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mathematical sciences, Computational Sciences & Mathematics

We focus on merging high-performance computing with data-centric analysis capabilities to solve significant problems in energy, the environment, and national security. PNNL has made scientific breakthroughs and advanced frontiers in high-performance computer science, computational biology and bioinformatics, subsurface simulation modeling, and multiscale mathematics.

Jay Xu Named to International Journal of Computational Mathematics Editorial Board

Congratulations to Zhijie “Jay” Xu, of PNNL’s Multiscale Mathematics team (ACMD), who was named an editorial board member of the International Journal of Computational Mathematics, a peer-reviewed, open-access journal that publishes original research and review articles spanning all areas of computational mathematics. He joins a 25-person international board with diverse mathematics-based expertise and is the sole representative from a U.S. Department of Energy national laboratory.

Kleese van Dam to Discuss Computing Infrastructure Deployment at SMC2014

Kerstin Kleese van Dam, a senior researcher in PNNL's Data Sciences group, was invited to speak at the upcoming 2014 Smoky Mountains Computational Sciences and Engineering Conference, or SMC2014, where she will address a session devoted to "Math and Computer Science Challenges for Big Data, Analytics, and Scalable Applications." The invitation-only conference, to be held September 2-4, 2014 in Gatlinburg, Tennessee, is being hosted by Oak Ridge National Laboratory. The conference, featuring computing and engineering experts from national laboratories, academia, government, and private industry, seeks to generate collaborations and leadership relevant to research involving high-priority computational science applications.


With Three Papers in SC14, Krishnamoorthy Proves 'HPC Matters' to PNNL

Sriram Krishnamoorthy, a research scientist with PNNL’s High Performance Computing group, is making a notable impact at this year’s SC14 conference as co-author of three accepted papers—two, of which, are up for Best Paper awards. This year, the SC14 conference accepted only 84 out of 392 paper submissions, which includes eight Best Paper and six Best Student Paper finalists.

Match. Color. Repeat.

When a frustrated car lover who just happens to have a keen interest in applied graph theory takes to Google, the search results can yield something interesting. In this case, one former professor’s online search for an efficient way to judge classic Jaguars led him to Dr. Mahantesh Halappanavar, a scientist with PNNL’s High Performance Computing group, whose research involving graph matching and coloring algorithms proved to be an opportune and novel matchup between classic cars and classical graph theory.

Tracking Data Changes

At the upcoming Third International Congress on Big Data, or BigData 2014, computer scientists and engineers from PNNL and Rensselaer Polytechnic Institute, working together as part of the Atmospheric Radiation Measurement (ARM) Data Integration team, will showcase their model for versioning complex data sets such as those generated and stored daily from the ARM Climate Research Facility’s fixed and mobile user facilities. Currently, the collection and storage pace for that data exceeds 10 terabytes monthly. Matt Macduff and Sherman Beus (PNNL) and their co-author Benno Lee (RPI) will present their paper, “Versioning Complex Data,” which addresses issues with changes to complex, large data sets meant as references for analysis and how to track and communicate those changes to users, during the BigData session on Friday, June 27, 2014.

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