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24th international conference on Algorithms and Architectures for parallel Processing, ICA3PP 2024

24th International Conference on Algorithms and Architecture...

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24th international conference on Algorithms and Architectures for parallel Processing, ICA3PP 2024

ISBN: (纸本)9789819615414

The proceedings contain 131 papers. The special focus in this conference is on Algorithms and Architectures for parallel Processing. The topics include: MARO: Enabling Full MPI Automatic Refactoring in DSL-Based Programming Framework;SSC: An SRAM-Based Silence computing Design for On-chip Memory;TP-BFT: A Faster Asynchronous BFT Consensus with parallel Structure;LTP: A Lightweight On-Chip Temporary Prefetcher for Data-Dependent Memory Accesses;A Neural Network-Based PUF Protection Method Against Machine Learning Attack;Compression Format and Systolic Array Structure Co-design for Accelerating Sparse Matrix Multiplication in DNNs;multidimensional Intrinsic Identity Construction and Dynamic Seamless Authentication Schemes in IoT Environments;invisible Backdoor Attack with Image Contours Triggers;finestra: Multi-aggregator Swarm Learning for Gradient Leakage Defense;DIsFU: Protecting Innocent Clients in Federated Unlearning;multiple-Round Aggregation of Abstract Semantics for Secure Heterogeneous Federated Learning;dynamic Privacy Protection with Large Language Model in Social networks;a Dynamic Symmetric Searchable Encryption Scheme for Rapid Conjunctive Queries;a Data Watermark Scheme Base on Data Converted Bitmap for Data Trading;distributed Incentive Algorithm for Fine-Grained Offloading in Vehicular Ad Hoc networks;mitigating Over-Unlearning in Machine Unlearning with Synthetic Data Augmentation;AW-YOLOv9: Adverse Weather Conditions Adaptation for UAV Detection;efficient and Privacy-Preserving Ranking-Based Federated Learning;on-Chain Dynamic Policy Evaluation for Decentralized Access Control;DPG-FairFL: A Dual-Phase GAN-Based Defense Framework Against Image-Based Fairness Data Poisoning Attacks in Federated Learning.

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24th international conference on Algorithms and Architectures for parallel Processing, ICA3PP 2024

24th International Conference on Algorithms and Architecture...

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24th international conference on Algorithms and Architectures for parallel Processing, ICA3PP 2024

ISBN: (纸本)9789819615445

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Securing Digital Integrity: Proposed Comprehensive Framework for Deepfake Detection and Blockchain Validation 5th

Securing Digital Integrity: Proposed Comprehensive Framework...

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5th international conference on computing, Communications, and Cyber Security, IC4S 2023

作者： Jain, Anant Gaur, Adamya Gupta, Gauranshi Mishra, Shubhangi Johari, Rahul Vidyarthi, Deo Prakash Guru Gobind Singh Indraprastha University Delhi India School of Computer and Systems Sciences Parallel and Distributed System Lab JNU Delhi India

ISBN: (纸本)9789819773701

This paper proposes a comprehensive solution to combat the growing threat of Deepfake technology, employing Convolutional Neural networks (CNNs) and Blockchain. CNNs analyze video frames for anomalies indicative of Deepfake manipulation, while Blockchain ensures content integrity through timestamping and IPFS hashes. Leveraging transfer learning with EfficientNet-B1 architecture and dropout layers to prevent overfitting, the CNN model attains a 98.53% accuracy on testing data. Smart contracts are utilized to store social media content and AI verification results. The methodology integrates private storage on social media platforms, AI-based CNN verification, Blockchain timestamping, smart contract verification, and continuous improvement. By synergizing AI and Blockchain technologies, our approach aims to bolster defenses against deceptive content proliferation, enhancing the reliability of online media ecosystems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Proceedings of the Fifteenth iasted international conference on parallel and distributed computing and Systems

Proceedings of the Fifteenth IASTED International Conference...

