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When a numerical simulation has to handle a physics problem with a wide range of time-dependent length scales, dynamically adaptive discretizations can be the method of choice. We present a major upgrade to the numerical relativity code…

General Relativity and Quantum Cosmology · Physics 2023-05-31 Sarah Renkhoff , Daniela Cors , David Hilditch , Bernd Brügmann

We have carried out numerical simulations of strongly gravitating systems based on the Einstein equations coupled to the relativistic hydrodynamic equations using adaptive mesh refinement (AMR) techniques. We show AMR simulations of NS…

General Relativity and Quantum Cosmology · Physics 2009-11-11 Edwin Evans , Sai Iyer , Erik Schnetter , Wai-Mo Suen , Jian Tao , Randy Wolfmeyer , Hui-Min Zhang

Multi-resolution methods such as Adaptive Mesh Refinement (AMR) can enhance storage efficiency for HPC applications generating vast volumes of data. However, their applicability is limited and cannot be universally deployed across all…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-02 Daoce Wang , Pascal Grosset , Jesus Pulido , Tushar M. Athawale , Jiannan Tian , Kai Zhao , Zarija Lukić , Axel Huebl , Zhe Wang , James Ahrens , Dingwen Tao

We present an adaptive multilevel Monte Carlo (AMLMC) algorithm for approximating deterministic, real-valued, bounded linear functionals that depend on the solution of a linear elliptic PDE with a lognormal diffusivity coefficient and…

Numerical Analysis · Mathematics 2022-12-07 Joakim Beck , Yang Liu , Erik von Schwerin , Raúl Tempone

In recent work we have shown how an accurate reduced model can be utilized to perform mesh refinement in random space. That work relied on the explicit knowledge of an accurate reduced model which is used to monitor the transfer of activity…

Numerical Analysis · Mathematics 2016-09-21 Jing Li , Panos Stinis

Optimizing scientific applications to take full advan-tage of modern memory subsystems is a continual challenge forapplication and compiler developers. Factors beyond working setsize affect performance. A benchmark framework that…

Performance · Computer Science 2018-12-20 Mahesh Lakshminarasimhan , Catherine Olschanowsky

Adaptive Mixed-Criticality (AMC) is a fixed-priority preemptive scheduling algorithm for mixed-criticality hard real-time systems. It dominates many other scheduling algorithms for mixed-criticality systems, but does so at the cost of…

Operating Systems · Computer Science 2024-11-04 Bruno Mendes , Pedro F. Souto , Pedro C. Diniz

Pixel- and voxel-based representations of microstructures obtained from tomographic imaging methods is an established standard in computational materials science. The corresponding highly resolved, uniform discretitization in numerical…

Numerical Analysis · Mathematics 2019-08-27 Andreas Fischer , Bernhard Eidel

In an effort to study the applicability of adaptive mesh refinement (AMR) techniques to atmospheric models an interpolation-based spectral element shallow water model on a cubed-sphere grid is compared to a block-structured finite volume…

Computational Physics · Physics 2009-11-13 Amik St-Cyr , Christiane Jablonowski , John M. Dennis , Henry M. Tufo , Stephen J. Thomas

We present the first high order one-step ADER-WENO finite volume scheme with Adaptive Mesh Refinement (AMR) in multiple space dimensions. High order spatial accuracy is obtained through a WENO reconstruction, while a high order one-step…

Numerical Analysis · Mathematics 2015-03-11 Michael Dumbser , Olindo Zanotti , Arturo Hidalgo , Dinshaw S. Balsara

This work presents Adaptive Robot Coordination (ARC), a novel hybrid framework for multi-robot motion planning (MRMP) that employs local subproblems to resolve inter-robot conflicts. ARC creates subproblems centered around conflicts, and…

Robotics · Computer Science 2023-12-15 Irving Solis , James Motes , Mike Qin , Marco Morales , Nancy M. Amato

In recent years, there is a growing need to train machine learning models on a huge volume of data. Designing efficient distributed optimization algorithms for empirical risk minimization (ERM) has therefore become an active and challenging…

Optimization and Control · Mathematics 2019-11-19 Ching-pei Lee , Kai-Wei Chang

Active debris removal (ADR) missions have garnered significant interest as means of mitigating collision risks in space. This work proposes a convex optimization-based model predictive control (MPC) approach to provide guidance for such…

Optimization and Control · Mathematics 2023-08-21 Minduli Wijayatunga , Roberto Armellin , Harry Holt , Laura Pirovano , Claudio Bombardelli

A new concept is introduced for the adaptive finite element discretization of partial differential equations that have a sparsely representable solution. Motivated by recent work on compressed sensing, a recursive mesh refinement procedure…

Numerical Analysis · Mathematics 2009-02-26 Sadegh Jokar , Volker Mehrmann , Marc Pfetsch , Harry Yserentant

Despite the increasing prevalence of vector observations, computation of optimal experimental design for multi-response models has received limited attention. To address this problem within the framework of approximate designs, we introduce…

Computation · Statistics 2026-02-13 Pál Somogyi , Samuel Rosa , Radoslav Harman

We introduce a novel architecture and computational framework for formal, automated analysis of systems with a broad set of nonlinearities in the feedback loop, such as neural networks, vision controllers, switched systems, and even simple…

Optimization and Control · Mathematics 2018-05-02 Ivan Papusha , Ufuk Topcu , Steven Carr , Niklas Lauffer

The call for efficient computer architectures has introduced a variety of application-specific compute engines to the heterogeneous computing landscape. One particular engine, the analog mesh computer, has been well received due to its…

Numerical Analysis · Computer Science 2018-11-20 Jeff Anderson , Engin Kayraklioglu , Volker Sorger , Tarek El-Ghazawi

Many engineering systems require accurate simulations of complex physical systems. Yet, analytical solutions are only available for simple problems, necessitating numerical approximations such as the Finite Element Method (FEM). The cost…

Parallel trajectory optimization via the Alternating Direction Method of Multipliers (ADMM) has emerged as a scalable approach to long-horizon motion planning. However, existing frameworks typically decompose the problem into parallel…

Robotics · Computer Science 2026-04-27 Jiajun Yu , Guodong Liu , Li Wang , Pengxiang Zhou , Wentao Liu , Yin He , Chao Xu , Fei Gao , Yanjun Cao

Many physical problems involve spatial and temporal inhomogeneities that require a very fine discretization in order to be accurately simulated. Using an adaptive mesh, a high level of resolution is used in the appropriate areas while…

Numerical Analysis · Mathematics 2017-09-25 Florence Drui , Alexandru Fikl , Pierre Kestener , Samuel Kokh , Adam Larat , Vincent Le Chenadec , Marc Massot
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