English
Related papers

Related papers: A Decentralized Parallelization-in-Time Approach w…

200 papers

A numerical method for the direct numerical simulation of incompressible wall turbulence in rectangular and cylindrical geometries is presented. The distinctive feature resides in its design being targeted towards an efficient…

Fluid Dynamics · Physics 2009-11-11 Paolo Luchini , Maurizio Quadrio

In view of the rapid rise of the number of cores in modern supercomputers, time-parallel methods that introduce concurrency along the temporal axis are becoming increasingly popular. For the solution of time-dependent partial differential…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-09-22 Andrea Arteaga , Daniel Ruprecht , Rolf Krause

We develop a novel parallel decomposition strategy for unweighted, undirected graphs, based on growing disjoint connected clusters from batches of centers progressively selected from yet uncovered nodes. With respect to similar previous…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-09 Matteo Ceccarello , Andrea Pietracaprina , Geppino Pucci , Eli Upfal

Solving inverse problems and achieving statistical rigour in landscape evolution models requires running many model realizations. Parallel computation is necessary to achieve this in a reasonable time. However, no previous algorithm is…

Computational Engineering, Finance, and Science · Computer Science 2019-01-23 Richard Barnes

This work proposes a data-driven method for enabling the efficient, stable time-parallel numerical solution of systems of ordinary differential equations (ODEs). The method assumes that low-dimensional bases that accurately capture the time…

Numerical Analysis · Computer Science 2017-07-14 Kevin Carlberg , Lukas Brencher , Bernard Haasdonk , Andrea Barth

In this paper, we face the problem of simulating discrete random variables with general and varying distributions in a scalable framework, where fully parallelizable operations should be preferred. The new paradigm is inspired by the…

Methodology · Statistics 2018-01-04 Giacomo Aletti

This paper studies parallelization schemes for stochastic Vector Quantization algorithms in order to obtain time speed-ups using distributed resources. We show that the most intuitive parallelization scheme does not lead to better…

Machine Learning · Statistics 2012-05-14 Matthieu Durut , Benoît Patra , Fabrice Rossi

In this work the parallel-in-time algorithm Parareal was applied to the ocean-circulation and sea-ice model FESOM2 developed by the Alfred-Wegener Institut (AWI). The climate model provides one time integration method and hence, the coarse…

Numerical Analysis · Mathematics 2022-08-17 Benedict Philippi , Thomas Slawig

The unknown parameters of simulation models often need to be calibrated using observed data. When simulation models are expensive, calibration is usually carried out with an emulator. The effectiveness of the calibration process can be…

Computation · Statistics 2024-12-03 Özge Sürer , Stefan M. Wild

We consider the initial-boundary value problem for a quasilinear time-fractional diffusion equation, and develop a fully discrete solver combining the parareal algorithm in time with a L1 finite-difference approximation of the Caputo…

Numerical Analysis · Mathematics 2025-10-14 Josefa Caballero , Łukasz Płociniczak , Kishin Sadarangani

Parallel-in-time algorithms have been successfully employed for reducing time-to-solution of a variety of partial differential equations, especially for diffusive (parabolic-type) equations. A major failing of parallel-in-time approaches to…

Numerical Analysis · Mathematics 2019-08-28 Hans De Sterck , Stephanie Friedhoff , Alexander J. M. Howse , Scott P. MacLachlan

This paper is about partitioning in parallel and distributed simulation. That means decomposing the simulation model into a numberof components and to properly allocate them on the execution units. An adaptive solution based on…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-07 Gabriele D'Angelo

The idle computers on a local area, campus area, or even wide area network represent a significant computational resource---one that is, however, also unreliable, heterogeneous, and opportunistic. This type of resource has been used…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Adriana Iamnitchi , Ian Foster

Simulations of physical phenomena are essential to the expedient design of precision components in aerospace and other high-tech industries. These phenomena are often described by mathematical models involving partial differential equations…

Computational Physics · Physics 2017-01-05 Daniel Magee , Kyle E Niemeyer

Numerical solution of partial differential equations on parallel computers using domain decomposition usually requires synchronization and communication among the processors. These operations often have a significant overhead in terms of…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-01-11 Soumyadip Ghosh , Jiacai Lu , Vijay Gupta , Gretar Tryggvason

This paper presents a scalable Bayesian technique for decentralized state estimation from multiple platforms in dynamic environments. As has long been recognized, centralized architectures impose severe scaling limitations for distributed…

Artificial Intelligence · Computer Science 2012-12-12 Matthew Rosencrantz , Geoffrey Gordon , Sebastian Thrun

This article introduces a highly parallel algorithm for molecular dynamics simulations with short-range forces on single node multi- and many-core systems. The algorithm is designed to achieve high parallel speedups for strongly…

Computational Physics · Physics 2013-11-20 R. Meyer

We consider parallel simulations for asynchronous systems employing L processing elements that are arranged on a ring. Processors communicate only among the nearest neighbors and advance their local simulated time only if it is guaranteed…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 A. Kolakowska , M. A. Novotny , G. Korniss

We propose a new computational framework that combines the recently developed time-parallel (TP) and the compound wavelet matrix (CWM) methods. The framework, termed tpCWM, offers significant computational acceleration by making…

Computational Physics · Physics 2009-09-29 George Frantziskonis , Krishna Muralidharan , Pierre Deymier , Srdjan Simunovic , Sreekanth Pannala

Prior work on Automatically Scalable Computation (ASC) suggests that it is possible to parallelize sequential computation by building a model of whole-program execution, using that model to predict future computations, and then…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-09-21 Peter Kraft , Amos Waterland , Daniel Y Fu , Anitha Gollamudi , Shai Szulanski , Margo Seltzer
‹ Prev 1 4 5 6 7 8 10 Next ›