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We present the NVIDIA cuQuantum SDK, a state-of-the-art library of composable primitives for GPU-accelerated quantum circuit simulations. As the size of quantum devices continues to increase, making their classical simulation progressively…

Simulations based on particle methods, such as Smoothed Particle Hydrodynamics (SPH), are known to be computationally demanding. While such methods have for long been executed in parallel on multi-core CPUs, in recent years the increasing…

Computational Engineering, Finance, and Science · Computer Science 2026-03-18 Xiangyu Hu , Alberto Guarnieri

Simulating large-scale microswimmer dynamics in viscous fluid poses significant challenges due to the coupled high spatial and temporal complexity. Conventional high-performance computing (HPC) methods often address these two dimensions in…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-15 Ruixiang Huang , Weifan Liu

In this paper we present a tool that performs CUDA accelerated LTL Model Checking. The tool exploits parallel algorithm MAP adjusted to the NVIDIA CUDA architecture in order to efficiently detect the presence of accepting cycles in a…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-12-15 Jiří Barnat , Luboš Brim , Milan Češka

GROMACS is a widely used package for biomolecular simulation, and over the last two decades it has evolved from small-scale efficiency to advanced heterogeneous acceleration and multi-level parallelism targeting some of the largest…

Computational Engineering, Finance, and Science · Computer Science 2015-06-03 Páll Szilárd , Mark James Abraham , Carsten Kutzner , Berk Hess , Erik Lindahl

Large-scale HPC simulations of plasma dynamics in fusion devices require efficient parallel I/O to avoid slowing down the simulation and to enable the post-processing of critical information. Such complex simulations lacking parallel I/O…

Ab initio molecular dynamics (AIMD) based on density functional theory (DFT) has become a workhorse for studying the structure, dynamics, and reactions in condensed matter systems. Currently, AIMD simulations are primarily carried out at…

Chemical Physics · Physics 2025-06-10 Ritama Kar , Sagarmoy Mandal , Vaishali Thakkur , Bernd Meyer , Nisanth N. Nair

Advances in high-throughput simulation (HTS) software enabled computational databases and big data to become common resources in materials science. However, while computational power is increasingly larger, software packages orchestrating…

Computational Physics · Physics 2023-12-22 Daniel Schwalbe-Koda

In this article we introduce a novel coupled algorithm for massively parallel direct numerical simulations of electrophoresis in microfluidic flows. This multiphysics algorithm employs an Eulerian description of fluid and ions, combined…

Computational Engineering, Finance, and Science · Computer Science 2018-05-29 Dominik Bartuschat , Ulrich Rüde

We present a hybrid continuum-atomistic scheme which combines molecular dynamics (MD) simulations with on-the-fly machine learning techniques for the accurate and efficient prediction of multiscale fluidic systems. By using a Gaussian…

Fluid Dynamics · Physics 2016-03-16 David Stephenson , James R Kermode , Duncan A Lockerby

We present a novel convex formulation that weakly couples the Material Point Method (MPM) with rigid body dynamics through frictional contact, optimized for efficient GPU parallelization. Our approach features an asynchronous time-splitting…

Robotics · Computer Science 2025-07-08 Chang Yu , Wenxin Du , Zeshun Zong , Alejandro Castro , Chenfanfu Jiang , Xuchen Han

Numerical modeling of the intensity and evolution of flood events are affected by multiple sources of uncertainty such as precipitation and land surface conditions. To quantify and curb these uncertainties, an ensemble-based simulation and…

Geophysics · Physics 2023-02-17 Junyu Wei , Xiangyu Luo , Weihong Liao , Xiaohui Lei , Jianshi Zhao , Haocheng Huang , Hao Wang

This paper introduces the Sheffield Magnetohydrodynamics Algorithm Using GPUs (SMAUG+), an advanced numerical code for solving magnetohydrodynamic (MHD) problems, using multi-GPU systems. Multi-GPU systems facilitate the development of…

Computational Physics · Physics 2017-12-01 N. Gyenge , M. K. Griffiths , R. Erdélyi

Recent developments in many-body potential energy representation via deep learning have brought new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Here we describe DeePMD-kit, a package written in…

Computational Physics · Physics 2018-05-23 Han Wang , Linfeng Zhang , Jiequn Han , Weinan E

Training multi-billion to trillion-parameter language models efficiently on GPU clusters requires leveraging multiple parallelism strategies. We present Galvatron, a novel open-source framework (dubbed 'Optimus-Megatron' in the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-08 Esmail Gumaan

Computational chemistry allows researchers to experiment in sillico: by running a computer simulations of a biological or chemical processes of interest. Molecular dynamics with molecular mechanics model of interactions simulates N-body…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-03-03 Jana Pazúriková

The FastGeodis package provides an efficient implementation for computing Geodesic and Euclidean distance transforms (or a mixture of both), targeting efficient utilisation of CPU and GPU hardware. In particular, it implements the…

Computer Vision and Pattern Recognition · Computer Science 2022-11-28 Muhammad Asad , Reuben Dorent , Tom Vercauteren

We leverage highly successful prior projects sponsored by multiple NSF grants and gifts from industry: the BLAS-like Library Instantiation Software (BLIS) and the libflame efforts to lay the foundation for a new flexible framework by…

Mathematical Software · Computer Science 2026-04-09 Devin A. Matthews , Tze Meng Low , Margaret E. Myers , Devangi N. Parikh , Robert A. van de Geijn

We present the numerical methods and GPU-accelerated implementation underlying a Total Lagrangian finite element framework for finite-deformation flexible multibody dynamics, introduced in the companion paper [1]. The framework supports…

Computational Engineering, Finance, and Science · Computer Science 2026-05-04 Zhenhao Zhou , Ruochun Zhang , Ganesh Arivoli , Dan Negrut

The deformability of soft condensed matter often requires modelling of hydrodynamical aspects to gain quantitative understanding. This, however, requires specialised methods that can resolve the multiscale nature of soft matter systems. We…

Soft Condensed Matter · Physics 2017-12-22 Ulf D. Schiller , Timm Krüger , Oliver Henrich