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检索条件"任意字段=9th International Conference on Algorithms and Architectures for Parallel Processing"

共 2826 条记录，以下是11-20 订阅

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19th international conference on algorithms and architectures for parallel processing, ICA3PP 2019

19th International Conference on Algorithms and Architecture...

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19th international conference on algorithms andarchitectures for parallel processing, ICA3PP 2019

ISBN: (纸本)9783030389604

the proceedings contain 102 papers. the special focus in this conference is on algorithms and architectures for parallel processing. the topics include: Utility-Based Location Distribution Reverse Auction Incentive Mechanism for Mobile Crowd Sensing Network;safeguarding Against Active Routing Attack via Online Learning;reliability Aware Cost Optimization for Memory Constrained Cloud Workflows;null Model and Community Structure in Heterogeneous Networks;an Asynchronous Algorithm to Reduce the Number of Data Exchanges;two-Stage Clustering Hot Event Detection Model for Micro-blog on Spark;mobility-Aware Workflow Offloading and Scheduling Strategy for Mobile Edge Computing;HSPP: Load-Balanced and Low-Latency File Partition and Placement Strategy on Distributed Heterogeneous Storage with Erasure Coding;adaptive Clustering for Outlier Identification in High-Dimensional Data;Improving the parallelism of CESM on GPU;penguin Search Aware Proactive Application Placement;a Data Uploading Strategy in Vehicular Ad-hoc Networks Targeted on Dynamic Topology: Clustering and Cooperation;Cloud Server Load Turning Point Prediction Based on Feature Enhanced Multi-task LSTM;Neuron Fault Tolerance Capability Based Computation Reuse in DNNs;reliability Enhancement of Neural Networks via Neuron-Level Vulnerability Quantization;A Fault Detection Algorithm for Cloud Computing Using QPSO-Based Weighted One-Class Support Vector Machine;paraMoC: A parallel Model Checker for Pushdown Systems;FastDRC: Fast and Scalable Genome Compression Based on Distributed and parallel processing;a parallel Approach to Advantage Actor Critic in Deep Reinforcement Learning;Blockchain-PUF-Based Secure Authentication Protocol for Internet of things;parallel Approach to Sliding Window Sums;selective Velocity Distributed Indexing for Continuously Moving Objects Model;a New Bitcoin Address Association Method Using a Two-Level Learner Model.

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A High-Speed FPGA Implementation of the Multidimensional Reconciliation for Continuous Variables Quantum Key Distribution 9

A High-Speed FPGA Implementation of the Multidimensional Rec...

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9th international conference on Communication, Image and Signal processing, CCISP 2024

作者： Sun, Jialu Cheng, Hao Jin, Zeyuan Chen, Yong Chen, Genlong Ren, Lihong Jiang, Xueqin School of Information Science and Technology Donghua University Shanghai China

ISBN: (纸本)9798350356656

For continuous variable quantum key distribution (CV-QKD) protocol, information reconciliation (IR) is a key step that can significantly affect the performance of CV-QKD. Because of multidimensional reconciliation suitable for low signal-to-noise ratio (SNR) and long transmission distance scenario, a parallel architecture for the multidimensional reconciliation in CV-QKD implemented on field programmable gate array (FPGA) is proposed in this paper. Using a binarized d-dimensional spherical vector c and a parallel computation of the coefficient a and rotation matrix M, the parallel architecture achieves 45.635 Mbps processing throughput at 250 MHz in the system clock, with frame error rate (FER) less than 0.001 when the SNR exceeds 0.71 dB. © 2024 IEEE.

关键词： parallel architectures

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19th international conference on algorithms and architectures for parallel processing, ICA3PP 2019

19th International Conference on Algorithms and Architecture...

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19th international conference on algorithms andarchitectures for parallel processing, ICA3PP 2019

ISBN: (纸本)9783030389901

the proceedings contain 102 papers. the special focus in this conference is on algorithms and architectures for parallel processing. the topics include: A New Robust and Reversible Watermarking Technique Based on Erasure Code;exit-Less Hypercall: Asynchronous System Calls in Virtualized Processes;automatic Optimization of Python Skeletal parallel Programs;impromptu Rendezvous Based Multi-threaded Algorithm for Shortest Lagrangian Path Problem on Road Networks;FANG: Fast and Efficient Successor-State Generation for Heuristic Optimization on GPUs;DETER: Streaming Graph Partitioning via Combined Degree and Cluster Information;which Node Properties Identify the Propagation Source in Networks?;t/t-Diagnosability of BCube Network;strark-H: A Strategy for Spatial Data Storage to Improve Query Efficiency Based on Spark;SWR: Using Windowed Reordering to Achieve Fast and Balanced Heuristic for Streaming Vertex-Cut Graph Partitioning;multitask Assignment Algorithm Based on Decision Tree in Spatial Crowdsourcing Environment;TIMOM: A Novel Time Influence Multi-objective Optimization Cloud Data Storage Model for Business Process Management;RTEF-PP: A Robust Trust Evaluation Framework with Privacy Protection for Cloud Services Providers;a Privacy-Preserving Access Control Scheme with Verifiable and Outsourcing Capabilities in Fog-Cloud Computing;utility-Aware Edge Server Deployment in Mobile Edge Computing;predicting Hard Drive Failures for Cloud Storage Systems;Efficient Pattern Matching on CPU-GPU Heterogeneous Systems;improving Performance of Batch Point-to-Point Communications by Active Contention Reduction through Congestion-Avoiding Message Scheduling;an Open Identity Authentication Scheme Based on Blockchain;RBAC-GL: A Role-Based Access Control Gasless Architecture of Consortium Blockchain;flexible Data Flow Architecture for Embedded Hardware Accelerators;developing Patrol Strategies for the Cooperative Opportunistic Criminals.

