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mathematical sciences, Computational Sciences & Mathematics

PNNL’s Computing Research portfolio—spanning from basic to applied—includes data and computational engineering, high-performance computing, applied mathematics, semantic and human language technologies, machine learning, data and computing architectures, systems integration, and software and application development.
At PNNL, scientists, engineers, programmers, and researchers work together to apply advanced theories, methods, algorithms, models, evaluation tools and testbeds, and computational-based solutions address complex scientific challenges affecting energy, biological sciences, the environment, and national security.


Setting the Standards

In a collaboration with the World Wide Web Consortium, known as W3C, PNNL data scientists Eric Stephan and Sumit Purohit were recognized for their contributions to Data on the Web Best Practices, a standards guide documenting best practices for data on the Web that recently was published as a formal Recommendation. These best practices offer data-sharing solutions for assuring scientific data have lasting impact.


A Publishing Machine

Roberto Gioiosa, a research scientist with PNNL’s High Performance Computing group, has been a publishing machine with several papers slated for presentation at major computing conferences, including IPDPS 2017, AsHES 2017, and CCGRID 2017, as well as a chapter in the recently released book, Rugged Embedded Systems: Computing in Harsh Environments.


Hoisie Noted as 'One to Watch' in 2017

Adolfy Hoisie, PNNL’s Chief Scientist for Computing and Laboratory Fellow, recently was named one of a dozen “People to Watch” in 2017 by HPCwire. He joins an international mix of top high-performance computing talent, representing industry, such as AMD, Baidu, and Google, as well as computer scientists and researchers from other Department of Energy national laboratories.


Ready for the Dawn of Aurora

Argonne Leadership Computing Facility recently named 10 computational research projects for its Aurora Early Science Program. Among them, the PNNL-led NWChemEx Exascale Computing Project that aims to develop a new version of the popular computational chemistry code, NWChem. The time on Aurora will enable the NWChemEx team to develop, test, design, and implement NWChemEx on a computing system geared directly for exascale computing.


Tumeo Starts New Year as ACM Senior Member

Congratulations to Antonino Tumeo, a scientist in the ACMD Division’s High Performance Computing group, who kicked off 2017 by being named a Senior Member for the Association for Computing Machinery. ACM uses this designation to recognize senior members for their exceptional performance that “sets them apart from their peers.”

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