Encrypting pictures quickly and securely is required to secure image transmission over the internet and local networks. This may be accomplished by employing a chaotic scheme with ideal properties such as unpredictability and non-periodicity. However...
In this paper, the weighted tardiness single-machine scheduling problem is considered. To solve it an approximate (tabu search) algorithm, which works by improving the current solution by searching the neighborhood, is used. Methods of eliminating ba...
This paper explores the application of parallel algorithms and high-performance computing (HPC) in the processing and forecasting of large-scale water demand data. Building upon prior work, which identified the need for more robust and scalable forec...
Parametric decay instability (PDI) generated in milliseconds is an important physical phenomenon in ionospheric heating. Usually, numerical simulations are used to study PDI mechanisms. They can intuitively investigate the generation and development...
Land-surface temperature (LST) is a very important parameter in the geosciences. Conventional LST retrieval is based on large-scale remote-sensing (RS) images where split-window algorithms are usually employed via a traditional stand-alone method. Wh...
In this paper, we propose a novel family of semi-implicit hybrid finite volume/finite element schemes for computational fluid dynamics (CFD), in particular for the approximate solution of the incompressible and compressible Navier-Stokes equations, a...
As a popular linear filter, the mean filter is widely used in different applications as a basic tool for image enhancement. Its main purpose is to reduce the noise in an image and thus to prepare the picture for other image-processing operations depe...
The problem of analyzing a big amount of user data to determine their preferences and, based on these data, to provide recommendations on new products is important. Depending on the correctness and timeliness of the recommendations, significant profi...
The paper proposes a parallel algorithm for solving large overdetermined systems of linear algebraic equations with a dense matrix. This algorithm is based on the use of a modification of the conjugate gradient method, which is able to take into acco...
Maintaining a high rate of productivity, in terms of completed jobs per unit of time, in High-Performance Computing (HPC) facilities is a cornerstone in the next generation of exascale supercomputers. Process malleability is presented as a straightfo...
We present a discretization method of the Navier–Stokes Cahn–Hilliard equations which offers an impressing simplicity, making it easy to implement a scalable parallel code from scratch. The method is based on a special pressure projection...
We present a parallel algorithm for computing the covering radius of a linear
Numerical estimation of Lyapunov exponents in non-linear dynamical systems results in a very high computational cost. This is due to the large-scale computational cost of several Runge–Kutta problems that need to be calculated. In this work we introd...
We propose a method to parallelize a 3D incompressible Navier–Stokes solver that uses a fully implicit fractional-step method to simulate sediment transport in prismatic channels. The governing equations are transformed into generalized curvili...
The Message Passing Interface (MPI) technique is an old solution and an improvement on the Monte Carlo N-Particle Transport (MCNP) method’s enormous computational time, which has not been evaluated based on PHITS code—a recently developed...
As high-performance computing (HPC) platforms continue to scale up, communication costs have become a critical bottleneck affecting overall application performance. An effective strategy to overcome this limitation is to overlap communication with co...
In this paper, the deterministic ensemble Kalman filter is implemented with a parallel technique of the message passing interface based on our in-house black oil simulator. The implementation is separated into two cases: (1) the ensemble size is grea...
Large-scale inverse problems that require high-performance computing arise in various fields, including regional air quality studies. The paper focuses on parallel solutions of an emission source identification problem for a 2D advection–diffus...
As the development of high-performance computing (HPC) is growing, exascale computing is on the horizon. Therefore, it is imperative to develop parallel systems, such as graphics processing units (GPUs) and programming models, that can effectively ut...
The importance of high-performance computing is increasing, and Exascale systems will be feasible in a few years. These systems can be achieved by enhancing the hardware’s ability as well as the parallelism in the application by integrating mor...
High-performance computing (HPC) and its supercomputers are essential for solving the most difficult issues in many scientific computing domains. The proliferation of computational resources utilized by HPC systems has resulted in an increase in the...
In this paper we introduce an approach to accelerate many-scenario (i.e., hundreds to thousands) power system simulations which is based on a highly scalable and flexible open-source software environment. In this approach, the parallel execution of s...
The matrix information geometric signal detection (MIGSD) method has achieved satisfactory performance in many contexts of signal processing. However, this method involves many matrix exponential, logarithmic, and inverse operations, which result in...