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Comparative Analysis of Various CNN architectures in Recognizing Objects in a Classification System 9

Comparative Analysis of Various CNN Architectures in Recogni...

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9th IEEE international conference for Convergence in Technology, I2CT 2024

作者： Surve, Yash Pudari, Kshitija Bedade, Sonali Masanam, Balaji Durai Bhalerao, Kinnari Mhatre, Pratik Vidyalankar Institute of Technology Department of Electronics And Telecommunication Engineering Mumbai India

ISBN: (纸本)9798350394474

Object recognition, an essential technique in computer vision, enables machines to identify and understand real-time objects and environments based on input images. the main aim of this technology is to accurately recognize image features to enable accurate object recognition. With the rapid evolution of various machine learning (ML) and deep learning (DL) algorithms, the world of image processing and computer vision has witnessed significant growth. Deep learning algorithms offer high accuracy by processing vast amounts of data, while machine learning algorithms provide flexibility in selecting the best combinations of features and classifiers for learning purposes. Convolutional Neural Network (CNN) is a widely used deep-learning model that is highly effective in classifying images. AlexNet, VGG16, ResNet and GoogleNet are some of the well-known CNN architectures used for object recognition. the paper proposes a comparative analysis of prediction accuracy between these pre-trained CNN models using transfer learning. the transfer learning approach, on the other hand, involves the fine-tuning of pre-trained models to enhance prediction accuracy in various image classification scenarios. In this paper, the CNN models are trained and tested on a dataset containing images of apples, oranges and bananas. Experimental results with a real dataset show that MobileNet V2 has the highest accuracy of 92.80%. © 2024 IEEE.

关键词： Image classification

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Novel Control Structures for parallel Two-Stage Converters Based on Shared SVPWAM/SVPWM 9

Novel Control Structures for Parallel Two-Stage Converters B...

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9th international conference on Power and Renewable Energy

作者： Wu, Zhuoqun Yanshan Univ Dept Elect Engn Qinhuangdao Hebei Peoples R China

ISBN: (纸本)9798350377477;9798350377460

Current-source converters are favored for their special and wide output voltage range. In order to increase power transmission, the structure and control strategies of parallel current-source converters have been developed. Meanwhile, two-stage cascaded current-source converters have an extremely wide output voltage range. However, until now, the control strategy for two-stage parallel current- source converters has not been studied. therefore, this paper focuses on the control structure of current-source converters with this particular topology. Based on the proposed control architecture, multiple parallel current-source converters only need to use the same SVPWM or SVPWAM (Space Vector Pulse Width Modulation) (Space Vector Pulse Width Amplitude Modulation), eliminating the need for each parallel converter to use its own modulation scheme as in traditional droop control architectures. Even in the presence of differences in parameters among paralleled branches and filters, sinusoidal grid current, unit power factor, 1000V output for the load can still be achieved. Simulation results also validate the correctness of theoretical analysis and the effectiveness of the proposed approach.

关键词： SVPWAM two-stage current-source converter modulation multiplexing droop control

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ICBSP 2024 - Proceedings of the 2024 9th international conference on Biomedical Imaging, Signal processing

ICBSP 2024 - Proceedings of the 2024 9th International Confe...

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2024 9th international conference on Biomedical Imaging, Signal processing, ICBSP 2024

ISBN: (纸本)9798400717499

the proceedings contain 24 papers. the topics discussed include: an integrated deep learning model to analyze CT scans for minimally invasive accurate classification of T1a small renal masses;tissue type classification for whole slide histological images with graph convolutional neural network;classifying skin diseases using convolutional neural networks;comparative analysis of YOLO architectures for automated detection of liver disease in histopathological images;bibliometric analysis and research trends in artificial intelligence for medical imaging in Alzheimer’s disease;personalized federated learning using client clustering for medical image classification;data augmentation of domain learning in optic nerve combined cup-disc segmentation with a few labeled data;and a coronary plaque detection and identification method based on medical prior knowledge and hybrid attention unit.

