PHOENICS research is foundational in striving to create the blueprint for future photonic compute systems in a post-von-Neumann computing era.
PHOENICS stands for “Photonic enabled petascale in-memory computing with femtojoule energy consumption” and sums up the three goals of the project:
in-memory computing will allow data processing more similar to the human brain by removing the separation between computing and data storage units;
photonic technology will provide high speed data transport where current electronic systems face severe limitations;
photonic computing will lead to significant energy advantages.
Modern digital electronic technologies struggle with the enormous amount of generated and processed data. A growing gap arises between needs and capabilities of today’s information technology infrastructure. Conventional approaches based on electrical data processing are limited by the parameters of bandwith because of connectivity demands, latency because of sequential operation, and power efficiency because compute density does not scale linearly with the number of inputs.
By switching to the optical domain and nanophotonic circuits PHOENICS will set a new paradigm in AI and neuromorphic computing:
- Photonic interconnects can directly address the data transport problem: most of the energy on a modern microelectronic chip is consumed charging and discharging metal wires.
- Photonic systems can utilize optical multiplexing and high speed signals to achieve ultrahigh bandwidth density. This translates to a very high computational density (ops/s/mm2).
- Energy efficiency: Implementing linear operations such as multiply-accumulate (MAC) in the photonic domain does not intrinsically consume any significant energy.
The PHOENICS project aims to establish neuromorphic photonic hardware to realize next generation compute platforms for AI.