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检索条件"任意字段=5th International Conference on Algorithms and Architectures for Parallel Processing"

共 3239 条记录，以下是201-210 订阅

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Development and Application of a Monte Carlo Tree Search Algorithm for Simulating Da Vinci Code Game Strategies

Development and Application of a Monte Carlo Tree Search Alg...

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Intelligent Computing and Human-Computer Interaction (ICHCI), international conference on

作者： Ye Zhang Mengran Zhu Kailin Gui Jiayue Yu Yong Hao Haozhan Sun University of Pittsburgh Pittsburgh PA USA Miami University Oxford OH USA University of Washington Seattle WA USA Warner Bro. Discovery Culver City CA USA Columbia University New York NY USA Duke University Durham NC USA

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

In this study, we explore the efficiency of the Monte Carlo Tree Search (MCTS), a prominent decision-making algorithm renowned for its effectiveness in complex decision environments, contingent upon the volume of simulations conducted. Notwithstanding its broad applicability, the algorithm's performance can be adversely impacted in certain scenarios, particularly within the domain of game strategy development. this research posits that the inherent branch divergence within the Da Vinci Code board game significantly impedes parallelism when executed on Graphics processing Units (GPUs). To investigate this hypothesis, we implemented and meticulously evaluated two variants of the MCTS algorithm, specifically designed to assess the impact of branch divergence on computational performance. Our comparative analysis reveals a linear improvement in performance with the CPU-based implementation, in stark contrast to the GPU implementation, which exhibits a non-linear enhancement pattern and discernible performance troughs. these findings contribute to a deeper understanding of the MCTS algorithm's behavior in divergent branch scenarios, highlighting critical considerations for optimizing game strategy algorithms on parallel computing architectures.

关键词： Solid modeling Monte Carlo methods Codes Computational modeling Instruction sets Graphics processing units Games parallel processing Time measurement Robots

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Classification of Human Indoor Activities with Resource Constrained Network architectures on Audio Data 5

Classification of Human Indoor Activities with Resource Cons...

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IEEE 5th international conference and Workshop Obuda on Electrical and Power Engineering (IEEE CANDO-EPE)

作者： Anand, Joseph Koch, Marcel Schlenke, Fabian Kohlmorgen, Fabian Wohrle, Hendrik Dortmund Univ Appl Sci & Arts Dept Informat Technol Dortmund Germany

ISBN: (纸本)9798350346190

Many functions and processes in Smart Homes can be improved by incorporating knowledge about the activities of the inhabitants. the inhabitant activities can be recognized by classifying typical sounds related to the activities using audio classification methods. In this paper, we present and approach for the classification of activity-based audio data, taking into account that in many cases the data processing has to be deployed on a resource-constrained device. An indoor dataset is created by recording 11 distinct human actions that are typically perfomed in a living room and kitchen setup. A Convolutional Neural Network (CNN) is used for classification that achieves an accuracy of up to 98%. In addition, network optimization methods like depthwise separable convolutions, pruning, channel scaling and quantization is used to reduce the memory footprint and computational requirements to obtain an optimized network with 93% fewer Million Floating point Operations (MFLOPs) and less than 2% drop in accuracy is achieved for use in resource-constrained devices.

关键词： Audio Classification IoT Machine Learning Human Activity Recognition Edge Computing

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LSSM-SpMM: A Long-Row Splitting and Short-Row Merging Approach for parallel SpMM on PEZY-SC3s 24th

LSSM-SpMM: A Long-Row Splitting and Short-Row Merging Appro...

