Abstract: Code-based Distributed Matrix Multiplication (DMM) has been widely studied as an effective method for large-scale matrix computations in distributed systems. Two central challenges in ...

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...

TL;DR: ASUS has officially introduced the Level Sense feature to prevent GPU sag by using sensors to monitor whether the board is sagging in real-time, and warn the owner if this is happening. This ...

Researchers at FOM Institute for Atomic and Molecular Physics (AMOLF) in the Netherlands have developed a new type of soft, flexible material that can perform complex calculations, much like computers ...

(RTTNews) - Novavax, Inc. (NVAX) announced Tuesday progress on its collaboration and license agreement (CLA) with Sanofi SA (SNY) regarding Novavax's Matrix-M adjuvant. The companies have amended ...

Nothing’s original Glyph Interface was the perfect level of gimmick — it added a bit of flair to the back of its first few phones, but always felt like it had a purpose. I trusted it for everything ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

Google DeepMind’s AI systems have taken big scientific strides in recent years — from predicting the 3D structures of almost every known protein in the universe to forecasting weather more accurately ...

In the quest to transform organizations, leaders often champion bold visions: compelling declarations of a better future. Yet many of these dreams fizzle away. Why? Because they fail to bridge the ...