In this hackathon, you'll take on the challenge of compiling legacy code to run efficiently on the Tenstorrent Wormhole, a modern tensor processors.

But you're not starting from scratch—we'll be building on top of dace/sdfglib, implementing stateful dataflow multigraphs (Ben-Nun et al., SC'19), and bringing in ideas from Tensorize (Brauckmann et al., CGO’25) to optimize code for AI-native execution models.

This is your chance to explore data-centric compilation and modern tensor chips.

Requirements

Participants will:

- Analyze and transform legacy codes using stateful dataflow multigraphs.

- Extend dace/sdfglib to support the lifting of tensor operations from loops, inspired by Tensorize.

- Target a state-of-the-art tensor processor, a Tenstorrent Wormhole

- Develop IR passes, scheduling strategies, or new representations that help legacy code embrace tensorized compute.

Hackathon Sponsors

Prizes

1 non-cash prize
Pizza, Drinks and Fun
1 winner

Have fun and learn about compiler engineering with world-class engineers and researchers

Devpost Achievements

Submitting to this hackathon could earn you:

Judges

Alexandru Calotoiu

Alexandru Calotoiu

Tal Ben Nun

Tal Ben Nun

Judging Criteria

  • Performance

Questions? Email the hackathon manager

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