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Demonstrate an ML application that implements inferencing for with a hardened neural network on a chip using Tiny Tapeout
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Demonstrate an ML application that implements inferencing for with a hardened neural network on a chip using Tiny Tapeout
In this contest, we invite you to develop your own deep neural network and implement it on a chip using Tiny Tapeout.
The goal of these projects are to demonstrate the process of developing a custom chip for ML acceleration using exist ML development flows based on PyTorch, TensorFlow Lite or other, coupled with the streamlined development flow for custom silicon using Tiny Tapeout leveraging the Efabless chipIgnite solution.
For those projects meeting the submission requirements, we will be awarding up to 10 slots chosen from the pool of entries. Winning projects will be provided free fabrication of their design on the Tiny Tapeout submission for the June chipIgnite shuttle. Each winning project receives a Tiny Tapeout Demo board with a copy of the Tiny Tapeout chip.
Register below to stay updated when we post the example design, additional information and other resources.