Scalable In-Memory Computing Architectures for Sparse Matrix Multiplication

We present two novel memory-dense and fully parallel architectures for analog sparse matrix multiplication: one based on memristive nanowires, and the other based on 3D lithographic memristors, both realized on a CMOS-integrated chip, Cumulus. We experimentally demonstrate accurate generation of deterministic chaotic signals via an echo state network on Cumulus.