Hypermultiplexed integrated-photonics-based optical tensor processor

The escalating data volume and complexity resulting from the rapid
expansion of artificial intelligence (AI), internet of things (IoT), and
5G/6G mobile networks is creating an urgent need for energy-efficient,
scalable computing hardware. Here we demonstrate a hypermultiplexed
integrated photonics-based tensor optical processor (HITOP) that can
perform trillions of operations per second (TOPS) at the energy efficiency
of 40 TOPS/W. Space-time-wavelength three-dimensional (3D) optical
parallelism enables O(N2) operations per clock-cycle using O(N) modulator
devices. The system is built with wafer-fabricated III/V micron-scale
lasers and high-speed thin-film Lithium-Niobate electro-optics for
encoding at 10s femtojoule/symbol. Lasing threshold incorporates an analog
inline rectifier (ReLu) nonlinearity for low-latency activation. The
system scalability is verified with machine learning models of 405,000
parameters. A combination of high clockrates, energy-efficient processing,
and programmability unlocks the potential of light for large-scale AI
accelerators in applications ranging from training of large AI models to
real-time decision making in edge deployment.