Topology for Statistical Modeling of Petascale Data
- Univ. of Utah, Salt Lake City, UT (United States); University of Utah
- Univ. of Utah, Salt Lake City, UT (United States)
Many commonly used algorithms for mathematical analysis do not scale well enough to accommodate the size or complexity of petascale data produced by computational simulations. The primary goal of this project is to develop new mathematical tools that address both the petascale size and uncertain nature of current data. At a high level, the approach of the entire team involving all three institutions is based on the complementary techniques of combinatorial topology and statistical modelling. In particular, we use combinatorial topology to filter out spurious data that would otherwise skew statistical modelling techniques, and we employ advanced algorithms from algebraic statistics to efficiently find globally optimal fits to statistical models. The overall technical contributions can be divided loosely into three categories: (1) advances in the field of combinatorial topology, (2) advances in statistical modelling, and (3) new integrated topological and statistical methods. Roughly speaking, the division of labor between our 3 groups (Sandia Labs in Livermore, Texas A&M in College Station, and U Utah in Salt Lake City) is as follows: the Sandia group focuses on statistical methods and their formulation in algebraic terms, and finds the application problems (and data sets) most relevant to this project, the Texas A&M Group develops new algebraic geometry algorithms, in particular with fewnomial theory, and the Utah group develops new algorithms in computational topology via Discrete Morse Theory. However, we hasten to point out that our three groups stay in tight contact via videconference every 2 weeks, so there is much synergy of ideas between the groups. The following of this document is focused on the contributions that had grater direct involvement from the team at the University of Utah in Salt Lake City.
- Research Organization:
- Univ. of Utah, Salt Lake City, UT (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
- Contributing Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Texas A & M Univ., College Station, TX (United States)
- DOE Contract Number:
- SC0001922
- OSTI ID:
- 1347741
- Report Number(s):
- DOE-Utah--1922
- Country of Publication:
- United States
- Language:
- English
Similar Records
Final report for Texas A&M University Group Contribution to DE-FG02-09ER25949/DE-SC0002505: Topology for Statistical Modeling of Petascale Data (and ASCR-funded collaboration between Sandia National Labs, Texas A&M University and University of Utah)
Topology for Statistical Modeling of Petascale Data