Computer scientists have discovered a new way to multiply large matrices faster by eliminating a previously unknown inefficiency, leading to the largest improvement in matrix multiplication efficiency ...

High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...

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 ...

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