GPU-GRAPHICS PROCESSING UNIT IEEE PAPERS AND PROJECTS-2020



A graphics processing unit (GPU) is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. GPUs are used in embedded systems, mobile phones, personal computers, workstations, and game consoles.



Quantum simulations with graphics processing units
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17 4 Graphics processing unit implementation 1.2 Graphics processing units A graphics processing unit GPU is an electronic circuit originally designed to create or assist with the creation of outputs for display devices. The term graphics processing unit wasThe energy consumption can be influenced by the operational frequency used by the hardware, and modern CPUs (central processing unit) and GPUs ( graphics processing unit ) provide DVFS (dynamic voltage and frequency scaling) to reduce the energy con- sumption by

Multiple-precision matrix-vector multiplication on graphics processing units
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units such as graphics processing units (GPUs). A modern graphics processing unit is actually an array of streaming multiprocessors (SMs), each of which contains many streaming processors. Massive parallelism of the GPU is

An OpenGL Compliant Hardware Implementation of a Graphic Processing Unit using Field Programmable Gate Array-System on Chip Technology
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and reliability of high-performance FPGA systems . However, dynamic reconfiguration introduces further challenges for verification, testing and run-time validation as discussed by Diessel . This paper presents an implementation of a Graphics Processing Unit (GPU) using

A flexible and configurable GPGPU stereo matching framework
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Accordingly, we provide the frameworks quantitative speed and accuracy analysis eval- uated on the widely used stereo dataset. In addition, this paper also addresses the parallelization strategy on an embedded graphics processing unit

Spleeter: a fast and efficient music source separation tool with pre-trained models
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Spleeter is also very fast as it can separate a mix audio file into 4 stems 100 times faster than real-time (we note, though, that the model cannot be applied in real-time as it needs buffering) on a single Graphics Processing Unit (GPU) using the pre-trained 4-stems model GPUs. The authors of proposed a way of optimizing data transfer among GPUs in the supercomputer. The central idea was to use a multi-stream application in which each stream controls a graphics processing unit . The

Empirical Performance Comparisons of GPU, CPU, FPGA, and MAESTRO
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In this paper, we measure the efficiency of the hardware components that are representative of Graphics Processing Unit (GPU), Central Processing Unit (CPU), Field Pro- grammable Gate Arrays (FPGA), and MAESTRO System on Chip (SoC) (where available) used in signal

SubjuGator 2020: Design and Implementation of a Modular, High-Performance AUV
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software innovations. This model includes a controller area network (CAN) bus, onboard general-purpose graphics processing unit (GPGPU), deep learning and point cloud processing, and other challenge-specific designs. In

Modular Microservice based GPU Utilization Manager with Gunicorn
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Article Info Received: 07-04-2020 Revised: 01-07-2020 Accepted: 10-07-2020 Published: 13-07-2020 Abstract: Graphics processing unit (GPU) is a computer programmable chip that could perform rapid mathematical operations that can be accelerated with massive parallelism

Material Point Method based Fluid Simulation Optimization on GPU with CUDA
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through parallelization. This paper discusses the implementation of fluid simulation on the Graphics Processing Unit (GPU) with Compute Unified Device Architecture (CUDA) to improve fluid simulation performance. The simulation

Hardware-Accelerated Real-Time Stream Data Processing on Android with GNU Radio
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We show that it is possible to fully benefit from available accelerators, ie, Single Instruction Mul- tiple Data (SIMD) and the Graphics Processing Unit (GPU), which provide considerable speedups and allow for efficient implementa- tions

Iterative GPU Occlusion Culling with BVH
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Usually, what are seen in the past frame can be selected as the occluders, and their depth rendering is compared against the coarse bounding proxies of po- tential occludees. Occlusion query (OQ) in Graphics Processing Unit (GPU) is a typical technique In the present work, based on the performed system modeling and analysis, we planned the target design to be developed and implemented on a single workstation platform combining field-programmable gate array (FPGA) and graphics processing unit (GPU) co-processing

Blockwise Euclidean likelihood for spatio-temporal covariance models
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We derive the asymptotic properties of the proposed estimator and we illustrate the finite sample properties of our meth- odology by means of a simulation study highlighting the computational gains of the OpenCL graphics processing unit implementation

