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Multi-wavelength photonics breakthrough performs AI math at light speed
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 ...
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