Advanced Computing,
Mathematics, and Data
Advanced Computing,
Mathematics, and Data
Data-Model Convergence
The Data-Model Convergence (DMC) Initiative is an ambitious, five-year effort to create the next generation of scientific computing capability through a multidisciplinary software and hardware co-design methodology.
CENATE
The Center for Advanced Technology Evaluation (CENATE) is a computing proving ground focused on integrated evaluation of early technologies to predict their potential and guide future systems design.
Exascale Computing Project
The Exascale Computing Project (ECP) is responsible for developing the strategy, aligning the resources, and conducting the research and development necessary to achieve the nation’s imperative of delivering exascale computing by 2021. PNNL is a participating laboratory partner with the ECP.
PhILMs
PhILMs (Physics-Informed Learning Machines) investigators are encoding physics knowledge into machine learning to: 1) Design functional materials with tunable properties; 2) Solve longstanding problems exhibiting scaling cascades in combustion, subsurface and earth systems s; and 3) Establish probabilistic scientific computing as a new discipline at the interface of computational mathematics, multi-fidelity data, information fusion, and deep learning.
ARIAA
The co-design Center for Artificial Intelligence-focused Architectures and Algorithms (ARIAA) promotes the development of core technologies important for the application of artificial intelligence (AI) to Department of Energy (DOE) mission priorities.