# LightOn Optical Processing Unit: Scaling-up AI and HPC with a Non von Neumann co-processor

arXiv: https://arxiv.org/abs/2107.11814 · HTML: https://mlsanity.com/paper/2107.11814/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Jul 2021.

## Built on by (most cited first, 5 of 5)

- [Nonlinear optical encoding enabled by recurrent linear scattering](https://mlsanity.com/paper/2307.08558/) (2023)
- [Neural Brain: A Neuroscience-inspired Framework for Embodied Agents](https://mlsanity.com/paper/2505.07634/) (2025)
- [Scaling Laws Beyond Backpropagation](https://mlsanity.com/paper/2210.14593/) (2022)
- [Is the Number of Trainable Parameters All That Actually Matters?](https://mlsanity.com/paper/2109.11928/) (2021)
- [Training deep physical neural networks with local physical information bottleneck](https://mlsanity.com/paper/2602.09569/) (2026)

## Abstract (arXiv)

We introduce LightOn's Optical Processing Unit (OPU), the first photonic AI accelerator chip available on the market for at-scale Non von Neumann computations, reaching 1500 TeraOPS. It relies on a combination of free-space optics with off-the-shelf components, together with a software API allowing a seamless integration within Python-based processing pipelines. We discuss a variety of use cases and hybrid network architectures, with the OPU used in combination of CPU/GPU, and draw a pathway towards "optical advantage".