Abstract: A majority of coded matrix-matrix computation literature has broadly focused in two directions: matrix partitioning for computing a single computation task and batch processing of multiple ...

AlphaEvolve uses large language models to find new algorithms that outperform the best human-made solutions for data center management, chip design, and more. Google DeepMind has once again used large ...

FLUX is an educational deep learning framework that reimplements the core functionality of PyTorch and TensorFlow from scratch, using only C++ and the Standard Template Library. No external ...

Moore’s law is already pretty fast. It holds that computer chips pack in twice as many transistors every two years or so, producing major jumps in speed and efficiency. But the computing demands of ...

Extracellular biophysical properties have particular implications for a wide spectrum of cellular behaviors and functions, including growth, motility, differentiation, apoptosis, gene expression, cell ...

Two manipulator Jacobian matrix estimators for constrained planar snake robots are developed and tested, which enables the implementation of Jacobian-based obstacle-aided locomotion (OAL) control ...

Most of today’s quantum algorithms may not achieve practical speedups. Material science and chemistry have a huge potential and we hope more practical algorithms will be invented based on our ...