Mathematics for Analysis of Petascale Data | Apply Online

Opportunity Summary:

The Department of Energy (DOE) Office of Science, through the Office of Advanced Scientific Computing Research (ASCR) Applied Mathematics program, invited grant applications focused on the core mathematical problems that arise when trying to extract knowledge from extremely large datasets at the petascale. The central idea of the opportunity is not simply to analyze a large scientific dataset, but to create new mathematics and new numerical algorithms that make petascale-scale analysis possible, reliable, and insightful. Proposed work is expected to tackle fundamental issues such as how to identify the most important features in massive data and how to understand relationships among those features, especially when the data are too large, too complex, or too irregular for conventional methods.

The announcement frames petascale data broadly as the output of both computation and measurement. On the computing side, the DOE highlighted high-resolution simulations running on massively parallel machines, including major applications like climate modeling, fusion energy simulations, and other large-scale science and engineering computations. On the experimental and observational side, it also pointed to domains such as high energy physics and cosmology, where instruments and detectors produce huge volumes of data. Across these settings, the same practical obstacles repeat: the data may be distributed across systems, heterogeneous in type and structure, and characterized by statistical properties that change across space, time, or experimental conditions. The funding call emphasizes that these traits are not side details; they drive the need for fundamentally different mathematical approaches to representation, analysis, and interpretation.

A key requirement is that applications must be anchored in advances in mathematical methods or numerical algorithms. In other words, the DOE was seeking work that pushes the state of the art in the underlying mathematics of large-scale data analysis rather than proposals that mainly apply existing tools to a particular scientific problem, even if that problem is difficult and the dataset is huge. The intended outcome is a set of broadly useful models, methods, and tools that can generalize across DOE-relevant scientific domains and enable discovery from petascale datasets that would otherwise be impractical to analyze.

From an administrative standpoint, this was a discretionary funding opportunity using a grant mechanism within the Office of Science financial assistance program (CFDA 81.049). It did not require cost sharing or matching. Eligibility was listed as unrestricted, meaning it was open to any type of applicant organization, subject to any clarifications that might appear in the full announcement materials. The funding opportunity number was DE-PS02-09ER09-10, with the title "Mathematics for Analysis of Petascale Data." The opportunity was posted and created on March 30, 2009, with an application closing date of May 29, 2009, and an archive date of March 30, 2010.

The primary technical contact named in the announcement was Dr. Alexandra Landsberg in the ASCR Applied Mathematics program (landsberg@ascr.doe.gov, phone 301-903-8507, fax 301-903-7774). For access or system issues related to the electronic announcement, the notice pointed applicants to the IIPS HelpDesk (iipshelpdesk@e-center.doe.gov) and listed Lori Jernigan (Lori.Jernigan@science.doe.gov) as an additional point of contact for linking or opportunity access problems. Educational components were described as welcome but explicitly not required or emphasized, reinforcing that the core focus was research innovation in mathematics and algorithms for petascale data analysis.

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