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Proceedings of the Fifteenth iasted international conference on parallel and distributed computing and Systems

ISBN: (纸本)088986392X

The proceedings contains 69 papers from Fifteenth iasted international conference on parallel and distributed computing and systems. The topics discussed include: computing nearest neighbours in real time;distributed algorithms for constructing multicast trees;properties of neural networks studied from ND geometry and discrete algebra;knowledge inference for mobile monitoring;parallel design of multichannel inverse filters for audio reproduction;design of local access networks;a set-based approach to packet classification and a hybrid scheme for transmission schedules in streaming media.

关键词： parallel processing systems

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Comprehensive Deadlock Prevention for GPU Collective Communication 25

Comprehensive Deadlock Prevention for GPU Collective Communi...

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20th European conference on Computer Systems, EuroSys 2025, co-located 30th ACM international conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2025

作者： Pan, Lichen Liu, Juncheng Fu, Yongquan Yuan, Jinhui Zhang, Rongkai Li, Pengze Xiao, Zhen School of Computer Science Peking University China OneFlow Research China National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Defense Technology China

ISBN: (纸本)9798400711961

distributed deep neural network training necessitates efficient GPU collective communications, which are inherently susceptible to deadlocks. GPU collective deadlocks arise easily in distributed deep learning applications when multiple collectives circularly wait for each other. GPU collective deadlocks pose a significant challenge to the correct functioning and efficiency of distributed deep learning, and no general effective solutions are currently available. Only in specific scenarios, ad-hoc methods, making an application invoke collectives in a consistent order across GPUs, can be used to prevent circular collective dependency and deadlocks. This paper presents DFCCL, a novel GPU collective communication library that provides a comprehensive approach for GPU collective deadlock prevention while maintaining high performance. DFCCL achieves preemption for GPU collectives at the bottom library level, effectively preventing deadlocks even if applications cause circular collective dependency. DFCCL ensures high performance with its execution and scheduling methods for collectives. Experiments show that DFCCL effectively prevents GPU collective deadlocks in various situations. Moreover, extensive evaluations demonstrate that DFCCL delivers performance comparable to or superior to NCCL, the state-of-the-art collective communication library highly optimized for NVIDIA GPUs. © 2025 Copyright held by the owner/author(s).

关键词： Deep neural networks

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A Q-Learning Driven Artificial Bee Colony Algorithm for Multi-objective Multiplex Industrial Chain networks Design with Multiple Supply Cycles 25th

A Q-Learning Driven Artificial Bee Colony Algorithm for Mul...

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25th international conference on parallel and distributed computing, Applications and Technologies, PDCAT 2024

作者： Wang, Zhenyu Sun, Xianzhou An, Zhengyi Jiang, Yichuan Di, Kai Hu, Xianghui School of Cyber Science and Engineering Southeast University Nanjing211189 China School of Computer Science and Engineering Southeast University Nanjing211189 China

ISBN: (纸本)9789819642069

The traditional single industrial chain structure is gradually evolving into the multiplex industrial chain networks. The design problem of multiplex industrial chain networks with multiple supply cycles (MICND-MSC) is studied in this paper. The impact of cross-chain supply of multiple raw materials by enterprises during the production process is considered in the problem. The mixed-integer linear programming (MILP) model of MICND-MSC is constructed and an artificial bee colony algorithm (ABC) with reinforcement learning mechanism (LDABC) is proposed to address the MICND-MSC. Heuristic methods named HMC, HMR, and PRH are designed to construct potential initial candidates for the population. The neighborhood structures for different production stages are employed in the LDABC to explore the solution space during the evolution processes. The reinforcement learning mechanism is utilized to learn empirical knowledge of neighborhood structures to guide the search process. The experimental results show that the LDABC is a potential algorithm to address the MICND-MSC. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Heuristic methods

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XMeta-OS: A Conceptual Framework for Unified Resource Management in distributed Edge-Cloud Environments 3rd

XMeta-OS: A Conceptual Framework for Unified Resource Manag...

