Paul Kuberry

dblp:119/8830 · also Paul A. Kuberry · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
0000-0002-2426-4591ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021Theory of computation · 1 · 1 since 2021
YearPublicationVenuePosition
2026 Trilinos: Enabling Scientific Computing across Diverse Hardware Architectures at Scale
abstract
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 undergone substantial changes to support new applications and new hardware architectures, this document is an update to “An Overview of the Trilinos project” by Heroux et al. (ACM Transactions on Mathematical Software, 31(3):397–423, 2005). It describes the design of Trilinos, introduces its new organization in product areas, and highlights established and new features available in Trilinos. Particular focus is put on the modernized software stack based on the Kokkos ecosystem to deliver performance portability across heterogeneous hardware architectures. This article also outlines the organization of the Trilinos community and the contribution model to help onboard interested users and contributors.
Matthias Mayr, Alexander Heinlein, Christian A. Glusa, Sivasankaran Rajamanickam, Maarten Arnst, Roscoe A. Bartlett, Luc Berger-Vergiat, Erik G. Bowman, Karen D. Devine, Graham Harper, Michael A. Heroux, Mark Hoemmen, Jonathan J. Hu, Brian Michael Kelley, Kyungjoo Kim, Drew P. Kouri, Paul Kuberry, Kim Liegeois, Curtis C. Ober, Roger P. Pawlowski, Carl Pearson, Mauro Perego, Eric T. Phipps, Denis Ridzal, Nathan V. Roberts, Christopher M. Siefert, Heidi Thornquist, Romin Tomasetti, Christian Trott, Ray S. Tuminaro, James M. Willenbring, Michael M. Wolf, Ichitaro Yamazaki
ACM Trans. Math. Softw.17
2025 Nonintrusive Data-Driven Model Order Reduction for Circuits Based on Hammerstein Architectures
abstract
We demonstrate that system identification techniques can provide a basis for effective, nonintrusive model order reduction (MOR) for common circuits that are key building blocks in microelectronics. Our approach is motivated by the practical operation of these circuits and utilizes a canonical Hammerstein architecture. To demonstrate the approach we develop parsimonious Hammerstein models for a nonlinear CMOS differential amplifier and an operational amplifier circuit. We train these models on a combination of direct current (DC) and transient SPICE circuit simulation data using a novel sequential strategy to identify their static nonlinear and linear dynamical parts. Simulation results show that the Hammerstein model is an effective surrogate for these types of circuits that accurately and efficiently reproduces their behavior over a wide range of operating points and input frequencies.
Joshua Hanson, Paul Kuberry, Biliana S. Paskaleva, Pavel B. Bochev
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.2