Motion-compensated image reconstruction enables new clinical applications of Magnetic Resonance Imaging (MRI), but it relies on computationally intensive algorithms. This study focuses on the Generalized Reconstruction by Inversion of Coupled Systems...
As a convolutional operation in a space domain, Gaussian filtering involves a large number of computational operations, a number that increases when the sizes of images and the kernel size also increase. Thus, finding methods to accelerate such compu...
Cell signaling and gene transcription occur at faster time scales compared to cellular death, division, and evolution. Bridging these multiscale events in a model is computationally challenging. We introduce a framework for the systematic development...
Parameter uncertainty analysis is one of the hot issues in hydrology studies, and the Generalized Likelihood Uncertainty Estimation (GLUE) is one of the most widely used methods. However, the scale of the existing research is relatively small, which...
The finite-difference time-domain (FDTD) method is a versatile electromagnetic simulation technique, widely used for solving various broadband problems. However, when dealing with complex structures and large dimensions, especially when applying perf...
The High Intensity Muon Beams (HIMB) project at the Paul Scherrer Institute (PSI) will deliver muon beams with unprecedented intensities of up to
The growing adoption of supercomputers across various scientific disciplines, particularly by researchers without a background in computer science, has intensified the demand for parallel applications. These applications are typically developed using...
Process-based numerical models developed to perform hydraulic/hydrologic/water quality analysis of watersheds and rivers have become highly sophisticated, with a corresponding increase in their computation time. However, for incidents such as water p...
Direct methods based on iterative projection algorithms can determine protein crystal structures directly from X-ray diffraction data without prior structural information. However, traditional direct methods often converge to local minima during elec...
Multiphase flow solvers are widely-used applications in OpenFOAM, whose scalability suffers from the costly communication overhead. Therefore, we establish communication-optimized multiphase flow solvers in OpenFOAM. In this paper, we first deliver a...
Microgrids have drawn attention due to their helpfulness in the development of renewable energy. It is necessary to make an optimal power dispatch scheme for each micro-source in a microgrid in order to make the best use of fluctuating and unpredicta...
Remote sensing (RS) image segmentation is an essential step in geographic object-based image analysis (GEOBIA) to ultimately derive “meaningful objects”. While many segmentation methods exist, most of them are not efficient for large data sets. Thus,...
Global Navigation Satellite System (GNSS) ultra-rapid orbit is critical for geoscience and real-time engineering applications. To improve the computational efficiency and the accuracy of predicted orbit, a parallel approach for multi-GNSS ultra-rapid...
The application of single chain mean-field theory (SCMFT) on semiflexible chain brushes is reviewed. The worm-like chain (WLC) model is the best mode of semiflexible chain that can continuously recover to the rigid rod model and Gaussian chain (GC) m...
This paper presents a parallel implementation of a non-local transform-domain filter (BM4D). The effectiveness of the parallel implementation is demonstrated by denoising image series from computed tomography (CT) and magnetic resonance imaging (MRI)...
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-...
The Computation and Modeling Engineering Laboratory (CaMEL), an implicit solver-based storm surge model, has been extended for use on high performance computing platforms. An MPI (Message Passing Interface) based parallel version of CaMEL has been de...
The possibility to create a flood wave in a river network depends on the geometric properties of the river basin. Among the models that try to forecast the Instantaneous Unit Hydrograph (IUH) of rainfall precipitation, the so-called Multifractal Inst...
Today, various applications in different domains increasingly rely on high-performance computing (HPC) to accomplish computations swiftly. Integrating one or more programming models alongside the used programming language enhances system parallelism,...
The International Work Conference on Bioinspired Intelligence (IWOBI) is an annual event that comprises both an international peer-reviewed scientific conference and a set of workshops and other activities in order to foster the research abilities an...
This study aims to solve the problem that the traditional method of measuring the poverty level in rural and urban areas of China from a purely monetary perspective can’t comprehensively analyze and reflect the poverty. In this study, a multidi...
With the development of mature Computational Fluid Dynamics (CFD) tools for fluids (air and liquid) and Finite Element Methods (FEM) for solids and structures, many approaches have been proposed to tackle the so-called Fluid–Structure Interaction or...