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

Parallel computing is an important method used in high performance computing. A new SIMD architecture named ESCA (Engineering and Science Computing Accelerator) is introduced briefly in this paper. It ...

Using an advanced Monte Carlo method, Caltech researchers found a way to tame the infinite complexity of Feynman diagrams and ...

In parallel, advancements in RSA processor design have integrated sophisticated enhancements to Montgomery multiplication and modular exponentiation, delivering improved throughput and reduced ...

A clever method from Caltech researchers now makes it possible to unravel complex electron-lattice interactions, potentially transforming how we understand and design quantum and electronic materials.

Discover Alpha Evolve, Google’s self-improving AI that’s redefining intelligence and reshaping the future of technology and innovation.

These factors greatly increase the complexity of algorithm design and challenge traditional ways of thinking about the design of parallel and distributed algorithms. Here, we review recent work on ...

In a paper published in Nature Physics, the Caltech team uses its new method to precisely compute the strength of ...

Caltech scientists have found a fast and efficient way to add up large numbers of Feynman diagrams, the simple drawings physicists use to represent particle interactions. The new method has already ...