Photonic innovation: researchers in the US have created an optical metamaterial that can perform vector–matrix multiplication. (Courtesy: iStock/Henrik5000) A new silicon photonics platform that can ...

There has been an ever-growing demand for artificial intelligence and fifth-generation communications globally, resulting in very large computing power and memory requirements. The slowing down or ...

Abstract: Sparse matrix-vector multiplication (SpMV) is a critical kernel in scientific computing and high-performance applications, yet it remains challenging to optimize due to irregular memory ...

Researchers at MIT's Computer Science & Artificial Intelligence Lab (CSAIL) have open-sourced Multiply-ADDitioN-lESS (MADDNESS), an algorithm that speeds up machine learning using approximate matrix ...

“Several manufacturers have already started to commercialize near-bank Processing-In-Memory (PIM) architectures. Near-bank PIM architectures place simple cores close to DRAM banks and can yield ...

This project is a framework for benchmarking a wide range of algorithms for sparse linear algebra using Scala and Apache Spark. It evaluates different data structures, sparse formats, and execution ...