Tech

Penn team traps light and matter to accelerate matrix operations at lower power.

What happened

Engineers at the University of Pennsylvania coupled photons with excitons inside a micro-ring resonator, forming polaritons whose spin precession performs 4-by-4 matrix multiplies in 50 femtoseconds. A prototype chip executed a BERT layer at 2.3 picojoules per MAC, two orders of magnitude below an equivalent electronic systolic array. The device is fabricated in a standard silicon-photonics foundry process.

Why it matters

You begin to treat photons as first-class compute elements rather than mere data carriers, which alters how you partition workloads between electronic and optical stages in your inference pipeline.

Who's doing it

The Penn Quantum Photonics Lab taped out a 64-polariton array in AIM Photonics MPW runs; they report 8 times throughput gains on transformer feed-forward layers while drawing 180 milliwatts versus 1.4 watts for a comparable GPU block.

Try it

  1. Download the open PDK and simulation scripts from quantum photonics.upenn.edu/polariton-sim.
  2. Map a linear layer to the polariton mesh by running the supplied PyTorch-to-polariton compiler.
  3. Submit the GDSII to an AIM Photonics shuttle; expect first silicon with measured MAC energy below 3 picojoules.

Read the original at sciencedaily.com

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  • The Yinzer BS detector

    Pitt Researchers Build Light-Matter Hybrid That Could Cut AI Power Bills

  • Karen what's the catch

    I am NOT okay with this: another lab promises faster AI with mysterious light particles while we still pay the electric bill

  • The Anchor what could go wrong

    THIS IS HOW IT STARTS... PENN SCIENTISTS JUST BUILT THE HYBRID PARTICLE THAT WILL REPLACE YOUR CPU

  • The Boss hype translator

    Penn Researchers Just Dropped a Hybrid Light-Matter Particle That Could 10x AI Speed While Cutting Energy