引用

24th international conference on algorithms and architectures for parallel processing, ICA3PP 2024

作者： Cao, Ligang Wang, Qinglin Yang, Shun Xia, Rui Guo, Weihao Liu, Jie Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789819615506

Sparse Matrix-Dense Matrix Multiplication (SpMM) is a crucial kernel used in a wide range of fields including machine learning and linear algebra solvers. thus, enhancing the performance of SpMM is essential. the uneven distribution of non-zeros in sparse matrices and the tight data dependency between sparse and dense matrices make efficiently running SpMM on various hardware platforms challenging. To address these issues, optimisations are tailored according to the characteristics of the different hardware platforms. In this study, we propose a Long Row Split and Short Row Merge (LSSM) approach on the new MIMD computing platform PEZY-SC3s, utilising the standard Compressed Sparse Row (CSR) format to optimise SpMM. Specifically, LSSM divides the rows of the sparse matrix into short rows (rows with a number of non-zeros less than blockSize) and long rows (rows with a number of non-zeros greater than blockSize), applying splitting to the long rows and merging to the short rows to optimize their computations separately. Additionally, based on the hardware features of PEZY-SC3s, we employed the atomic cache for workload scheduling, SIMD instructions to accelerate computation, and Local Memory to reduce data read-write operations, addressing issues of poor data locality, workload imbalance, and vectorisation during SpMM execution. As the first study of SpMM on PEZY-SC3s, compared with BS-SpMM and RoDe-SpMM implemented on PEZY-SC3s, LSSM-SpMM offers up to 26.17× and 13.59× acceleration on the SuiteSparse and deep learning datasets, respectively, with geometric mean speedups of 1.56× and 1.71×. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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Implementation of FIR Digital Filter Algorithm in C Language on DSP Platform

Implementation of FIR Digital Filter Algorithm in C Language...

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Information Science, parallel and Distributed Systems (ISPDS), international conference on

作者： Guoyong Wang Huaihua Normal College Huaihua China

ISBN: (数字)9798350352719

ISBN: (纸本)9798350352726

this article provides a detailed overview of the process of implementing an FIR digital filter using the TI TMS320 series DSP platform with the C programming language. It covers topics such as the working principle of FIR filters, design methods, DSP development environment setup, C code implementation, simulation verification, and system testing. through simulation verification, the frequency response characteristics of the FIR filter are confirmed, and the system testing results demonstrate that the FIR filter achieves effective signal filtering under appropriate conditions with accurate frequency response and high signal-to-noise ratio. this document comprehensively validates the excellent signal processing performance of FIR filters on the DSP platform, offering valuable insights for applications involving FIR filter design on DSP platforms.

关键词： Performance evaluation System testing Information science Codes Finite impulse response filters Signal processing algorithms Digital signal processing

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A novel parallel hybrid model for forecasting the stock price 5

A novel parallel hybrid model for forecasting the stock pric...

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5th international conference on Machine Learning and Natural Language processing (MLNLP)

作者： Zhu, Chengdong Xu, Zhenyang Han, Lianfeng China Univ Min & Technol Xuzhou Jiangsu Peoples R China

ISBN: (纸本)9781450399067

In recent years, in addition to the growth in the number of investors in the stock market, there has been a growing interest in predicting stock prices. Accurate stock prices can effectively improve investment returns on the premise of reducing investment risks for stock investors. therefore, this study presents a hybrid Bo-LSTM-SVR model to predict the next day's stock closing price. Firstly, the hyper-parameters of LSTM and SVR as well as the length of their respective sliding windows are optimized by the Bayesian optimization method, so as to obtain more accurate predicted values of the single models. the genetic algorithm is then adopted every day to decide the weight of the two single models, and finally, the combined predicted values are obtained. In order to ensure that the prediction of the proposed model is more accurate, this model and the other six models are applied to predict the closing prices of the Shanghai Composite Index on the next trading day. the results reveal that the model proposed in this study is the most accurate, with the smallest MAE and RMSE as well as the largest R(boolean AND)2. Compared with other models, the proposed model is more suitable for stock price prediction, which provides a dependable tool for investors to make stock investment decisions.

