Edge AI Hardware Hack with Tenstorrent @ Studio 45
Come join for a full day of building on the latest AI hardware with the Tenstorrent team.
The event is free of charge! Seats are limited.
Agenda
9:30am-10:00am - Registration / Coffee and Networking
10am-10:30am - Kickoff
10:30a-5:30p - Build
Lunch provided
5:30p-6:30p - Demos
5 Different Challenge Tracks
All Tenstorrent software is open source, and we encourage participants to browse the code ahead of time to pick a challenge that aligns with their interests. Whether you’re into compiler internals, ML training, or graphics experiments, there’s something here to get your hands dirty with.
Below are a few suggested challenges—these are optional, but they’re all meaningful contributions to the growing Tenstorrent ecosystem.
Implement an Operator in tt-metal
Help extend operator support in Tenstorrent’s low-level programming stack, tt-metal, by implementing a commonly used math or neural net primitive. We recommend: GitHub Issue #15939: Implement rsqrt. This is a great way to learn how ops are lowered and scheduled in Tenstorrent’s architecture.Ray Marching with the SFPU
Use the Special Function Processing Unit (SFPU) to build a basic Signed Distance Field (SDF) renderer using ray marching. This challenge explores how Tenstorrent’s hardware handles nonlinear math and graphics-style workloads, showing that it’s not just for transformers and CNNs.Implement SRCNN for Image Upscaling
Deploy a Super-Resolution Convolutional Neural Network (SRCNN)—a simple 3-layer model that enhances low-res images—on Wormhole using tt-metal. This task is approachable for those looking to understand model mapping, tensor layout, and operator sequencing on Tenstorrent hardware.Train word2vec with tt-train
Train a classic word2vec embedding model using Tenstorrent’s training stack, tt-train. This challenge is great for exploring custom training loops, loss functions, and tensor movement in a real-world NLP training scenario.Port the CLIP Image Encoder to tt-nn
Take the vision backbone of CLIP (Contrastive Language-Image Pretraining) and port it to run inference on tt-nn.
This is ideal for participants excited about foundation models and wanting to explore the boundaries of Tenstorrent’s inference APIs.
Winning Prize
🏆 Best use of Tenstorrent will win a Wormhole n150d ($1099 value).
Hosting partners
Tenstorrent builds high-performance AI processors and RISC-V CPUs designed for scalable, efficient machine learning and deep learning workloads in data centers and edge devices.
Koyeb is the fastest way to deploy full stack apps and AI workloads globally. No ops, servers, or infrastructure management.
Thank you to our venue Studio 45!
Studio45 is a professional coworking space for professionals building across diferent areas of hardware and robotics.