Explanipedia

In Situ Data Analysis Through Physics-informed Tensor Decompositions (LDRD Final Report) Open

Daniel Dunlavy, Eric Phipps, Hemanth Kolla, John N. Shadid, Edward Geoffrey Phillips · 2025

Performance Portable Gradient Computations Using Source Transformation Open

Kim Liegeois, Brian E. Kelley, Eric Phipps, Sivasankaran Rajamanickam, Vassil Vassilev · 2025

Derivative computation is a key component of optimization, sensitivity analysis, uncertainty quantification, and nonlinear solvers. Automatic differentiation (AD) is a powerful technique for evaluating such derivatives, and in recent years…

Trilinos: Enabling Scientific Computing Across Diverse Hardware Architectures at Scale Open

Matthias Mayr, Alexander Heinlein, Christian Glusa, Siva Rajamanickam, Maarten Arnst , et al. · 2025

Trilinos is a community-developed, open-source software framework that facilitates building large-scale, complex, multiscale, multiphysics simulation code bases for scientific and engineering problems. Since the Trilinos framework has unde…

Constrained Tensor Decompositions for Low-Rank Modeling of Multiphysics Simulation Data Open

Daniel Dunlavy, Eric Phipps, Hemanth Kolla, John N. Shadid, Phillips Edward · 2024

Performance Portable Gradient Computations Using Source Transformation Open

Kim Liegeois, Brian E. Kelley, Eric Phipps, Sivasankaran Rajamanickam, Vassil Vassilev , et al. · 2024

Hybrid Parallel Tucker Decomposition of Streaming Data Open

Eric Phipps, Saibal De, Hemanth Kolla, Antoine Meyer, Francesco Rizzi · 2024

Climate Mode Identification with Tensor Decompositions Open

Thomas Ehrmann, Eric Phipps, Diana Bull, Hemanth Kolla · 2024

Towards Reverse Mode Automatic Differentiation of Kokkos-Based Code Using the LLVM Compiler Infrastructure Open

Kim Liegeois, Brian E. Kelley, Eric Phipps, Sivasankaran Rajamanickam · 2024

Towards reverse mode automatic differentiation of Kokkos-based codes Open

Kim Liegeois, Brian E. Kelley, Eric Phipps, Sivasankaran Rajamanickam · 2024

Derivative computation is a key component of optimization, sensitivity analysis, uncertainty quantification, and the solving of nonlinear problems. Automatic differentiation (AD) is a powerful technique for evaluating such derivatives, and…

Efficient Computation of Tucker Decomposition for Streaming Scientific Data Compression Open

Saibal De, Zitong Li, Hemanth Kolla, Eric Phipps · 2023

The Tucker decomposition, an extension of singular value decomposition for higher-order tensors, is a useful tool in analysis and compression of large-scale scientific data. While it has been studied extensively for static datasets, there …

Constrained Tucker Decompositions and Conservation Principles for Direct Numerical Simulation Data Compression Open

Daniel Dunlavy, Eric Phipps, Hemanth Kolla, John N. Shadid, Edward Geoffrey Phillips · 2023

Strengthening the US Department of Energy’s Recruitment Pipeline: The DOE/NNSA Predictive Science Academic Alliance Program (PSAAP) Experience Open

John Holmen, Verónica Melesse Vergara, Erik W. Draeger, Eric Phipps, Philip J. Smith , et al. · 2023

The US Department of Energy (DOE) oversees a system of 17 national laboratories responsible for developing unique scientific capabilities beyond the scope of academic and industrial institutions. These labs strive to keep America at the fo…

An Assessment of the Laminar Hypersonic Double-Cone Experiments in the LENS-XX Tunnel Open

Jaideep Ray, Patrick Blonigan, Eric Phipps, Kathryn Maupin · 2023

This is an investigation on two experimental datasets of laminar hypersonic flows, over a double-cone geometry, acquired in Calspan—University at Buffalo Research Center’s Large Energy National Shock (LENS)-XX expansion tunnel. These datas…

Generalized Canonical Polyadic Tensor Decompositions for Streaming Data Open

Eric Phipps, Nicholas Johnson, Tamara G. Kolda · 2023

Low-Rank Tensor Decompositions with Nonlinear Constraints for Conserving Quantities of Interest in Numerical Simulation Data Modeling Open