关键词： stock price prediction hybrid model Bayesian optimization LSTM SVR

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Language-Based Colorization with Sparse Attention and Multi-scale Cross-Modal Semantic Alignment 24th

Language-Based Colorization with Sparse Attention and Mult...

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24th international conference on algorithms and architectures for parallel processing, ICA3PP 2024

作者： Zhang, Ying Gao, Yutong Liu, Xuan Zhang, Lefeng Liu, Xianggan Jiang, Shan Ethnic Language Intelligent Analysis and Security Governance Minzu University of China Beijing China Faculty of Data Science City university of Macau China Natural Language Processing and Knowledge Graph Lab Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9789819615476

Language-based colorization generates realistic and aesthetically appealing colors by leveraging the guidance of intuitive and user-friendly natural language descriptions. Previous methods in language-based image colorization face several significant challenges, including limited color richness, color bleeding, color distortions, and inconsistent color styles. these issues often arise due to the reliance on dense attention mechanisms, which can lead to an overemphasis on global features at the expense of local details. Furthermore, many feature fusion modules for text and grayscale images are not designed to achieve adequate alignment of the diverse feature representations, resulting in suboptimal colorization outcomes. In this paper, we explore a novel module that employs sparse attention to mitigate the issue of color bleeding and limited colorfulness in image colorization tasks. By introducing a sparse attention mechanism, our method enables more flexible allocation of computational resources with a focus on color awareness. Additionally, we propose a module that effectively aligns grayscale images with color descriptions, thereby improving the consistency and quality of the colorization results. this module leverages the synergy between image features and language descriptions to solve long-standing issues like color bleeding. Empirical evaluations demonstrate that our approach surpasses recent state-of-the-art techniques in both automatic and language-based colorization tasks, validating the effectiveness and robustness of our proposed method in generating high-quality, visually appealing colorized images. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Semantics

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Fault Diagnosis Based on Digital Twin Modeling of Bearings

Fault Diagnosis Based on Digital Twin Modeling of Bearings

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Information Science, parallel and Distributed Systems (ISPDS), international conference on

作者： Zhenxin Liang Ziwen Wu School of Mechanical Engineering Xinjiang University Urumqi China

ISBN: (数字)9798350352719

ISBN: (纸本)9798350352726

As critical rotating machinery components, the monitoring of the health status and fault diagnosis of bearings become particularly important. In this paper, a bearing digital twin model and fault diagnosis system based on ANSYS and Matlab is proposed. First, a high-precision digital twin model of the bearing was constructed using ANSYS software, which can simulate the physical behavior of the bearing under different working conditions. Subsequently, a Matlab-based fault diagnosis system was developed, which is able to read vibration data automatically and extract fault features through an improved spectral cliff algorithm and deconvolution algorithm. the system is designed with a modular architecture, including key aspects such as data acquisition, signal preprocessing, feature extraction and fault diagnosis. the experimental results show that the proposed system outperforms the traditional methods in terms of the accuracy of fault detection and the efficiency of diagnosis.

关键词： Fault diagnosis Deconvolution Software algorithms Signal processing algorithms Feature extraction Prediction algorithms Mathematical models

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5th international conference on Applications of Fluid Dynamics, ICAFD 2020

5th International Conference on Applications of Fluid Dynami...

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5th international conference on Applications of Fluid Dynamics, ICAFD 2020

