Assessing national exposure to and impact of glacial lake outburst floods considering uncertainty under data sparsity by H. Chen, Q. Liang, J. Zhao, S. B. Maharjan

“…A significant number of GLOF scenarios is subsequently generated based on this estimated plausible range of peak discharges. A graphics processing unit (GPU)-based hydrodynamic model is then adopted to simulate the resulting flood hydrodynamics in different GLOF scenarios. …”
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Implementation of Special Function Unit for Vertex Shader Processor Using Hybrid Number System by Avni Agarwal, P. Harsha, Swati Vasishta, S. Sivanantham

“…The OpenGL ES Standard documents the requirements of graphic processing unit. A prime feature of this standard is a special function unit (SFU), which performs all the required mathematical computations on the vertex information corresponding to the image. …”
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Combined Acceleration Methods for Solid Rocket Motor Grain Burnback Simulation Based on the Level Set Method by Ran Wei, Futing Bao, Yang Liu, Weihua Hui

“…Relevant methods were improved by making use of unique characteristics of the grains, and graphical processing unit (GPU) parallelization is utilized to perform the computationally intensive operations. …”
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Fast Endmember Extraction for Massive Hyperspectral Sensor Data on GPUs by Zebin Wu, Shun Ye, Jie Wei, Zhihui Wei, Le Sun, Jianjun Liu

“…A method of parallel optimization for the well-known N-FINDR algorithm on graphics processing units (NFINDR-GPU) is proposed to realize fast endmember extraction for massive hyperspectral sensor data in this paper. …”
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Accelerating Smith-Waterman Alignment for Protein Database Search Using Frequency Distance Filtration Scheme Based on CPU-GPU Collaborative System by Yu Liu, Yang Hong, Chun-Yuan Lin, Che-Lun Hung

“…Recently, several works have adopted the graphic card with Graphic Processing Units (GPUs) and their associated CUDA model to enhance the performance of SW computations. …”
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The Potential for a GPU-Like Overlay Architecture for FPGAs by Jeffrey Kingyens, J. Gregory Steffan

“…We propose a soft processor programming model and architecture inspired by graphics processing units (GPUs) that are well-matched to the strengths of FPGAs, namely, highly parallel and pipelinable computation. …”
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Simulating Growth Kinetics in a Data-Parallel 3D Lattice Photobioreactor by A. V. Husselmann, K. A. Hawick

“…Our parallel implementation on graphical processing units of the simulation provides key advantages, which we also briefly discuss. …”
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TESLA GPUs versus MPI with OpenMP for the Forward Modeling of Gravity and Gravity Gradient of Large Prisms Ensemble by Carlos Couder-Castañeda, Carlos Ortiz-Alemán, Mauricio Gabriel Orozco-del-Castillo, Mauricio Nava-Flores

“…An implementation with the CUDA technology in a single and in several graphics processing units (GPUs) is presented for the calculation of the forward modeling of gravitational fields from a tridimensional volumetric ensemble composed by unitary prisms of constant density. …”
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Fast Random Permutation Tests Enable Objective Evaluation of Methods for Single-Subject fMRI Analysis by Anders Eklund, Mats Andersson, Hans Knutsson

“…In this work, it is shown how the computational power of cost-efficient graphics processing units (GPUs) can be used to speed up random permutation tests. …”
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Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU by Jinwei Wang, Xirong Ma, Yuanping Zhu, Jizhou Sun

“…The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. …”
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Efficient Probabilistic and Geometric Anatomical Mapping Using Particle Mesh Approximation on GPUs by Linh Ha, Marcel Prastawa, Guido Gerig, John H. Gilmore, Cláudio T. Silva, Sarang Joshi

