PNNL convenes leaders from the Department of Energy, national laboratories, computing industry and academia for a two-day workshop to advance quantum computing for computational chemistry.

Computer scientist Antonino Tumeo is guest editing a special issue of IEEE’s Computer publication focused on democratizing microelectronics.

The comprehensive guide can help companies build AI data centers that keep energy costs low and maintain grid stability.

A research team from Pacific Northwest National Laboratory used machine reasoning to schedule scientific workflows while guaranteeing quality of service (QoS).

PNNL’s Robert Rallo and Nathan Hodas speak to students about the future of AI.

An international research team deployed AI-powered computing to solve important chemical structures for energy applications using NVIDIA hardware.

PNNL set to create a practical path for near-term hybrid classical-quantum computers with NVIDIA accelerated computing.

Connecting energy generation, electricity storage, and using sensors and control software to track load, including precommercial market marine energy generation technologies.

The Scientific Discovery through Advanced Computing institute will focus on making scientific machine learning accessible to domain scientists.

The Genesis Mission will mobilize the Department of Energy’s 17 National Laboratories, industry, and academia to build an integrated discovery platform.

This achievement earned DIMPLES a Best Paper award at the ACM International Conference on Supercomputing 2025.

As Laboratory Director Steve Ashby pens his last monthly column, he highlights PNNL’s accomplishments with pride and gratitude.

Micron and PNNL co-design the Crete computer system, delivering a new memory architecture for data-intensive scientific computing and AI applications.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

A new generation of microelectronics research begins at PNNL.

Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.

The speed and agility of cloud computing opens doors to completing advanced computational chemistry workflows in days instead of months.

Researchers discussed this topic at the 2024 Analog Computing for Science Workshop co-led by Antonino Tumeo.

PNNL researchers are exploring the kinds of flicker waveforms that the eye and brain can detect, seeking to understand the different visual and non-visual effects that result.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.