H3DFact: Heterogeneous 3D Integrated CIM for Factorization with Holographic Perceptual Representations

arXiv:2404.04173v1 Announce Type: cross
Abstract: Disentangling attributes of various sensory signals is central to human-like perception and reasoning and a critical task for higher-order cognitive and neuro-symbolic AI systems. An elegant approach to represent this intricate factorization is via high-dimensional holographic vectors drawing on brain-inspired vector symbolic architectures. However, holographic factorization involves iterative computation with high-dimensional matrix-vector multiplications and suffers from non-convergence problems.
In this paper, we present H3DFact, a heterogeneous 3D integrated in-memory compute engine capable of efficiently factorizing …

abstract ai systems architectures arxiv brain brain-inspired cognitive cs.ar cs.lg factorization however human human-like neuro neuro-symbolic ai perception reasoning sensory symbolic ai systems type vector vectors via