Accelerating ML Models and NP-Hard Optimisation Problems Using Light
In this talk, I shall introduce our efforts to build an Analog Optical Computer (AOC) to speed-up specialized computations. We estimate that AOC can offer more than 100x improvement in overall system efficiency in terms of Tera Operations per Second per Watt (TOPS/Watt at Int8 precision), as compared to state-of-the-art digital hardware, at scale.
Authors
- Daniel Cletheroe (ORCID: https://orcid.org/0009-0003-6444-9149)
- Babak Rahmani (ORCID: https://orcid.org/0000-0002-0856-9635)
- Jannes Gladrow (ORCID: https://orcid.org/0000-0002-2973-4492)
- Greg O’Shea
- Francesca Parmigiani (ORCID: https://orcid.org/0000-0001-7784-2829)
- Christos Gkantsidis (ORCID: https://orcid.org/0000-0002-6898-2368)
- Burcu Canakci (ORCID: https://orcid.org/0000-0002-8406-7768)
- James Clegg (ORCID: https://orcid.org/0009-0002-3428-7161)
- Kirill P. Kalinin (ORCID: https://orcid.org/0000-0003-0622-3056)
- Hitesh Ballani (ORCID: https://orcid.org/0000-0003-1573-3314)
- Grace Brennan
- Jiaqi Chu (ORCID: https://orcid.org/0009-0008-4744-334X)
- Douglas J. Kelly
- H.H.C. Kremer
- Ant Rowstron
- Fabian Falk
Institutions
- Microsoft Research (United Kingdom) (GB)
Publication Details
- Published
- 2025-06-23
- DOI
- https://doi.org/10.1109/cleo/europe-eqec65582.2025.11110570
- Primary Topic
- Image Enhancement Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00