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This paper synthesizes anytime algorithms, in the form of continuous-time dynamical systems, to solve monotone variational inequalities. We introduce three algorithms that solve this problem: the projected monotone flow, the safe monotone…

Optimization and Control · Mathematics 2025-02-18 Ahmed Allibhoy , Jorge Cortés

We present a new time-stepping algorithm for nonlinear PDEs that exhibit scale separation in time. Our scheme combines asymptotic techniques (which are inexpensive but can have insufficient accuracy) with parallel-in-time methods (which,…

Numerical Analysis · Mathematics 2014-02-24 Terry Haut , Beth Wingate

In this paper, I discuss the challenges in porting hydrodynamic codes to futuristic exascale HPC systems. In particular, we describe the computational complexities of finite difference method, pseudo-spectral method, and Fast Fourier…

Computational Physics · Physics 2019-11-25 Mahendra K. Verma

A two-phase, low-Mach-number flow solver is created and verified for variable-density liquid and gas with phase change. The interface is sharply captured using a split Volume-of-Fluid method generalized for a non-divergence-free liquid…

Fluid Dynamics · Physics 2022-06-08 Jordi Poblador-Ibanez , William A. Sirignano

For simulating incompressible flows by projection methods. it is generally accepted that the pressure-correction stage is the most time-consuming part of the flow solver. The objective of the present work is to develop a fast hybrid…

Fluid Dynamics · Physics 2023-06-05 Jiannong Fang

Approximate computing is emerging as an alternative to accurate computing due to its potential for realizing digital circuits and systems with low power dissipation, less critical path delay, and less area occupancy for an acceptable…

Hardware Architecture · Computer Science 2018-01-19 P Balasubramanian

With the commencement of the exascale computing era, we realize that the majority of the leadership supercomputers are heterogeneous and massively parallel even on a single node with multiple co-processors such as GPUs and multiple cores on…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-06 Pratik Nayak , Terry Cojean , Hartwig Anzt

The future of high-performance computing, specifically on future Exascale computers, will presumably see memory capacity and bandwidth fail to keep pace with data generated, for instance, from massively parallel partial differential…

Computational Physics · Physics 2020-01-29 Alec M. Dunton , Lluís Jofre , Gianluca Iaccarino , Alireza Doostan

High-fidelity numerical simulations of compressible flow past a rapidly rotating cylinder are used to investigate the evolution of aerodynamic loads and flow instability over a wide range of Reynolds numbers (Re = 1000 to 6000). The study…

Fluid Dynamics · Physics 2026-05-27 Sanjeev Kumar , Santosh Kumar , Aditi Sengupta

Writing high performance solvers for engineering applications is a delicate task. These codes are often developed on an application to application basis, highly optimized to solve a certain problem. Here, we present our work on developing a…

Computational Engineering, Finance, and Science · Computer Science 2018-08-14 Niclas Jansson , Rahul Bale , Keiji Onishi , Makoto Tsubokura

The modeling of atmospheric processes in the context of weather and climate simulations is an important and computationally expensive challenge. The temporal integration of the underlying PDEs requires a very large number of time steps,…

Numerical Analysis · Mathematics 2020-01-03 Francois P. Hamon , Martin Schreiber , Michael L. Minion

A scalable algorithm for solving compact banded linear systems on distributed memory architectures is presented. The proposed method factorizes the original system into two levels of memory hierarchies, and solves it using parallel cyclic…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-05 Hang Song , Kristen V. Matsuno , Jacob R. West , Akshay Subramaniam , Aditya S. Ghate , Sanjiva K. Lele

In this paper we combine the Parareal parallel-in-time method together with spatial parallelization and investigate this space-time parallel scheme by means of solving the three-dimensional incompressible Navier-Stokes equations.…

Computational Engineering, Finance, and Science · Computer Science 2017-05-18 Roberto Croce , Daniel Ruprecht , Rolf Krause

This paper continues to develop a fault tolerant extension of the sparse grid combination technique recently proposed in [B. Harding and M. Hegland, ANZIAM J., 54 (CTAC2012), pp. C394-C411]. The approach is novel for two reasons, first it…

Numerical Analysis · Mathematics 2014-04-11 Brendan Harding , Markus Hegland , Jay Larson , James Southern

This paper investigates parallelization strategies for solving power flow problems in both transmission and unbalanced, three-phase distribution systems by developing a scalable power flow solver, ExaGridPF, which is compatible with…

Computational Engineering, Finance, and Science · Computer Science 2017-11-30 Bin Wang , John Bachan , Cy Chan

This paper is concerned with a space-time adaptive numerical method for instationary porous media flows with nonlinear interaction between porosity and pressure, with focus on problems with discontinuous initial porosities. A convergent…

Numerical Analysis · Mathematics 2025-08-27 Markus Bachmayr , Simon Boisserée

This paper presents the development of an Adaptive Algebraic Multiscale Solver for Compressible flow (C-AMS) in heterogeneous porous media. Similar to the recently developed AMS for incompressible (linear) flows [Wang et al., JCP, 2014],…

Numerical Analysis · Mathematics 2017-05-17 Matei Tene , Yixuan Wang , Hadi Hajibeygi

Multiscale mixed methods based on non-overlapping domain decompositions can efficiently handle the solution of significant subsurface flow problems in very heterogeneous formations of interest to the industry, especially when implemented on…

Numerical Analysis · Mathematics 2025-02-25 Dilong Zhou , Rafael Guiraldello , Felipe Pereira

We propose an adaptive numerical solver for the study of viscoelastic 2D two-phase flows using the volume-of-fluid method. The scheme uses the robust log conformation tensor technique of Fattal & Kupferman (2004,2005} combined with the…

Fluid Dynamics · Physics 2018-07-03 J. M. Lopez-Herrera , S. Popinet , A. A. Castrejon-Pita

Parallel computing has played an important role in speeding up convex optimization methods for big data analytics and large-scale machine learning (ML). However, the scalability of these optimization methods is inhibited by the cost of…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-12-19 Aditya Devarakonda , Kimon Fountoulakis , James Demmel , Michael W. Mahoney