IEEE

Toward Realism: Sparse Matrix Statistics in the North American and Synthetic Electric Grid Models

Abstract: This letter uses sparse matrix statistics to highlight a structural gap between North American grid models and the synthetic cases commonly used in research. North American grids exhibit ...
IEEE

Scalable In-Memory Computing Architectures for Sparse Matrix Multiplication

Abstract: 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 ...
marktechpost

Google AI Introduces STATIC: A Sparse Matrix Framework Delivering 948x Faster Constrained Decoding for LLM Based Generative Retrieval

In industrial recommendation systems, the shift toward Generative Retrieval (GR) is replacing traditional embedding-based nearest neighbor search with Large Language Models (LLMs). These models ...
GitHub

LinearKAN: A very fast implementation of Kolmogorov-Arnold Networks via Dynamic Input-Indexed Matrix Multiplication

Kolmogorov-Arnold Networks (KANs) training and inference are accelerated by orders of magnitude through exploiting the structure of the uniform linear (C⁰) B-spline (see Fig. 1). Because the intervals ...