ISBN: (纸本)9789811919282

the proceedings contain 33 papers. the special focus in this conference is on Applications of Fluid Dynamics. the topics include: Impact of Radiation on Flow of Copper-Water Nanofluid Squeezed Between parallel Plates Filled with Darcy Porous Medium;MHD Flow of Casson Nanofluid Over An Inclined Porous Stretching Surface;dispersion of Rayleigh Wave in a Shielded Anisotropic Generalized thermoelastic Layer;nonlinear Equation for Wave Motion with Undulated Bottom;numerical Study on Nanofluid Flow and Heat Transfer Over a thin Moving Needle with Arrhenius Pre-Exponential Factor Law and Slip Effect;effect of Magnetic Field on Unsteady Flow of Dusty Fluid Due to Constant Pressure Gradient through a Circular Cylinder: An Analytical Treatment;convective Flow over a Vertical Cone Embedded in a Stratified Medium by Group theoretical Method;peristaltic Flow of Ferromagnetic Fluid in a Vertical Slot with Mixed Convection;mathematical Modeling for Non-linear Wave Interaction of Submerged Body Using Hybrid Element Method;aligned Magnetic Field and Radiation Absorption Effects on Free Convection Chemically Reactive Flow Past An Inclined Surface;Investigating the Risk of Airborne COVID-19 and the Importance of Social Restrictions in Regulating the Transmission;a Numerical Algorithm Based on Tension Spline Scheme for Solving Singularly Perturbed Differential Difference Equations with Shifts;splines for Atmospheric Data;Dynamics of SEIR Model of Nipah Virus;thermodynamic Analysis of Cross-Flow Heat Exchanger with Organic Blends As Substitute to Ionic Coolants;modified Image processing Technique for Measurement of Intermittent Flow Characteristics;Modification of Surface Properties of AA7075 by Friction Stir processing;POD—ANN Reduced Order Macromodel of Nonlinear Autonomous Dissipative System Using Machine Learning.

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Halide Code Generation Framework in Phylanx 28th

Halide Code Generation Framework in Phylanx

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28th international European conference on parallel and Distributed Computing , Euro-Par 2022

作者： Tohid, R. Shirzad, Shahrzad Taylor, Christopher Sakin, Sayef Azad Isaacs, Katherine E. Kaiser, Hartmut Center for Computation and Technology Louisiana State University Baton Rouge United States Tactical Computing Labs Muenster United States SCI Institute University of Utah Salt Lake City United States

ISBN: (纸本)9783031312083

Separating algorithms from their computation schedule has become a de facto solution to tackle the challenges of developing high performance code on modern heterogeneous architectures. Common approaches include Domain-specific languages (DSLs) which provide familiar APIs to domain experts, code generation frameworks that automate the generation of fast and portable code, and runtime systems that manage threads for concurrency and parallelism. In this paper, we present the Halide code generation framework for Phylanx distributed array processing platform. this extension enables compile-time optimization of Phylanx primitives for target architectures. To accomplish this, (1) we implemented new Phylanx primitives using Halide, and (2) partially exported Halide’s thread pool API to carry out parallelism on HPX (Phylanx’s runtime) threads. (3) showcased HPX performance analysis tools made available to Halide applications. the evaluation of the work has been done in two steps. First, we compare the performance of Halide applications running on its native runtime with that of the new HPX backend to verify there is no cost associated with using HPX threads. Next, we compare performances of a number of original implementations of Phylanx primitives against the new ones in Halide to verify performance and portability benefits of Halide in the context of Phylanx. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Array processing

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Comparative Analysis of parallel and Cascaded architectures for the Realization of High-Speed FIR Filters with FPGA

Comparative Analysis of Parallel and Cascaded Architectures ...

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international conference on Inventive Research in Computing Applications (ICIRCA)

作者： Apurva Kumari Lolla Mahidhar Kotha Manideep Kodali Mounika Dept. of ECE B V Raju Institute of Technology Narsapur India

this research work presents a detailed analysis on the design and implementation of parallel and cascade topologies in addition to the realization of high-speed FIR filters using FPGAs. An FPGA-based FIR filter's design, implementation, and verification using Verilog HDL are thoroughly analyzed. It is demonstrated that the filter's hardware implementation is effective in terms of clock frequency, utilization of resources, and latency. the architectures are also contrasted, and their benefits and shortcomings are discussed. the parallel architecture is better suitable for high-speed FIR filters than the cascade architecture, according to implementation findings on a Xilinx Spartan-3E FPGA and a VIRTEX FPGA.

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