /etc/apt/sources.list.d/coral-edgetpu.list curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add - sudo apt-get update

sudo apt-get install gasket-dkms libedgetpu1-std

sudo sh -c "echo 'SUBSYSTEM==\"apex\", MODE=\"0660\", GROUP=\"apex\"' >> /etc/udev/rules.d/65-apex.rules" sudo groupadd apex sudo adduser $USER apex

Now REBOOT, after reboot check if TPU is detected by: lspci -nn | grep 089a #Output: 03:00.0 System peripheral: Device 1ac1:089a Check if pcie driver is loaded: ls /dev/apex_0 #Output: /dev/apex_0

If i tried to follow these steps after changing the device tree, I would have not been able to install the gasket and pcie drivers because of not being able to install headers. Further steps:

echo "kernel=kernel8.img" | sudo tee -a /boot/config.txt Omitted other steps regarding config changes which were mentioned in the guide Then changed the Device tree settings: https://www.jeffgeerling.com/blog/2023/how-customize-dtb-device-tree-binary-on-raspberry-pi (NOTE: If you are on kernel version 6.6, which is currently the latest, change the msi-parent settings to 0x67 instead of 0x66. Source: https://gist.github.com/dataslayermedia/714ec5a9601249d9ee754919dea49c7e?permalink_comment_id=4989560#gistcomment-4989560)

Installed docker: curl -sSL https://get.docker.com | sh

Then followed the steps from : https://www.jeffgeerling.com/blog/2023/testing-coral-tpu-accelerator-m2-or-pcie-docker to create and run docker image

tested by running the sample image classifier script of tpu