“Since this vector-matrix multiplication computation is done optically and simultaneously, one does not need to store the intermediate-stage information. Therefore, the results and processes are less ...

Real PIM systems can provide high levels of parallelism, large aggregate memory bandwidth and low memory access latency, thereby being a good fit to accelerate the widely-used, memory-bound Sparse ...

Sparse Matrix Multiplication October 1, 2015 by MichaelS Sparse matrix computations are prevalent in many scientific and technical applications. In many simulation applications, the solving of the ...

Nearly all big science, machine learning, neural network, and machine vision applications employ algorithms that involve large matrix-matrix multiplication. But multiplying large matrices pushes the ...

Photonic accelerators have been widely designed to accelerate some specific categories of computing in the optical domain, especially matrix multiplication, to address the growing demand for ...

A novel AI-acceleration paper presents a method to optimize sparse matrix multiplication for machine learning models, particularly focusing on structured sparsity. Structured sparsity involves a ...

Automattic, the open source force behind WordPress.com, WooCommerce, Longreads, Simplenote and Tumblr, has made a $4.6M strategic investment into New Vector — the creators of an open ...

Also, we want to calculate E4' in the form of 'matrix and vector multiplication', because in the world of deep learning, the matrix parameters can be trained based on data.