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3rd international conference on Advances in computing Research, ACR 2025

作者： Zacharioudakis, Eleftherios Kakoulli, Elena Evripidou, Salomi Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos Pafos Cyprus National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9783031876462

This paper introduces XMeta-OS, a meta-operating system specially designed with Linux as its foundation to unify and optimize resource management for the distributed edge-cloud when dynamic use of GPU resources is possible. This approach offer a new GPU abstraction layer and dynamic edge-cloud allocation model that offer enhanced flexibility and resource utilization over existing systems like Kubernetes and OpenStack. By using likely sensitive data, the model applied cloud-pushed deployment model. XMeta-OS manages computer resources in real-time. Therefore, fulfilling high performance various needs. It allocates CPU and GPU in real-time to workloads requiring massive parallel processing, such as machine learning, scientific simulations, real-time data analytics, and transportation tasks. Fabrication in the laboratory of an edge-cloud environment can help to assess the scalability, fault tolerance and efficiency of the system. It showcases the overall architectural design of XMeta-OS. Changes to the kernel and security solutions for safe and effective distribution are suggested. This article presents the design of the XMeta-OS. The future of XMeta-OS entails usage and testing with which we see latency, energy, computation and other such measurements in labs. XMeta-OS is a solution to cost performance, emerging application, large-scale edge-cloud deployments, and distributed GPU-enabled infrastructures. Meta-Operating System in Edge-Cloud Continuum for dynamic resource management of GPU. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cluster computing

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Long-Term and Periodicity-Aware Spatio-Temporal Model for Traffic Flow Prediction 25th

Long-Term and Periodicity-Aware Spatio-Temporal Model for Tr...

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25th international conference on parallel and distributed computing, Applications and Technologies, PDCAT 2024

作者： Hua, Qiang Lv, DongLiang Dong, Chun-Ru Zhang, Feng College of Mathematics and Information Science Hebei University Baoding071002 China

ISBN: (纸本)9789819642069

With the continuous expansion of comprehensive road transport networks in major cities, accurate traffic flow prediction—an essential component of intelligent urban transport systems has become increasingly challenging. Spatio-Temporal Graph Neural networks (STGNNs), which combine time-series models like the Transformer with spatial relationship learning models such as Graph Neural networks (GNNs), have shown significant promise in addressing this challenge. However, they still face issues like insufficient exploitation of long-term dependencies, high structural and computational complexity, and underutilization of periodic patterns in traffic data. To address these limitations, we propose LL-MLP, a spatio-temporal model based on an encoder-decoder architecture. Our approach extends the look-back window to better capture long-term dependencies, introduces learnable parameter matrices to enhance spatial information extraction, and incorporates periodic information as a dynamic covariate to further leverage temporal patterns. Extensive experiments on four real-world traffic datasets demonstrate that LL-MLP achieves performance on par with or exceeding that of existing model architectures. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Graph neural networks

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Proceedings of the iasted international conference on parallel and distributed computing and Systems

Proceedings of the IASTED International Conference on Parall...

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iasted international conference on parallel and distributed computing and networks, PDCN 2007

ISBN: (纸本)9780889866379

The proceedings contain 72 papers. The topics discussed include: effects of hotspots on throughput in mobile ad hoc networks;a localized broadcast scheme for minimizing power consumption in wireless mobile ad hoc networks;no-beacon GEDIR: location-based ad-hoc routing with less communication overhead;an information service infrastructure for ambient networks;battery efficient wireless system discovery scheme for inter-system handover;traffic analysis of mobile sensor networks;cross-layer design based data aggregation for maximizing network lifetime;performance evaluation of offloading software modules to cluster network;performance evaluation on low-latency communication mechanism of DIMMnet-2;a distribution technique for graph rewriting and model transformation systems;theory of commercial application management system and its implementation - amps;and performance of load balancing for grid computing.

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Proceedings of the 16th iasted international conference on parallel and distributed computing and Systems

Proceedings of the 16th IASTED International Conference on P...

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Proceedings of the 16th iasted international conference on parallel and distributed computing and Systems

The proceedings contain 147 papers from the Proceedings of the 16th iasted international conference on parallel and distributed computing and Systems. The topics discussed include: a grid simulation infrastructure supporting advance reservation;auction-based resource allocation protocols in grids;effectiveness of grid configurations on application performance;a constant time shortest-path routing algorithm for pyramid networks;wormhole routers for network-on-chop;communication optimization on broadcast-based clusters;a localization algorithm extension for the evolvable sensor network;and migration algorithms for automated load balancing.

关键词： distributed computer systems

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