246 citations · 375 across the 4 of their papers we have counts for
6 papers
LightOn Optical Processing Unit: Scaling-up AI and HPC with a Non von Neumann co-processor
Charles Brossollet, Alessandro Cappelli, Igor Carron +14
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 TeraOP…
Photonic co-processors in HPC: using LightOn OPUs for Randomized Numerical Linear Algebra
Daniel Hesslow, Alessandro Cappelli, Igor Carron +6
Randomized Numerical Linear Algebra (RandNLA) is a powerful class of methods, widely used in High Performance Computing (HPC). RandNLA provides approximate solutions to linear alge…
Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment
Julien Launay, Iacopo Poli, Kilian Müller +5
The scaling hypothesis motivates the expansion of models past trillions of parameters as a path towards better performance. Recent significant developments, such as GPT-3, have bee…
Light-in-the-loop: using a photonics co-processor for scalable training of neural networks
Julien Launay, Iacopo Poli, Kilian Müller +4
As neural networks grow larger and more complex and data-hungry, training costs are skyrocketing. Especially when lifelong learning is necessary, such as in recommender systems or…
Random Projections through multiple optical scattering: Approximating kernels at the speed of light
Alaa Saade, Francesco Caltagirone, Igor Carron +4
Random projections have proven extremely useful in many signal processing and machine learning applications. However, they often require either to store a very large random matrix,…
Imaging With Nature: Compressive Imaging Using a Multiply Scattering Medium
Antoine Liutkus, David Martina, Sébastien Popoff +6
The recent theory of compressive sensing leverages upon the structure of signals to acquire them with much fewer measurements than was previously thought necessary, and certainly w…