Keren Bergman, Columbia University at Multicore World 2023

Petascale photonic connectivity for energy efficient AI computing
Abstract
High-performance systems are increasingly bottlenecked by the energy and communications costs of interconnecting numerous compute and memory resources. Integrated silicon photonics offer the opportunity of embedding optical connectivity that directly delivers high off-chip communication bandwidth densities with low power consumption. Our recent work has shown how integrated silicon photonics with comb-driven dense wavelength-division multiplexing can scale to realize Pb/s chip escape bandwidths with sub-picojoule/bit energy consumption. Beyond alleviating the bandwidth/energy bottlenecks, embedded photonics can enable new architectures that leverage the distance independence of optical transmission with flexible connectivity tailored to accelerate distributed ML applications.