Matrix, the pioneer in generative AI inference compute for data centers, has closed $275 million in Series C funding, valuing the company at $2 billion and bringing the total raised to date to $450 ...

Chip startup d-Matrix Inc. today disclosed that it has raised $275 million in funding to support its commercialization ...

At the Financial Analyst Day, AMD's leadership presented many plans for the coming years. Much remained unspecific, but there ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

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 ...

I was in a meeting last week raging about the stupidity of nvidia's current valuation. They fell into this completely by accident, TWICE (crypto and now LLMs). There is no guarantee that GPUs will be ...

Large language models such as ChaptGPT have proven to be able to produce remarkably intelligent results, but the energy and monetary costs associated with running these massive algorithms is sky high.

Department of Chemistry, Wayne State University, 48202, Detroit, MI, USA Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all ...

Over the past decade, Graphics Processing Units (GPUs) have revolutionized high-performance computing, playing pivotal roles in advancing fields like IoT, autonomous vehicles, and exascale computing.

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 ...