The development of low-loss reconfigurable integrated optical devices enables further research into technologies including photonic signal processing, analogue quantum computing, and optical neural ...

1. Introduction Solving a linear system A x = b is a basic algorithmic problem with direct applications to scientific computing, engineering, and physics, and is at the core of algorithms for many ...

data point (a.k.a. training case): One item of data; affinity propagation clusters data points exemplar: A data point that is nicely representative of itself and some other data points. similarity: ...

General sparse matrix–matrix multiplication (SpGEMM) is integral to many high-performance computing (HPC) and machine learning applications. However, prior field-programmable gate array (FPGA)-based ...

Leopard is a fast, modern implementation of sparse, multifrontal symmetric indefinite matrix factorization. It lets you factorize and solve for large sparse matrices much faster than what is possible ...

The first is a sparse dictionary learning algorithm in order to estimate Green’s function vectors between focal or source points in the image window and receiver locations on the array. The second is ...