Edge applications evolved into a variety of scenarios that include the acquisition and compression of immense amounts of images acquired in space remote environments such as satellites and drones, where characteristics such as power have to be proper...
In conventional spaceborne Synthetic Aperture Radar (SAR) systems, raw echo data are usually downlinked to ground stations for image formation, resulting in substantial communication burden and processing delay. Although onboard SAR imaging can allev...
This paper present contributions to the state-of-the art for graphics processing unit (GPU-based) embedded intelligence (EI) research for architectures and applications. This paper gives a comprehensive review and representative studies of the emergi...
This work evaluates the computing performance of finite element analysis in structural mechanics using modern multi-GPU systems. We can avoid the usual memory limitations when using one GPU device for many-core computing using multiple GPUs for scien...
In this survey, we provide a comprehensive classification of GPU task scheduling approaches, categorized by their underlying algorithmic techniques and evaluation metrics. We examine traditional methods—including greedy algorithms, dynamic prog...
The graphics processing unit (GPU) plays a crucial role in boosting application performance and enhancing computational tasks. Thanks to its parallel architecture and energy efficiency, the GPU has become essential in many computing scenarios. On the...
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...
With the exponential growth of big data, efficient groupby aggregation (GA) has become critical for real-time analytics across industries. GA is a key method for extracting valuable information. Current CPU-based solutions (such as large-scale parall...
Studies on the real-time detection of connected components in graph streams have been carried out. The existing connected component detection method cannot process connected components incrementally, and the performance deteriorates due to frequent d...
Background: The simulation of electrophysiological cardiac models plays an important role in facilitating the investigation of cardiac behavior under various conditions. However, these simulations often require a lot of computational resources. Metho...
To meet the high throughput requirement of communication systems, the design of high-throughput low-density parity-check (LDPC) decoders has attracted significant attention. This paper proposes a high-throughput GPU-based LDPC decoder, aiming at the...
Driven by the emergence of Graphics Processing Units (GPUs), the solution of increasingly large and intricate numerical problems has become feasible. Yet, the integration of GPUs into Computational Fluid Dynamics (CFD) codes still presents a signific...
The direct porting of the Range Migration Algorithm to GPUs for three-dimensional (3D) cylindrical synthetic aperture radar (CSAR) imaging faces difficulties in achieving real-time performance while the architecture and programming models of GPUs sig...
In this work, we examine the performance, energy efficiency, and usability when using Python for developing high-performance computing codes running on the graphics processing unit (GPU). We investigate the portability of performance and energy effic...
Polygon reconstruction is widely used across various fields. Although the current polygon reconstruction algorithms have achieved near-linear time complexity, they still fail to meet the speed demands imposed by the exponential growth in polygon numb...
Accelerators, such as GPUs (Graphics Processing Unit) that is suitable for handling highly parallel data, and FPGA (Field Programmable Gate Array) with algorithms customized architectures, are widely adopted. The motivation is that algorithms with va...
Functional magnetic resonance imaging (fMRI) is a non-invasive brain imaging technique, which has been regularly used for studying brain’s functional activities in the past few years. A very well-used measure for capturing functional associatio...
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...
Monte Carlo methods rely on sequences of random numbers to obtain solutions to many problems in science and engineering. In this work, we evaluate the performance of different pseudo-random number generators (PRNGs) of the Curand library on a number...
In this paper we show how to efficiently implement parallel discrete simulations on multicore and GPU architectures through a real example of an application: a cellular automata model of laser dynamics. We describe the techniques employed to build an...
Scientific and simulation applications are continuously gaining importance in many fields of research and industries. These applications require massive amounts of memory and substantial arithmetic computation. Therefore, general-purpose computing on...
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...
GPUs are commonly used to accelerate the execution of applications in domains such as deep learning. Deep learning applications are applied to an increasing variety of scenarios, with edge computing being one of them. However, edge devices present se...
The primary function of multimedia systems is to seamlessly transform and display content to users while maintaining the perception of acceptable quality. For images and videos, perceptual quality assessment algorithms play an important role in deter...
