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We present a GPU implementation of LAMMPS, a widely-used parallel molecular dynamics (MD) software package, and show 5x to 13x single node speedups versus the CPU-only version of LAMMPS. This new CUDA package for LAMMPS also enables…

Materials Science · Physics 2011-03-08 Christian R. Trott , Lars Winterfeld , Paul S. Crozier

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

Particle-in-Cell (PIC) Monte Carlo (MC) simulations are central to plasma physics but face increasing challenges on heterogeneous HPC systems due to excessive data movement, synchronization overheads, and inefficient utilization of multiple…

Lattice Boltzmann method models offer a novel framework for the simulation of high Reynolds number dilute gravity currents. The numerical algorithm is well suited to acceleration via implementation on massively parallel computer…

In this work, we present accLB, a high-performance Fortran-based lattice Boltzmann (LB) solver tailored to multiphase turbulent flows on multi-GPU architectures. The code couples a conservative phase-field formulation of the Allen-Cahn…

The lattice Boltzmann method exhibits excellent scalability on current supercomputing systems and has thus increasingly become an alternative method for large-scale non-stationary flow simulations, reaching up to a trillion grid nodes.…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-05-11 Florian Schornbaum , Ulrich Rüde

Current supercomputers often have a heterogeneous architecture using both CPUs and GPUs. At the same time, numerical simulation tasks frequently involve multiphysics scenarios whose components run on different hardware due to multiple…

Computational Engineering, Finance, and Science · Computer Science 2024-12-10 Samuel Kemmler , Christoph Rettinger , Ulrich Rüde , Pablo Cuéllar , Harald Köstler

The Lattice Boltzmann method (LBM) for solving fluid flow is naturally well suited to an efficient implementation for massively parallel computing, due to the prevalence of local operations in the algorithm. This paper presents and analyses…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-01-04 Mark Mawson , Alistair Revell

We show that efficient simulations of the Kardar-Parisi-Zhang interface growth in 2 + 1 dimensions and of the 3-dimensional Kinetic Monte Carlo of thermally activated diffusion can be realized both on GPUs and modern CPUs. In this article…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-01-21 Jeffrey Kelling , Géza Ódor , Máté Ferenc Nagy , Henrik Schulz , Karl-Heinz Heinig

Matrix multiplication is a foundational operation in scientific computing and machine learning, yet its computational complexity makes it a significant bottleneck for large-scale applications. The shift to parallel architectures, primarily…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-30 Mufakir Qamar Ansari , Mudabir Qamar Ansari

We present the results of an effort to accelerate a Rational Hybrid Monte Carlo (RHMC) program for lattice quantum chromodynamics (QCD) simulation for 2 flavours of staggered fermions on multiple Kepler K20X GPUs distributed on different…

High Energy Physics - Lattice · Physics 2018-05-08 Sourendu Gupta , Pushan Majumdar

Lattice Boltzmann method (LBM) is a promising approach to solving Computational Fluid Dynamics (CFD) problems, however, its nature of memory-boundness limits nearly all LBM algorithms' performance on modern computer architectures. This…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-08-11 Yuankun Fu , Fengguang Song

To accelerate the solution of large eigenvalue problems arising from many-body calculations in nuclear physics on distributed-memory parallel systems equipped with general-purpose Graphic Processing Units (GPUs), we modified a previously…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-02 Pieter Maris , Chao Yang , Dossay Oryspayev , Brandon Cook

We present LBcuda, a GPU accelerated version of LBsoft, our open-source MPI-based software for the simulation of multi-component colloidal flows. We describe the design principles, the optimization and the resulting performance as compared…

We present an efficient open-source implementation of the multiparticle collision dynamics (MPCD) algorithm that scales to run on hundreds of graphics processing units (GPUs). We especially focus on optimizations for modern GPU…

Soft Condensed Matter · Physics 2018-08-01 Michael P. Howard , Athanassios Z. Panagiotopoulos , Arash Nikoubashman

Molecular dynamics facilitates the simulation of a complex system to be analyzed at molecular and atomic levels. Simulations can last a long period of time, even months. Due to this cause the graphics processing units (GPUs) and multi-core…

Computational Physics · Physics 2021-02-02 Iuliana Marin , Nicolae Goga , Maria Goga

This paper presents a comprehensive comparison of three dominant parallel programming models in High Performance Computing (HPC): Message Passing Interface (MPI), Open Multi-Processing (OpenMP), and Compute Unified Device Architecture…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-06-19 Nizar ALHafez , Ahmad Kurdi

Multiphase compressible flows are often characterized by a broad range of space and time scales. Thus entailing large grids and small time steps, simulations of these flows on CPU-based clusters can thus take several wall-clock days.…

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

The trend towards highly parallel multi-processing is ubiquitous in all modern computer architectures, ranging from handheld devices to large-scale HPC systems; yet many applications are struggling to fully utilise the multiple levels of…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-07-19 Michael Lange , Gerard Gorman , Michele Weiland , Lawrence Mitchell , Xiaohu Guo , James Southern