Distributed computing has markedly advanced the efficiency and reliability of complex numerical tasks, particularly matrix multiplication, which is central to numerous computational applications from ...

Multiplying the content of two x-y matrices together for screen rendering and AI processing. Matrix multiplication provides a series of fast multiply and add operations in parallel, and it is built ...

AI training time is at a point in an exponential where more throughput isn't going to advance functionality much at all. The underlying problem, problem solving by training, is computationally ...

DESILO, a Privacy Enhancing Technology (PET) company, and Cornami, a leader in scalable compute acceleration, today announced new research that significantly improves the performance of encrypted AI ...

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 ...

Optical computing uses photons instead of electrons to perform computations, which can significantly increase the speed and energy efficiency of computations by overcoming the inherent limitations of ...

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 ...