Multiplying two matrices is common in many applications and can be easily parallelized. First, lets look at a simple example of parallelizing a loop, in Fortran.

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 ...

Let D ⊂ ℂ be a bounded domain, whose boundary B consists of k simple closed continuous curves, and H∞ (D) be the algebra of bounded analytic functions on D. We prove the matrix-valued corona theorem ...

With Deep Reinforcement Learning, DeepMind has discovered an algorithm no human thought of. It is supposed to significantly accelerate matrix multiplication.