More QPU magic from Pete Warden

Back in June, we mentioned Pete Warden’s port of the Deep Belief image-recognition SDK to the Pi, which used the VideoCore IV QPUs to provide an accelerated GEMM matrix-multiply function. Since then, Pete’s been optimizing his code, and has reduced the time required to process an image to 3 seconds (versus 20 seconds for the baseline ARM implementation and 6 seconds for his original QPU version).

Classifying dogs and their balls

Classifying dogs and their balls

In the spirit of “leaving a trail of breadcrumbs through the forest”, Pete has written up an excellent summary of his experiences here. Head on over and check it out.

6 comments

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I would have included the image that was being processed.
https://raw.githubusercontent.com/jetpacapp/DeepBeliefSDK/gh-pages/source/data/dog.jpg

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thanks :)

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Thanks for the insight into how tricky GPU programming can be! The summary given in the link was fascinating even to this mere mortal who has only done a littl assembly programming on simple processors.

It is marvelous that a computer aimed at education of children doubles as a scientific tool. I wonder how long it will be before a 12-year old creates an interesting GPU program on the Pi.

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Is that supposed to read ‘QPU’ or ‘GPU’ ? Wikipedia defines ‘QPU’ as a ‘Quantum processing unit’……I know the Pi is brilliant; but I didn’t realize it was doing Quantum Computing just yet !!

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QPU stands for Quad Processor Unit.

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@Liz Thanks for the clarification !

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