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Parametric linear programming is a central operation for polyhedral computations, as well as in certain control applications.Here we propose a task-based scheme for parallelizing it, with quasi-linear speedup over large problems.This type…

Computational Geometry · Computer Science 2020-10-01 Camille Coti , David Monniaux , Hang Yu

Recent years have witnessed an unprecedented increase in experiments and hybrid simulations involving quantum computers. In particular, quantum annealers. Although quantum supremacy has not been established thus far, there exist a plethora…

Quantum Physics · Physics 2019-12-10 Konrad Jałowiecki , Andrzej Więckowski , Piotr Gawron , Bartłomiej Gardas

Scientific computing is increasingly incorporating the advancements in machine learning and the ability to work with large amounts of data. At the same time, machine learning models are becoming increasingly sophisticated and exhibit many…

Programming Languages · Computer Science 2019-07-19 Mike Innes , Alan Edelman , Keno Fischer , Chris Rackauckas , Elliot Saba , Viral B Shah , Will Tebbutt

The advent of asynchronous iterative scheme gives high efficiency to numerical computations. However, it is generally difficult to handle the problems of resource management and convergence detection. This paper uses JACK2, an asynchronous…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-12 Qinmeng Zou , Guillaume Gbikpi-Benissan , Frederic Magoules

The paper studies the convergence of some parallel multisplitting block iterative methods for the solution of linear systems arising in the numerical solution of Euler equations. Some sufficient conditions for convergence are proposed. As…

Numerical Analysis · Mathematics 2014-10-14 Cheng-yi Zhang , Shuanghua Luo , Zongben Xu

Solving partial differential equations with deep learning makes it possible to reduce simulation times by multiple orders of magnitude and unlock scientific methods that typically rely on large numbers of sequential simulations, such as…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-11-24 Philipp A. Witte , Russell J. Hewett , Kumar Saurabh , AmirHossein Sojoodi , Ranveer Chandra

Parallel computing has turned out to be the enabling technology to solve complex physical systems. However, the transition from shared memory, vector computers to massively parallel, distributed memory systems and, recently, to hybrid…

Astrophysics · Physics 2007-05-23 P. Hoeflich

Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. These hardware and software innovations promise to revolutionize solution times for complex problems. In this…

The objective of this research is to construct parallel implementations of the Jacobi algorithm used for the solution of linear algebraic systems, to measure their speedup with respect to the serial case and to compare each other, regarding…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-03-27 Athanasios Margaris , Stauros Souravlas , Manos Roumeliotis

ParaSail is a language specifically designed to simplify the construction of programs that make full, safe use of parallel hardware even while manipulating potentially irregular data structures. As parallel hardware has proliferated, there…

Programming Languages · Computer Science 2019-02-05 S. Tucker Taft

This paper proposes a general formulation for temporal parallelisation of dynamic programming for optimal control problems. We derive the elements and associative operators to be able to use parallel scans to solve these problems with…

Optimization and Control · Mathematics 2022-01-25 Simo Särkkä , Ángel F. García-Fernández

Analog Quantum Computers are promising tools for improving performance on applications such as modeling behavior of quantum materials, providing fast heuristic solutions to optimization problems, and simulating quantum systems. Due to the…

Quantum Physics · Physics 2024-07-31 Zachary Morrell , Marc Vuffray , Sidhant Misra , Carleton Coffrin

This paper introduces cuHALLaR, a GPU-accelerated implementation of the HALLaR method proposed in Monteiro et al. 2024 for solving large-scale semidefinite programming (SDP) problems. We demonstrate how our Julia-based implementation…

In this paper, we propose, analyze and implement efficient time parallel methods for the Cahn-Hilliard (CH) equation. It is of great importance to develop efficient numerical methods for the CH equation, given the range of applicability of…

Numerical Analysis · Mathematics 2023-04-28 Gobinda Garai , Bankim C. Mandal

We have presented some practical consequences on the molecular-dynamics simulations arising from the numerical algorithm published recently in paper Int. J. Mod. Phys. C 16, 413 (2005). The algorithm is not a finite-difference method and…

Exactly Solvable and Integrable Systems · Physics 2015-06-26 B. Brzostowski , M. R. Dudek , B. Grabiec , T. Nadzieja

We present and compare distributed parallelization strategies for the particle-in-Fourier (PIF) schemes used in kinetic plasma simulations. The different strategies are i) domain decomposition, where both the particles and Fourier modes are…

Computational Engineering, Finance, and Science · Computer Science 2026-05-12 Sriramkrishnan Muralikrishnan , Paul Fischill , Andreas Adelmann , Robert Speck

We reformulate the analysis of singularities of Feynman integrals in a way that can be practically applied to perturbative computations in the Standard Model in dimensional regularization. After highlighting issues in the textbook treatment…

High Energy Physics - Theory · Physics 2024-03-06 Claudia Fevola , Sebastian Mizera , Simon Telen

The parareal algorithm is known to allow for a significant reduction in wall clock time for accurate numerical solutions by parallelising across the time dimension. We present and test a micro-macro version of parareal, in which the fine…

Numerical Analysis · Mathematics 2019-12-20 Tony Lelièvre , Frédéric Legoll , Keith Myerscough , Giovanni Samaey

In this paper we propose a new parallel algorithm for solving global optimization (GO) multidimensional problems. The method unifies two powerful approaches for accelerating the search: parallel computations and local tuning on the behavior…

Optimization and Control · Mathematics 2011-03-31 Yaroslav D. Sergeyev

This paper is devoted to the problem of time parallelization of assimilation methods applying on unbounded time domain. In this way, we present a general procedure to couple the Luenberger observer with time parallelization algorithm. Our…

Optimization and Control · Mathematics 2022-12-06 Sebastián Riffo , Félix Kwok , Julien Salomon