Great question! And it’d be amazing to see someone create a project like this.

It’s possible to do general-purpose matrix multiplication on Metis, yep, but it needs to be framed as part of a neural network forward path and deployed as an ONNX model using the Gemm operator. It’s not a CUDA-style setup where you can run arbitrary math on memory directly—everything goes through the model deployment pipeline.

There’s a bit more info in the Gemm section of this doc: 

https://github.com/axelera-ai-hub/voyager-sdk/blob/release/v1.2.5/docs/reference/onnx-opset14-support.md#gemm

Did you have a specific project or use-case in mind, ​@DominikD ?

My idea is to do some basic image processing on the edge device, where I have multiple images (not a video) taken, where each image might be shifted a bit (camera was moved a bit) and would like to have a one crispy by aligning these images and do some kind of multi-frame image averaging.

Thanks for the link ​@Spanner :) Will have a look.

Fascinating! So combining multiple, possibly misaligned or blurred or imperfect images to create one that harnesses the best of all, to produce a high quality image?

Very cool! Keep us posted on that - would love to see it in action one day! How much progress have you made on it so far?

Yes, this way we can have (should have ) a much better image. So far, it's in an early development stage. Therefore, looking for options and using your chip popped up as one of the potential options.

This is a cool idea, and not one I’ve heard anyone talking about, so you might well be on to something there! Keep us all posted ​@DominikD!

(By the way, once you’ve found what you need, please hit the “best answer” button to close your question  No rush to do so, if there’s more to come - but when you’re ready )

​@DominikD Fascinating application indeed! Try to formulate it as a Neural network operation with a forward pass problem. Some pointers could be looking at the FFT as a convolution operation as well.  Then you can use our device to run them more efficiently. Keep us posted. Cheers!