This paper introduces a revolutionary, high-speed hybrid photonic-electronic memory architecture designed to solve the Von Neumann "Memory Wall" in AI tensor hardware accelerators. By exploiting the compile-time deterministic execution schedules of transformer models, the architecture translates data retention intervals directly into spatial light-propagation delays, bypassing traditional energy-intensive Optical-Electronic-Optical (OEO) conversion loops. The system utilizes a Time-Hierarchical split: short-term data (<0.5 μs) is managed on-chip via silicon-on-insulator (SOI) dispersive spirals, while intermediate macro delays (0.5 to 10.0 μs) are routed through a cascaded series network. This network combines co-packaged, high-density 2.043 km ultra-thin single-mode fiber spools (adapted from low-loss UAV tether technologies developed by 3DTech, Kyiv, Ukraine) for coarse delay blocks with on-chip spirals for sub-picosecond fine-tuning steps. Operating completely in the linear optical regime, the system eliminates the need for inline amplifiers or complex soliton management, delivering a 256 Mbit (32 MB) high-throughput, low-power volatile matrix activation cache layer with a Bit Error Rate (BER) < 10⁻¹⁵.
McCristal Robert (Thu,) studied this question.