Abstract: Sparse matrix multiplication is an important component of linear algebra computations. Implementing sparse matrix multiplication on an associative processor (AP) enables high level of ...

Abstract: Memory hierarchy latency is one of the main problems that prevents processors from achieving high performance. To eliminate the need of loading/storing large sets of data, Resistive ...

Computer scientists have discovered a new way to multiply large matrices faster than ever before by eliminating a previously unknown inefficiency, reports Quanta Magazine. This could eventually ...

Matrix multiplication is at the heart of many machine learning breakthroughs, and it just got faster—twice. Last week, DeepMind announced it discovered a more efficient way to perform matrix ...

1. Image transformations in Computer Graphics as images are composed of matrix. number of variables. 4. Self-driving car navigation can be made more accurate as matrix multiplication can accurately ...