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

Quantum computing promises leaps in chemistry and materials science, and PNNL is preparing to realize its potential with a collaborative approach.

Christina Lomasney moderates panel on commercialization pathways for emerging artificial intelligence and high-performance computing technologies.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

PNNL biodefense experts seek to identify, understand and mitigate the risks of biological pathogens—whether naturally occurring or intentionally created—so steps can be taken to prepare and respond.

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.

Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.

At the Nonproliferation, Counterproliferation, and Disarmament Science Gordon Research Conference, researchers from PNNL shared research and scientific approaches for countering diverse threats.

Scientists have developed a better way to recognize denial-of-service internet attacks, improving detection by 90 percent.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

Researchers have knitted together three large databases of information to help cybersecurity experts detect and prevent attacks.

Scientists have taken a key step toward harnessing a form of AI known as deep reinforcement learning to protect computer networks.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

James Ang, John Feo, and Marco Minutoli organized a high performance computing workshop at the prestigious ISC High Performance 2022 conference.

PNNL researchers contributed to the International Conference on Data Science and Advanced Analytics 2021 Best Paper Award-winning publication.

PNNL’s suite of Solid Phase Processing tools like Cold Spray is helping to strengthen hydroelectric dam materials such as turbines.

DOE’s continued support will allow CENATE researchers to advance computing through the evaluation of novel technologies.

PNNL computer scientist Ang Li serves as one of the principal investigators for a project selected to receive DOE funding.

Researchers to design their own computer accelerators for faster analysis of large datasets.