We introduce algorithmic advancements designed to expedite simulations in OpenFOAM using GPUs. These developments include the following. (a) The amgx4Foam library, which connects the open-source AmgX library from NVIDIA to OpenFOAM. Matrix generation...
Synthetic Aperture Radar (SAR) satellite image ortho-rectification requires pixel-level calculations, which are time-consuming. Moreover, for SAR images with large overlapping areas, the processing time for ortho-rectification increases linearly, sig...
Extreme rainstorms are difficult to predict and often result in catchment-scale rainfall flooding, leading to substantial economic losses globally. Enhancing the numerical computational efficiency of flood models is essential for improving flood fore...
The simulation of massive multiple-input multiple-output (MIMO) channel models is becoming increasingly important for testing and validation of fifth-generation new radio (5G NR) wireless networks and beyond. However, simulation performance tends to...
Patch-based methods improve the performance of infrared small target detection, transforming the detection problem into a Low-Rank Sparse Decomposition (LRSD) problem. However, two challenges hinder the success of these methods: (1) The interference...
Field Programmable Gate Arrays (FPGAs), renowned for their reconfigurable nature, offer unmatched flexibility and cost-effectiveness in engineering experimentation. They stand as the quintessential platform for hardware acceleration and prototype val...
Phase holography is a critical optical imaging and information processing technique with applications ranging from microscopy to optical communications. However, optimizing phase hologram generation remains a significant challenge due to the non-conv...
Large-scale spatial data mining contains two performance bottlenecks: iterative high-dimensional distance computation and irregular polygon verification. This study develops a Spark-compatible CPU-GPU acceleration framework for K-Means clustering and...
The SCHISM model is widely used for ocean numerical simulations, but its computational efficiency is constrained by the substantial resources it requires. To enhance its performance, this study develops GPU–SCHISM, a GPU-accelerated parallel ve...
Fully Homomorphic Encryption (FHE) enables privacy-preserving computation but is hindered by high computational overhead, with the key-switching operation being a primary performance bottleneck. This paper introduces the first CUDA-optimized GPU impl...
The precision of numerical overland flow models is limited by their computational cost. A GPU-accelerated 2D shallow flow model is developed to overcome this challenge in this study. The model employs a Godunov-type finite volume method (FVM) to solv...
This paper presents a GPU (Graphics Processing Unit)-accelerated and LTS (Local-time-Step)-based finite volume Shallow Water Model (SWM). The model performance is compared against the other five model versions (Single CPU versions with/without LTS, M...
Microstructure simulations of continuous casting billets are vital for understanding solidification mechanisms and optimizing process parameters. However, the commonly used CA (Cellular Automaton) model is limited by grid anisotropy, which affects th...
As the scale of China’s interconnected power grid continues to expand, traditional serial computing methods are no longer sufficient for the rapid analysis and computation of electrical networks with tens of thousands of nodes due to their smal...
The LU factorization of very large sparse matrices requires a significant amount of computing resources, including memory and broadband communication. A hybrid MPI + OpenMP + CUDA algorithm named SuperLU3D can efficiently compute the LU factorization...
This paper addresses the challenge of extracting feature points and image matching in Synthetic Aperture Radar (SAR) satellite images, particularly focusing on large-scale embedding. The widely used Scale Invariant Transform (SIFT) algorithm, success...
The study of ship waves is important for ship detection, coastal erosion and wave drag. This paper proposed a highly paralleled numerical computation method for efficiently simulating three-dimensional nonlinear kelvin waves. First, a numerical model...
Large-scale atmospheric dispersion model for emergency response to nuclear accidents requires high computational efficiency and numerical reliability. A GPU-oriented Lagrangian particle dispersion model was developed within FLEXPART framework to addr...
Fully Homomorphic Encryption (FHE) provides strong data confidentiality during computation but often suffers from high latency on Central Processing Units (CPUs). This study evaluates Graphics Processing Unit (GPU) acceleration for modern FHE librari...
In this paper, we consider the finite difference approximation for a one-dimensional mathematical model of heat conduction in a three-layered solid with interfacial conditions for temperature and heat flux between the layers. The finite difference sc...
Inverse synthetic aperture radar (ISAR) imaging techniques are frequently used in target classification and recognition applications, due to its capability to produce high-resolution images for moving targets. In order to meet the demand of ISAR imag...
In this paper, a GPU-accelerated Cholesky decomposition technique and a coupled anisotropic random field are suggested for use in the modeling of diversion tunnels. Combining the advantages of GPU and CPU processing with MATLAB programming control yi...
Microwave breakdown is crucial to the transmission of high-power microwave (HPM) devices, where a growing number of studies have analyzed the complex interactions between electromagnetic waves and the evolving plasma from theoretical and analytical p...
Graphics processing unit (GPU)-based computing for climate system models is a longstanding research area of interest. The rapid radiative transfer model for general circulation models (RRTMG), a popular atmospheric radiative transfer model, can calcu...
A holographic stereogram displays reconstructed 3D images by rearranging multiple 2D viewpoint images into small holographic pixels (hogels). However, conventional CPU-based hogel generation processes these images sequentially, causing computation ti...