“…In this paper, we present a solution based on two key ideas: a new registration method that generates a mapping between anatomies represented as a multicompartment model of class posterior images and geometries and an implementation of the algorithm using particle mesh approximation on Graphical Processing Units (GPUs) to fulfill the computational requirements. …”
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Novel Dynamic Partial Reconfiguration Implementation of K-Means Clustering on FPGAs: Comparative Results with GPPs and GPUs by Hanaa M. Hussain, Khaled Benkrid, Ali Ebrahim, Ahmet T. Erdogan, Huseyin Seker

“…In this work, a parameterized implementation of the K-means clustering algorithm in Field Programmable Gate Array (FPGA) is presented and compared with previous FPGA implementation as well as recent implementations on Graphics Processing Units (GPUs) and GPPs. The proposed FPGA has higher performance in terms of speedup over previous GPP and GPU implementations (two orders and one order of magnitude, resp.). …”
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Fourier or Wavelet bases as counterpart self-attention in spikformer for efficient visual classification by Qingyu Wang, Qingyu Wang, Duzhen Zhang, Xinyuan Cai, Tielin Zhang, Bo Xu

“…The FWformer can achieve comparable or even higher accuracies (0.4%–1.5%), higher running speed (9%–51% for training and 19%–70% for inference), reduced theoretical energy consumption (20%–25%), and reduced graphic processing unit (GPU) memory usage (4%–26%), compared to the standard spikformer. …”
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FPGA Implementation of Real-Time Compressive Sensing with Partial Fourier Dictionary by Yinghui Quan, Yachao Li, Xiaoxiao Gao, Mengdao Xing

“…Traditionally, CS can be implemented using a high-level computer language in a personal computer (PC) or multicore platforms, such as graphics processing units (GPUs) and Digital Signal Processors (DSPs). …”
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High Performance 3D PET Reconstruction Using Spherical Basis Functions on a Polar Grid by J. Cabello, J. E. Gillam, M. Rafecas

“…In this work, we have implemented the reconstruction algorithm using Graphical Processing Unit (GPU) technology for speed and a precomputed Monte-Carlo-calculated SRM for accuracy. …”
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From data to diagnosis: leveraging deep learning in IoT-based healthcare by Miracle A. Atianashie, Chukwuma Chinaza Adaobi

“…This article also discusses the pivotal role of Graphics Processing Units (GPUs)-accelerated computing and the expertise of medical professionals in refining deep learning models for clinical applications. …”
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Bringing Intelligence to SAR Missions: A Comprehensive Dataset and Evaluation of YOLO for Human Detection in TIR Images by Mostafa Rizk, Israa Bayad

“…Also, the trained models are deployed on graphical processing units. The tiniest trained model, YOLOv8n, achieves an inference rate of 273.6 frames per second (FPS) while the largest model, YOLOv8, achieves an inference rate of 100.29 FPS. …”
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High Performance Frequent Subgraph Mining on Transaction Datasets: A Survey and Performance Comparison by Bismita S. Jena, Cynthia Khan, Rajshekhar Sunderraman

“…Many authors have tried to achieve better performance using Graphic Processing Units (GPUs) which has multi-fold improvement over in-memory while dealing with large datasets. …”
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A Block-Based and Highly Parallel CNN Accelerator for Seed Sorting by Xiaoting Sang, Zhenghui Hu, Huanyu Li, Chunlei Li, Zhoufeng Liu

“…For embedded devices, the high-power consumption of graphics processing units (GPUs) is generally prohibitive, and the field programmable gate array (FPGA) becomes a solution to perform high-speed inference by providing a customized accelerator for a particular user. …”
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Accelerated pseudo-transient method for elastic, viscoelastic, and coupled hydromechanical problems with applications by Y. Alkhimenkov, Y. Y. Podladchikov

“…Recent advancements have demonstrated the APT method's computational efficiency, particularly when applied to quasi-static nonlinear problems using Graphical Processing Units (GPUs). This study presents a comprehensive analysis of the APT method, focusing on its application to quasi-static elastic, viscoelastic, and coupled hydromechanical problems, specifically those governed by quasi-static Biot poroelastic equations, across 1D, 2D, and 3D domains. …”
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