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The aim of parallel computing is to increase an application performance by executing the application on multiple processors. OpenMP is an API that supports multi platform shared memory programming model and shared-memory programs are…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-11-12 Vibha Rajput , Alok Katiyar

Algorithmic differentiation (AD) has become increasingly capable and straightforward to use. However, AD is inefficient when applied directly to solvers, a feature of most engineering analyses. We can leverage implicit differentiation to…

Optimization and Control · Mathematics 2023-06-28 Andrew Ning , Taylor McDonnell

The current trend of multicore architectures on shared memory systems underscores the need of parallelism. While there are some programming model to express parallelism, thread programming model has become a standard to support these system…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-12-13 D. T. Hasta , A. B. Mutiara

Parallel jobs are different from sequential jobs and require a different type of process management. We present here a process management system for parallel programs such as those written using MPI. A primary goal of the system, which we…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Ralph Butler , William Gropp , Ewing Lusk

An alternating direction method of multipliers (ADMM) solver is described for optimal resource allocation problems with separable convex quadratic costs and constraints and linear coupling constraints. We describe a parallel implementation…

Optimization and Control · Mathematics 2019-07-09 Zawar Qureshi , Sebastian East , Mark Cannon

The implicit 2D3V particle-in-cell (PIC) code developed to study the interaction of ultrashort pulse lasers with matter [G. M. Petrov and J. Davis, Computer Phys. Comm. 179, 868 (2008); Phys. Plasmas 18, 073102 (2011)] has been parallelized…

Plasma Physics · Physics 2016-08-24 George M. Petrov , Jack Davis

Alternating Direction Method of Multipliers (ADMM) has recently been proposed as a potential alternative optimizer to the Stochastic Gradient Descent(SGD) for deep learning problems. This is because ADMM can solve gradient vanishing and…

Optimization and Control · Mathematics 2021-06-24 Junxiang Wang , Zheng Chai , Yue Cheng , Liang Zhao

In contrast with many other convex optimization classes, state-of-the-art semidefinite programming solvers are yet unable to efficiently solve large scale instances. This work aims to reduce this scalability gap by proposing a novel…

Optimization and Control · Mathematics 2018-12-20 Mario Souto , Joaquim D. Garcia , Alvaro Veiga

We propose fork-join and task-based hybrid implementations of four classical linear algebra iterative methods (Jacobi, Gauss-Seidel, conjugate gradient and biconjugate gradient stabilised) as well as variations of them. Algorithms are duly…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-05-24 Pedro J. Martinez-Ferrer , Tufan Arslan , Vicenç Beltran

Discretizations of infinite-dimensional variational inequalities lead to linear and nonlinear complementarity problems with many degrees of freedom. To solve these problems in a parallel computing environment, we propose two active-set…

Optimization and Control · Mathematics 2007-05-23 Steven J. Benson , Todd S. Munson

A hybrid-parallel direct-numerical-simulation method with application to turbulent Taylor-Couette flow is presented. The Navier-Stokes equations are discretized in cylindrical coordinates with the spectral Fourier-Galerkin method in the…

Computational Physics · Physics 2014-10-21 Liang Shi , Markus Rampp , Bjoern Hof , Marc Avila

Discovering atom-level phenomena requires molecular dynamics (MD) simulations with ab initio accuracy. Machine learning interatomic potentials (MLIPs) enable stable, high-accuracy MD simulations, and their models exhibit scaling-law trends…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-20 Hongyu Wang , Weijian Liu , Hongtao Xu , Yan Wang , Mingzhen Li , Weile Jia , Guangming Tan

Outlier detection is a key field of machine learning for identifying abnormal data objects. Due to the high expense of acquiring ground truth, unsupervised models are often chosen in practice. To compensate for the unstable nature of…

Machine Learning · Computer Science 2020-02-11 Yue Zhao , Xueying Ding , Jianing Yang , Haoping Bai

Message Passing Interface (MPI) plays a crucial role in distributed memory parallelization across multiple nodes. However, parallelizing MPI code manually, and specifically, performing domain decomposition, is a challenging, error-prone…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-08-31 Nadav Schneider , Tal Kadosh , Niranjan Hasabnis , Timothy Mattson , Yuval Pinter , Gal Oren

We discuss the computational bottlenecks in molecular dynamics (MD) and describe the challenges in parallelizing the computation intensive tasks. We present a hybrid algorithm using MPI (Message Passing Interface) with OpenMP threads for…

Computational Physics · Physics 2015-07-28 Anirban Pal , Abhishek Agarwala , Soumyendu Raha , Baidurya Bhattacharya

As core counts and heterogeneity rise in HPC, traditional hybrid programming models face challenges in managing distributed GPU memory and ensuring portability. This paper presents DiOMP, a distributed OpenMP framework that unifies OpenMP…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-20 Baodi Shan , Mauricio Araya-Polo , Barbara Chapman

The alternating direction method of multipliers (ADMM) is widely used for solving large-scale semidefinite programs (SDPs), yet on instances with multiple primal-dual optimal solution pairs, it often enters prolonged slow-convergence…

Optimization and Control · Mathematics 2026-03-04 Shucheng Kang , Heng Yang

In this paper, we perform a comparison of two approaches for the parallelization of an existing, free software, FullSWOF 2D (http://www. univ-orleans.fr/mapmo/soft/FullSWOF/ that solves shallow water equations for applications in hydrology)…

The identification of primal variables and adjoint variables is usually done via indices in operator overloading algorithmic differentiation tools. One approach is a linear management scheme, which is easy to implement and supports memory…

Mathematical Software · Computer Science 2023-08-16 Max Sagebaum , Johannes Blühdorn , Nicolas R. Gauger

Realistic reservoir simulation is known to be prohibitively expensive in terms of computation time when increasing the accuracy of the simulation or by enlarging the model grid size. One method to address this issue is to parallelize the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-14 Tong Dong Qiu , Andreas Thune , Vinicius Oliveira Martins , Markus Blatt , Alf Birger Rustad , Razvan Nane