Graphics processing units (GPUs) are extensively used as accelerators across multiple application domains, ranging from general purpose applications to neural networks, and cryptocurrency mining. The initial utilization paradigm for GPUs was one appl...
The Adding-Doubling (AD) algorithm is a general analytical solution of the radiative transfer equation (RTE). AD offers a favorable balance between accuracy and computational efficiency, surpassing other RTE solutions, such as Monte Carlo (MC) simula...
Fractal dimension is widely used as a quantitative descriptor of structural complexity in digital images. However, its practical implementation often involves methodological and computational trade-offs. The compression-based estimator provides an in...
High-performance computing based on general-purpose graphical processing units (GPUs) is a powerful tool for reducing computational time. In a context where big data is becoming increasingly relevant, GPUs may play a crucial role. This study analyzes...
The data volume and computation task of MIMO radar is huge; a very high-speed computation is necessary for its real-time processing. In this paper, we mainly study the time division MIMO radar signal processing flow, propose an improved MIMO radar si...
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...
Current CNN-based stereo depth estimation models can barely run under real-time constraints on embedded graphic processing unit (GPU) devices. Moreover, state-of-the-art evaluations usually do not consider model optimization techniques, being that it...
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...
In quantum chemistry, constructing the Fock matrix is essential to compute Coulomb interactions among atoms and electrons and, thus, to determine electron orbitals and densities. In the fundamental framework of quantum chemistry such as the Hartree&n...
Using artificial intelligence tools to evaluate financial derivatives has become increasingly popular. PSO (particle swarm optimization) is one such tool. We present a comprehensive study of PSO for pricing American options on GPUs using OpenCL. PSO...
GPUs have been broadly used to accelerate big data analytics, scientific computing and machine intelligence. Particularly, matrix multiplication and convolution are two principal operations that use a large proportion of steps in modern data analysis...
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...
With the development of polarimetric synthetic aperture radar (PolSAR), quantitative parameter inversion has been seen great progress, especially in the field of soil parameter inversion, which has achieved good results for applications. However, Pol...
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...
Image Coregistration for InSAR processing is a time-consuming procedure that is usually processed in batch mode. With the availability of low-energy GPU accelerators, processing at the edge is now a promising perspective. Starting from the individuat...
This paper presents the Animated VISualization Tool (AVIST), an exploration-oriented data visualization tool that enables rapidly exploring and filtering large time series multidimensional datasets. AVIST highlights interactive data exploration by r...
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...
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...
Particle Swarm Optimization (PSO) is a widely used heuristic algorithm valued for its simplicity and robustness in solving diverse optimization problems. However, its high computational cost often limits large-scale applications. With the rapid devel...
In remote procedure call (RPC)-based graphic processing unit (GPU) virtualization environments, GPU tasks requested by multiple-user virtual machines (VMs) are delivered to the VM owning the GPU and are processed in a multi-process form. However, bec...
Enterprises increasingly run GPU-bound workloads such as Large Language Model (LLM) inference inside virtualized infrastructure, yet practitioners have little systematic guidance on how the choice of virtualization platform affects GPU passthrough in...
The range migration algorithm (RMA) based on Fourier transformation is widely applied in millimeter-wave (MMW) close-range imaging because of its few operations and small approximation. However, its interpolation stage is not effective due to the inv...
The process of image retrieval presents an interesting tool for different domains related to computer vision such as multimedia retrieval, pattern recognition, medical imaging, video surveillance and movements analysis. Visual characteristics of imag...
The increasing incorporation of Graphics Processing Units (GPUs) as accelerators has been one of the forefront High Performance Computing (HPC) trends and provides unprecedented performance; however, the prevalent adoption of the Single-Program Multi...
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...
Deep learning has a better output quality compared with traditional algorithms for video super-resolution (SR), but the network model needs large resources and has poor real-time performance. This paper focuses on solving the speed problem of SR; it...
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