Artificial intelligence grows more demanding every year. Modern models learn and operate by pushing huge volumes of data ...

The future of computing has arrived in a flash, literally. In A Nutshell Researchers created a computer that performs complex ...

Recently, a research team led by Prof. Sun Zhong at Peking University reported an analog hardware solution for real-time compressed sensing recovery, which has been published as an article titled ...

Sparse matrix computations are pivotal to advancing high-performance scientific applications, particularly as modern numerical simulations and data analyses demand efficient management of large, ...

I have the sense that some perspective is missing here. People should remember that every Boomer didn't spring wholly evil from the mind of a mid-1940's supervillain. The father figures of the Boomers ...

Sparse matrix computations are prevalent in many scientific and technical applications. In many simulation applications, the solving of the sparse matrix-vector multiplication (SpMV) is critical for ...

Most traditional high-performance computing applications focus on computations on very large matrices. Think seismic analysis, weather prediction, structural analysis. But today, with advances in deep ...