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Poster
in
Workshop: ML with New Compute Paradigms

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

Myoung-Gyun Suh

[ ] [ Project Page ]
[ OpenReview] 
Sun 15 Dec noon PST — 1:40 p.m. PST

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.

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