This requires an algorithm: students are taught to stack one number atop another and multiply each digit of the bottom number ...

Matrix multiplication is a key operation in scientific computing and machine learning, with GPU libraries like NVIDIA Cutlass and cuBLAS providing optimized implementations of the three nested loop ...

Matrix multiplication is one of the most basic algebraic operations. Since Strassen's surprising breakthrough algorithm from 1969, which showed that matrices can be multiplied faster than the most ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...

Over the past several years, there has been a steady drumbeat of warnings about the impact of quantum computing on traditional encryption methods, with consistent calls for organizations – both within ...

Introduction: Stroke remains a leading cause of morbidity and mortality globally, with a 23% relative annual increase in incidence worldwide and a staggering 87% rise in the United States alone.

It’s hard to ignore the seismic shifts brought about by algorithm-driven content. Every time you scroll through your social media feed or check your favorite news app, algorithms are diligently at ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

This is an implementation of the Karatsuba polynomial multiplication algorithm in the LEGv8 assembly language, a RISC ISA part of the ARM architecture family. This was done as my final project for ECE ...