AN OPEN-SOURCE, HARDWARE ACCELERATED INDUSTRY PROTOTYPE FOR MULTIDIMENSIONAL GLYPHS
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Our software utilizes the parallel processing power of the Graphics Processing Unit (GPU) to enable interactive exploration of thousands of multidimensional data-glyphs This is done by leveraging the parallel processing capabilities of a Graphics Processing Unit (GPU)

Novel Casestudy and Benchmarking of AlexNet for Edge AI: From CPU and GPU to FPGA
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perform. So, demand of processing power in them is significantly higher than what a standard CPU can offer. This has traditionally made CNNs more suited for running on a Graphics Processing Unit (GPU). However, GPUs

Investigation of Neutron-Irradiated Microstructure of Fe-Cr System: A GPU Accelerated Phase-field method
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J Lee, K Chang journal-home.s3.ap-northeast-2 of structural materials. Herein, we analyze the spinodal decomposition behavior under the fast neutron irradiation of the Fe-Cr system using a graphics processing unit (GPU)- accelerated phase-field method. Since high energy

A PARALLEL AVERAGED NEURAL NETWORK APPROACH FOR DETECTING SMARTPHONE PHISHES
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This paper explicitly discusses phishing attacks by their behavior and proposes a parallel defending approach to classifying messages as harm or spams using the Graphics Processing Unit (GPU) platform, which is achieved in logarithmic time of O(n log n) and also discusses tions and higher FoV. Furthermore, foveated rendering causes a reduction in bandwidth of signal transmission between Graphics Processing Unit (GPU) and display. This above work in inspired another extensive research study that

Parallelized Monte Carlo photon transport simulations for arbitrary multi-angle wide-field illumination in optoacoustic imaging
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field illumination. The performance of the MCOAI method is verified by comparison with the graphics processing unit (GPU)-accelerated MCX method in the typical cases with the pencil beam and ring source illumination. The

Exascale Computing Deployment Challenges
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In the shadows of the petascale cluster, however, the vector machine survived in the form of the GPU ( graphics processing unit ) or video card. Designed for one of the most intrinsically parallel tasks known real-time rendering, this Page 3

Analysis and concept proposal of an artificial intelligence laboratory with thoroughly selected hardware components for research and teaching
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for Deep Learning workloads , 201 researchgate.net, 10.13140/RG.2.2.22603.54563 M. Madiajagan, S. Sridhar Raj, Deep Learning and Parallel Computing Environment for Bioengineering Systems: Chapter 1 Parallel Computing, Graphics Processing Unit (GPU) and

Image Classification in Greenplum Database Using Deep Learning
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learning. We cover the Pivotal Extension Framework (PXF) to fetch and transform images from cloud object stores, and exploit graphics processing unit (GPU) cycles to run Apache MADlib deep learning methods. KEYWORDS

Automatic sound synthesis using the fly algorithm
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The previous section shows this work relying on SAE matrices to quantify the error between the input and target sound. For fast processing, we compute the SAE with the help of a Graphics Processing Unit (GPU) using the OpenGL Shading Language (GLSL) (see Figure 4)

New generation cloud computing.
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management for the scientific gateways ecosystems based on the service-oriented paradigm A multicriteria optimization model for cloud service provider selection in multicloud environments Partial migration technique for general purpose graphics processing unit tasks to

Journal of Signal Processing and Wireless Networks
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All models have a Broadcom system on a chip (SOC), which includes an ARM compatible central processing unit (CPU) and an on chip graphics processing unit .CPU speed ranges from 700MHz to 1.2 GHz for the pi 3 and on board memory range from 256 MB to 1GB RAM

A transfer-learning-based feature classification algorithm for UAV imagery in crop risk management
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By manual labeling, 287 training sets and 979 test sets are formed. AlexNet, a transfer neural network, is trained in a single central processing unit (CPU), single graphics processing unit (GPU), and double GPUs to test the complexity of the algorithmcontain- ing from dozens to thousands simpler independent cores. Specifically, we will use graphics processing unit (GPU) a manycore with thousands of simpler cores. Mul- ticore and manycore using GPU acceleration are Page 1. Computer vision algorithms acceleration using graphic processors NVIDIA

