Nearly all big science, machine learning, neural network, and machine vision applications employ algorithms that involve large matrix-matrix multiplication. But multiplying large matrices pushes the ...

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Oracle Spatial is a powerful set of Oracle objects for storing, manipulating, and querying graphical shapes. There are many transformation functions to find complicated results such as the ...

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 ...

With AlphaTensor, DeepMind Technologies has presented an AI system that is supposed to independently find novel, efficient and provably correct algorithms for complex mathematical tasks. AlphaTensor ...

A team of researchers developed “parallel optical matrix-matrix multiplication” (POMMM), which could revolutionize tensor ...

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

Photonics is promising to handle extensive vector multiplications in AI applications. Scientists in China have promoted a programmable and reconfigurable photonic linear vector machine named SUANPAN, ...