Discrete event system specification (DEVS) has been widely used in event-driven simulations for sensor-driven Internet of things (IoT) applications, such as monitoring the spread of fire disaster. Event-driven models for IoT sensor nodes and their co...
We propose a GPU-accelerated implementation of frequency-domain synthetic aperture focusing technique (SAFT) employing truncated regularized inverse k-space interpolation. Our implementation achieves sub-1s reconstruction time for data sizes of up to...
The importance of autonomous marine vehicles is increasing in a wide range of ocean science and engineering applications. Multi-objective optimization, where trade-offs between multiple conflicting objectives are achieved (such as minimizing expected...
Reverse time migration (RTM) exploits time-reversal symmetry and adjoint duality to focus wavefields and reconstruct subsurface reflectivity, but large surveys remain limited by the cost of forward and backward propagation. We present a Graphics Proc...
In this work, we introduce a scalable and efficient GPU-accelerated methodology for volumetric particle advection and finite-time Lyapunov exponent (FTLE) calculation, focusing on the analysis of Lagrangian coherent structures (LCS) in large-scale di...
Finite element analysis (FEA) remains the gold standard for simulating piezoelectric microactuators because it resolves coupled electromechanical fields with high fidelity. However, transient FEA becomes prohibitively expensive when thousands of actu...
A parallel implementation of wavelet-based autofocus (WBA) was presented to accelerate recursive operations and reduce computational costs. WBA evaluates digital focus indices (DFIs) using first- or second-order moments of the wavelet coefficients in...
Simulating hydraulic transients in ultra-long water (oil, gas) transmission or large-scale distribution systems are time-consuming, and exploring ways to improve the simulation efficiency is an essential research direction. The parallel implementatio...
Modeling and simulating the underwater optical imaging process can assist in optimizing the configuration of underwater optical imaging technology. Based on the Monte Carlo (MC) method, we propose an optical imaging model which is tailored for deep-s...
The traditional finite element program is executed on the CPU; however, it is challenging for the CPU to compute the ultra-large scale finite element model. In this paper, we present a set of efficient algorithms based on GPU acceleration technology...
Traditional population-based metaheuristic algorithms are effective in solving complex real-world problems but require careful strategy selection and parameter tuning. Metaphorless population-based optimization algorithms have gained importance due t...
Due to the complex topological relationship, poor data locality, and data racing problems in unstructured CFD computing, how to parallelize the finite volume method algorithms in shared memory to efficiently explore the hardware capabilities of many-...
Hyperspectral remote sensing, which can acquire data in both spectral and spatial dimensions, has been widely applied in various fields. However, the available data are limited by factors such as revisit time, imaging width, and weather conditions. T...
This study addresses the growing demand for scalable data encryption by evaluating the performance of AES (Advanced Encryption Standard) encryption and decryption using CBC (Cipher Block Chaining) and CTR (Counter Mode) modes across various CPU (Cent...
Ensuring the sustainability of ageing water-storage infrastructure is an increasingly urgent challenge under climate-driven hydrological extremes. In the Republic of Korea, approximately 18,000 small and medium-sized agricultural reservoirs—man...
GPU-accelerated quantum chemistry programs can dramatically reduce the time required for electronic structure calculations, yet most existing implementations either retrofit GPU kernels onto legacy CPU codebases or optimize individual kernels without...
Computational fluid dynamics (CFD) has become increasingly prevalent in marine and offshore engineering, with enhancing simulation efficiency emerging as a critical challenge. This study systematically evaluates the application of graphics processing...
The Biconjugate Gradient Stabilized (BiCGStab) algorithm is a widely used iterative method for solving large, sparse, and non-symmetric linear systems in scientific and engineering applications. While efficient, its performance is constrained by high...
A particle filter (PF) has been introduced for effective position estimation of moving targets for non-Gaussian and nonlinear systems. The time difference of arrival (TDOA) method using acoustic sensor array has normally been used to for estimation b...
The journal retracts the article titled “Amplitude and Phase Computable Ocean Wave Real-Time Modeling with GPU Acceleration” [...]
This paper introduces a GPU (graphics processing unit)-based fast motion synthesis algorithm for a large crowd. The main parts of the algorithms were selecting the most appropriate joint model given adaptive screen-space occupancy of each character a...
Alongside the development of smart water management and digital twin construction, hydrodynamic models have become a critical scientific tool in flood forecasting, with increasing attention and research focused on model computational efficiency. At t...
Modern computing systems increasingly rely on specialized hardware accelerators, such as Graphics Processing Units (GPUs), to meet growing computational demands. GPUs are essential for accelerating a wide range of applications, from machine learning...
Debris flow simulations are important in practical engineering. In this study, a graphics processing unit (GPU)-based numerical model that couples hydrodynamic and morphological processes was developed to simulate debris flow, transport, and morpholo...
Traditional simultaneous localization and mapping (SLAM) performs well in a static environment; however, with the abrupt increase of dynamic points in dynamic environments, the algorithm is influenced by a lot of meaningless information, leading to l...
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