Tongue fissure visualization by using deep learning an example of the application of artificial intelligence in traditional medicine
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tongue ssures in the images or not. Results Only 6 epochs were trained in this study and no GPU ( graphics processing unit ) was used. It took less Grad-CAM: gradient-weighted class activation mapping GPU: graphics processing unit Page 7. Page 7/13 Declarations

An Optimization to YOLOv3 Detection of Small, Fast M
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The accu was found to be 95.268% on a video containi sampled at 30 frames per second (assuming the object is al in the frame) on a GeForce 1050 Graphics Processing Unit . optimization includes a method of elimination of false positiv increase accuracyThis opened several and complementary ways of research. The first one aims to take advantage of the new capabilities of hardware components. Famous examples are parallel computing, use of graphics processing unit (GPU) for fast calculations very strongly in a unified way. Hence, this research proposes a Graphics Processing Unit (GPU)-based error-prone elliptic curve cryptog- raphy with an advanced memory management mechanism. It comprises the elliptic curve

Simulations of Wall Bounded Turbulent Flows Using General Pressure Equation
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flow calculation. Keywords General pressure equation Direct numerical simulation Wall bounded flow Turbulent square duct flow Turbulent lid-driven cavity flow Graphics processing unit 1 Introduction The simulations A Digital Imaging and Communications in Medicine/ Graphics Processing Unit (DICOM/GPU) server and software pipeline was established at a metropolitan county hospital intranet to demonstrate clinical integration of ML algorithms in radiology Mechanical Sciences and Engineering Abstract A novel block-structured Cartesian mesh method is developed that is well designed for the graphics processing unit (GPU) acceleration of flow simulations. The size of the parameters for faster backpropagation learning. In order to train the model with less hardware in a short time, we used the parallel computing archi- tecture with Cuda-enabled graphics processing unit . The results indicate thatGenerally, the neural network requires graphics processing unit for faster execution of machine learning models. This review paper gives a brief overview of real-time object detection and machine learning algorithms implemented by various researchers around the world of neurons controlled by a central nervous system and DL is also composed of several number of neural networks, where each neuron is represented as a single node and the entire activity is controlled by Central Processing Unit (CPU) or Graphics Processing Unit (GPU) [4

Studies on CUDA Offloading for Real-Time Simulation and Visualization
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Professor: Narumi Tetsu The Graphics Processing Unit (GPU) is a co-processor designed to aid the Central Pro- cessing Unit (CPU) for rendering 3D graphics A new paradigm was introduced by General Purpose Computing on Graphics Processing Unit (GPGPU). At the

Any unique image biomarkers associated with COVID-19
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AUC Area under the curve BCE Binary cross-entropy CAP Community-acquired pneumonia CI Confidencial interval CNN Convolutional neural network COVID-19 Novel coronavirus CT Computed tomography FC Fully connected GPU Graphics processing unit IRB Institutional

Analysis of the performance of a hybrid CPU/GPU 1D2D
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accurate flood simulation. Due to the speed of 1D schemes, a hybrid CPU/GPU 13 model that runs the 1D main channel on CPU and accelerates the 2D floodplain with a 14 Graphics Processing Unit (GPU) is presented. Since the

Advances in Transportation Cyber-Physical System (T-CPS)
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However, research to develop edge-AI hardware is in full-swing in various parts of the globe using various forms of hardware such as Graphics Processing Unit (GPU), neuromorphic computing, custom AI hardware accelerators (like Tensor Processing Unit (TPU)), and Field

OpenACC unified programming environment for GPU and FPGA multi-hybrid acceleration
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performance/power ratio. In particular, the Graphics Processing Unit (GPU) is the most popu- lar accelerator owing to its high peak FLOPS performance and high memory bandwidth supported by HBM etc. However, the performanceIn this paper, we focus on the Xilinx Zynq UltraScale+ EG Heterogeneous MPSoC, which is composed of four different processing elements (PE): a dual-core Cortex-R a quad-core ARM Cortex-A5 a graphics processing unit (GPU) and a high end FPGA

