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

OpenCGRA expedites the design-prototype cycle of computer architecture development.

New research aids the design of more efficient water purification technologies.

A research project that brings together mathematicians and atmospheric scientists has developed into a deep collaboration for improving atmospheric models.

Marcel Baer is a computational scientist working in PNNL’s Physical Sciences Division with a prominent effort in materials science and physical bioscience.

With quantum chemistry, researchers led by PNNL computational scientist Simone Raugei are discovering how enzymes such as nitrogenase serve as natural catalysts that efficiently break apart molecular bonds to control energy and matter.

PNNL highlights four researchers whose joint appointments are creating new and diverse opportunities for expanding knowledge and scientific impact across institutions.

George Karniadakis receives award highlighting 30 years of work developing computational methods to solve real-world problems.

Connected moments math shortcut shaves time and cost of quantum calculations while maintaining accuracy.

Using public data from the entire 1,500-square-mile Los Angeles metropolitan area, PNNL researchers reduced the time needed to create a traffic congestion model by an order of magnitude, from hours to minutes.

PNNL researchers have shown an improved binarized neural network can deliver a low-cost and low-energy computation to help the performance of smart devices and the power grid.

The project received an Innovative and Novel Computational Impact on Theory and Experiment (INCITE) award, a highly competitive U.S. Department of Energy Office of Science program.

PNNL and Microsoft Quantum partner to link quantum circuits to powerful government supercomputers.

Pacific Northwest National Laboratory researchers developed a graphical processing unit (GPU)-centered quantum computer simulator that can be 10 times faster than any other quantum computer simulator.

PNNL’s new Smart Power Grid Simulator, or Smart-PGSim, combines high-performance computing and artificial intelligence to optimize power grid simulations without sacrificing accuracy.

The MIT-sponsored competition encourages community approaches to developing new solutions for analyzing graphs and sparse data; PNNL has placed a winner in each year.

Tracking down nefarious users is just one example of work at PNNL’s Center for Advanced Technology Evaluation, a computing proving ground supported by DOE’s Advanced Scientific Computing Research program.

Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.

PNNL quantum computing pioneer Nathan Wiebe contributed to a Google-led quantum computing landmark study published in the journal Science.

Making sure there’s enough electricity at the lowest price is a critical endeavor undertaken daily by electricity market operators. Now, there’s an approach that provides more timely and accurate information to make day-ahead decisions.