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A Bandwidth-Adaptive On-Chip Storage Network Architecture 9

A Bandwidth-Adaptive On-Chip Storage Network Architecture

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9th international conference on Integrated Circuits and Microsystems, ICICM 2024

作者： Wang, Kou Yu, Ningmei Tian, Dian Yang, Liang Wang, Peng Xie, Minghui School of Automation and Information Engineering Xi'an University of Technology Xi'an China University of Alcalá Electronics Department Alcalá de Henares Madrid Spain

ISBN: (纸本)9798331509453

A scalable bandwidth-adaptive on-chip storage network architecture is proposed to address the severe data conflict and low bus parallelism in existing multi-level storage, Crossbar, and NoC architectures in edge accelerated computing. this architecture combines the advantages of centralized and distributed memory, allowing the memory hierarchy to be flexibly adapted based on current computational needs and memory access patterns to better accommodate multi-core processors and parallel computing requirements. this paper designs the result visualization method to visualize the stress of storing each node and bus. Furthermore, the full path test incentive is intended for the secondary sharing policy and router. the feasibility of this paper's architecture is verified through VCS simulation and visualization analysis. © 2024 IEEE.

关键词： parallel architectures

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Pomelo: Alternative Mechanism of threads Communication for Accelerating Convolution on SIMT Based Processor 9

Pomelo: Alternative Mechanism of Threads Communication for A...

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9th international conference on Intelligent Computing and Signal processing, ICSP 2024

作者： Feng, Zhenfu Yang, Lele Zhang, Yaying Xi'an University of Posts and Telecommunications School of Engineering Xi'an China

ISBN: (纸本)9798350376548

Single Instruction Multiple thread (SIMT) based processor and parallel model are effective ways to solve computation problems exist in big data era. Commonly, work load is organized into mass parallel computing threads according the specific application. However, interaction and communication between parallel individual threads is inevitable during the whole computing process. In this work, 1) a SIMT based processor named Pomelo is developed, 2) a fundamental thread communication method based on shard memory is implemented, 3) communication avoiding mechanism for reducing the time cost of thread communication is studied, 4) and convolution based test set is adapted on Pomelo to verify the effectiveness of the proposed mechanism. Experimental result illustrates that Pomelo processor equipped with proposed mechanism achieves 2X performance augmentation on test sets based on convolution. © 2024 IEEE.

关键词： parallel processing systems

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PLG-IQB: parallel LSTM-GRU with Improved QuickBundles for Vessel Trajectory Prediction 9

PLG-IQB: Parallel LSTM-GRU with Improved QuickBundles for Ve...

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9th international conference on Intelligent Computing and Signal processing, ICSP 2024

作者： Chen, Xueqin Yang, Jinlong School of Artificial Intelligence and Computer Science Jiangnan University Wuxi China

ISBN: (纸本)9798350376548

With the advancement of intelligent transportation systems, ship automatic identification system (AIS) data contains rich maritime traffic information. Utilizing this information effectively contributes to enhancing the efficiency of ship trajectory prediction. Traditional deep learning trajectory prediction algorithms often focus on improving the accuracy of short-term prediction models while neglecting the thorough utilization of navigational features, thereby limiting the achievement of longer-term trajectory prediction. To address the current inability of ship trajectory prediction to perform long-term forecasts, this study proposes an improved QuickBundles clustering algorithm for extracting navigational features. Subsequently, this navigational information is integrated into a parallel LSTM-GRU prediction model to achieve longer-term ship trajectory prediction. Experiments are conducted using data from the Houston-Galveston Bay area obtained from open sources (https://***), and the results demonstrate that the PLG-IQB algorithm performs well in long-term trajectory prediction. © 2024 IEEE.

关键词： Prediction models

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Massively parallel EEG algorithms for Pre-exascale architectures

Massively Parallel EEG Algorithms for Pre-exascale Architect...

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29th international conference on parallel and Distributed Computing (Euro-Par)

作者： Wang, Zeyu Juhasz, Zoltan Univ Pannonia Veszprem Hungary

ISBN: (纸本)9783031488023;9783031488030

High-density EEG is a non-invasive measurement method with millisecond temporal resolution that allows us to monitor how the human brain operates under different conditions. the large amount of data combined with complex algorithms results in unmanageable execution times. Large-scaleGPU parallelism provides the means to drastically reduce the execution time of EEG analysis and bring the execution of large cohort studies (over thousand subjects) within reach. this paper describes our effort to implement various EEG algorithms for multiGPUpre-exascale supercomputers. Several challenges arise during thiswork, such as the high cost of data movement and synchronisation compared to computation. A performance-oriented end-to-end design approach is chosen to develop highlyscalable, GPU-only implementations of full processing pipelines and modules. Work related to the parallel design of the family of Empirical Mode Decomposition algorithms is described in detail with preliminary performance results of single-GPU implementations. the research will continue with multi-GPU algorithm design and implementation aiming to achieve scalability up to thousands of GPU cards.

关键词： EEG Pre-exascale computing GPU

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