Defect Detection on 3D Print Products and in Concrete Structures Using Image Processing and Convolution Neural Network
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Because Cloud TPUs are used to accelerate this training, the config file must relate specifically to TPU training. The training process was carried out on the following hardware: GeForce TITAN X graphics processing unit (GPU), Intel Core i7 3.2 GHz, 16 GB memory processor

Natural Reeb Graphs
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Nat- ural Reeb graphs correctly capture all branches and loops of a surface, which is mandatory to provide a correct high- level explanation. The proposed method to generate Nat- ural Reeb graphs is designed to be executed efficiently on the graphics processing unit (GPU)

CUDA Based Computation of Quadratic Image Filters
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Recent GPU ( Graphics Processing Unit ) products provides a good mean to accelerate computation of image processing applications [27] F. Bozkurt, M. Yaganoglu, and FB Günay, Effective Gaussian Blurring Process on Graphics Processing Unit with CUDA, Int. J. Mach This reduction in cases is especially advantageous for graphics processing unit (GPU) kernels, where con- ditional statements significantly degrade performance. To verify our technique, we implemented a real-time curvature-based GPU isosurface raycaster

Creating a large-scale video mapping show: project development pipeline for the Tampere Film Festival Performance March 4-8 th 2020
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TAMK Tampere University of Applied Sciences. 4K a video resolution standard of 3840 by 2160 pixels. GPU the Graphics Processing Unit of the computer. CPU the central processing unit of the computer 3D the three-dimensional computer graphics

Probabilistic 4D Flight Planning in Structured Airspaces through Parallelized Simulation on GPUs
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parallel reduction techniques. We do so by employing CUDA[20], [21], a framework for general- purpose computing on Graphics Processing Unit (GPGPU) on devices manufactured by NVIDIA. Additionally, this choice allows

Natural language processing: machine learning and modelling linguistics in the domain of sentiment analysis
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Unit TF2 Tensor Flow 2 NLTK Natural Language ToolKit RE Regular Expression ASCII American Standard Code for Interchange UTF Unicode Transformation Format GLM Generalized Linear Model LSTM Long Short-Term Memory GPU Graphics Processing Unit CPU Central

Multiple-Relaxation-Time Lattice Boltzmann Simulation of Natural Convection and Entropy Generation of Non-Newtonian Power-law Cu-water Nanofluids
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method (LBM) accelerated by Graphics Processing Unit (GPU) computing. The left and right walls of the en CUDA C, which is a programming language designed to harness the power of the Graphics Processing Unit (GPU) to massively increase computation throughputImage processing was performed on a computer running a Linux operating system and equipped with a Core i5 central processing unit (CPU, Intel Corporation, Santa Clara, CA), 8 GB RAM, and a GeForce GTX 1050 graphics processing unit (GPU, Nvidia Corporation, Santa

Toward large-scale simulation of residual stress and distortion in wire and arc additive manufacturing?
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Simulation approaches including the iterative substructure method (ISM), dynamic mesh refining method (DMRM), and graphics processing unit (GPU) based explicit finite element method (FEM) were developed for accelerating additive manufacturing stress analysis that is very

A Fast GPU Algorithm for Complex Fenestration Systems Optimization
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method for annual daylight simulation. Two strategies to compute the daylight coefficients are presented and implemented on a Graphics Processing Unit (GPU) on top of the Nvidia OptiX library. Experimental results show our

An Analysis of Use of Image Processing and Neural Networks for Window Crossing in an Autonomous Drone
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TensoFlow was created by google and is based on Keras API, to facilitate the imple- mentation of high performance algorithms, especially for large servers. It accepts the use of GPU ( Graphics Processing Unit ) beyond CPU (Central Pro-cessing Unit) only

Nucleon-Nucleon Scattering in a Wave-Packet Formalism
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In this thesis I analyse the prospect of leveraging statistical analyses of the strong nuc- lear interaction by using the wave-packet continuum discretisation (WPCD) method to efficiently compute nucleon-nucleon (NN) scattering observables on a graphics processing unit (GPU)

Performance of Augmented Reality Remote Rendering via Mobile Network
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of both implementations. The video stream uses Advanced Video Coding (AVC) and the Nvidia Video SDK1 (9.0) allows the real-time encoding on the dedicated encoding units of the graphics processing unit (GPU). This reduces the additional encoding load on the