Hyperspectral Compute-In-Memory: An Opto-Electronic Computing Architecture Enabling Compute Density Beyond PetaOPS/mm$^2$

Myoung-Gyun Suh, Byoung Jun Park, Mostafa Honari Latifpour, Yoshihisa Yamamoto

Keywords: Compute-In-Memory, Optical Computing, Optical Frequency Combs, Artificial Intelligence

Abstract: We present a hyperspectral compute-in-memory architecture that utilizes both frequency and spatial dimensions for single-shot matrix-matrix multiplication. This approach offers exceptional parallelism, scalability, programmability, and efficient chip area utilization, potentially enabling a compute density exceeding PetaOPS/mm$^2$. The architecture demonstrates potential for energy-efficient, three-dimensional opto-electronic computing in future data center applications.

Submission Number: 43