Daniel Dunlavy, Hemanth Kolla, Eric Phipps, John N. Shadid, Edward Geoffrey Phillips · 2023

Incremental update techniques for online analysis of streaming tensor data Open

Eric Phipps, Saibal De, Hemanth Kolla, Nicholas Johnson, Tamara G. Kolda , et al. · 2023

Conserving Quantities of Interest in Low-Rank Tensor Decompositions of Numerical Simulation Data Open

Daniel Dunlavy, Hemanth Kolla, Eric Phipps · 2023

An Assessment of the Laminar Hypersonic Double-Cone Experiments in the LENS-XX Tunnel Open

Jaideep Ray, Patrick Blonigan, Eric Phipps, Kathryn Maupin · 2023

In this paper, we investigate two experimental datasets of laminar hypersonic flows, in vibrational and reactive non-equilibrium, over a double-cone geometry, acquired in CUBRC's LENS-XX expansion tunnel. These datasets have yet to be mode…

Majorize-Minimize Algorithms for Streaming Generalized Canonical Polyadic Tensor Decompositions. Open

Kyle Gilman, Eric Phipps · 2022

An Assessment of the Laminar Hypersonic Double-Cone Experiments in the LENS-XX Tunnel . Open

Jaideep Ray, Eric Phipps, Patrick Blonigan, Kathryn Maupin · 2022

An Assessment of the Laminar Hypersonic Double-Cone Experiments in the LENS-XX Tunnel (vignette). Open

Jaideep Ray, Patrick Blonigan, Eric Phipps, Kathryn Maupin · 2022

Automatic Differentiation of C++ Codes on Emerging Manycore Architectures with Sacado Open

Eric Phipps, Roger P. Pawlowski, Christian Robert Trott · 2022

Automatic differentiation (AD) is a well-known technique for evaluating analytic derivatives of calculations implemented on a computer, with numerous software tools available for incorporating AD technology into complex applications. Howev…

Split Bregman optimizer for online generalized CP tensor decomposition. Open

Kyle Gilman, Eric Phipps, Hemanth Kolla · 2022

ExaLearn – GenTen Tensor Software ECP Milestone Open

Hemanth Kolla, Eric Phipps, Michael Wolf · 2022

The objective of this milestone was to finish integrating GenTen tensor software with combustion application Pele using the Ascent in situ analysis software, partnering with the ALPINE and Pele teams. Also, to demonstrate the usage of the …

FIST-HOSVD Open

Benjamin Cobb, Hemanth Kolla, Eric Phipps, Ümit V. Çatalyürek · 2022

In this paper, several novel methods of improving the memory locality of the Sequentially Truncated Higher Order Singular Value Decomposition (ST-HOSVD) algorithm for computing the Tucker decomposition are presented. We show how the two pr…

Parallel memory-efficient computation of symmetric higher-order joint moment tensors Open

Zitong Li, Hemanth Kolla, Eric Phipps · 2022

The decomposition of higher-order joint cumulant tensors of spatio-temporal data sets is useful in analyzing multi-variate non-Gaussian statistics with a wide variety of applications (e.g. anomaly detection, independent component analysis,…

Parallel Memory-Efficient Computation of Symmetric Higher-Order Joint Moment Tensors. Open

Zitong Li, Hemanth Kolla, Eric Phipps · 2022

Automatic Differentiation of C++ Codes with Sacado. Open

Eric Phipps · 2021

Streaming Generalized Canonical Polyadic Tensor Decompositions Open

Eric Phipps, Nick Johnson, Tamara G. Kolda · 2021

In this paper, we develop a method which we call OnlineGCP for computing the Generalized Canonical Polyadic (GCP) tensor decomposition of streaming data. GCP differs from traditional canonical polyadic (CP) tensor decompositions as it allo…

Streaming Generalized Canonical Polyadic Tensor Decompositions Open

Eric Phipps, Nick Johnson, Tamara G. Kolda · 2021

In this paper, we develop a method which we call OnlineGCP for computing the Generalized Canonical Polyadic (GCP) tensor decomposition of streaming data. GCP differs from traditional canonical polyadic (CP) tensor decompositions as it allo…

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