Pacific Northwest National Laboratory partnered with the Treasury and Amazon Web Services to develop Cache, a cloud-based tool that allows the Treasury’s disparate data to be easily searched, translated, extracted, linked, and analyzed.
The Data-Model Convergence (DMC) Initiative is a multidisciplinary effort to create the next generation of scientific computing capability through a software and hardware co-design methodology.
The Flow Tradeoff Tool is a free, comprehensive software toolkit designed to evaluate trade-offs between hydropower energy production and environmental flows.
GeoBOSS is a software library that combines the data-handling capabilities of Spark and the user-friendliness of Python to simplify geospatial analytics and the transition between small-scale research and large-scale operational projects.
A new set of resources from PNNL helps guide dam owners and operators through response and recovery actions in the wake of cybersecurity or unusual incidents.
PNNL data scientists and engineers will be presenting at NeurIPS, the Thirty Fourth Conference on Neural Information Processing Systems, and the co-located Women in Machine Learning workshop, WiML.
The user-friendly Project Schedule Visualizer software developed at PNNL helps users readily identify and understand the impacts of updates to the schedule, budget, and risks associated with large, complex projects that cross departments.
Powered by few-shot learning, the Sharkzor AI-driven, scalable web application makes it possible to quickly characterize and sort electron microscopy images used to analyze radioactive materials.
This 18-month study will analyze how the region can meet its needs for reliable, resilient, and affordable energy along with decarbonization goals and other energy policies and priorities.
PNNL has developed a tool suite of interactive analytics that can be rapidly integrated into analyst workflows to empirically analyze and gain qualitative understanding of AI model performance jointly across dimensions.
