At the root of this challenge lies an often-overlooked solution: design.

NVIDIA is rolling out AI data center reference designs that combine digital twins with power, cooling, and controls ...

Machine intelligence enables a new era of productivity and is becoming an integral part of our lives and societies across many disciplines and functions. Machine intelligence relies on computing ...

While compute devices such as CPUs, GPUs, and XPUs are stealing the limelight in the artificial intelligence (AI) era, there is an increasing realization that powering AI at scale demands new power ...

Large language models (LLMs) and other neural networks draw substantial power when processing complex artificial-intelligence (AI) and machine-learning (ML) workloads. Designed for traditional server ...

A new KAIST roadmap reveals HBM8-powered GPUs could consume more than 15kW per module by 2035, pushing current infrastructure, cooling systems, and power grids to breaking point. The next generation ...

The study explains that energy use in data centres is dominated by two processes: computing and cooling. Together, they ...

The demand for increased compute density. An evolution to ±400-V DC distribution to next-generation AI/ML supercomputer racks to meet that demand. Challenges and solutions in making the move to ±400-V ...

With A.I. workloads climbing, sustainable data infrastructure, especially in the Nordics region, may offer a blueprint for balancing growth and ESG. Unsplash+ Yet, more recently, awareness has grown ...

This AI powered approach enables chip designers to evaluate design quality, manufacturability, and performance much earlier ...