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检索条件"任意字段=International Conference on Parallel Distributed and Grid Computing"

共 34218 条记录，以下是161-170 订阅

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Development of a Collaborative Design Platform Based on Bim (Building Information Modeling) and Cloud computing

Development of a Collaborative Design Platform Based on Bim ...

引用

Electronics, Energy Systems and Power Engineering (EESPE), IEEE international conference on

作者： Zekun Chang Shandong Vocational College of Industry Zibo China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

This study proposes a collaborative design platform based on BIM and cloud computing, combined with an innovative real-time synchronization algorithm, to solve the problems of delay, data consistency and synchronization conflict in cloud collaborative design. The proposed real-time synchronization algorithm is based on a distributed computing model. By introducing a distributed lock and timestamp mechanism, it effectively guarantees the data consistency and real-time performance in large-scale collaborative design, and can reduce data conflicts and improve collaborative efficiency when multiple design teams operate in parallel. In order to verify the effectiveness of the platform, this study conducted experiments in multiple architectural design projects, and the platform runs in mainstream cloud computing environments (such as AWS and Azure). The experimental results show that the collaborative design platform based on the innovative algorithm has significant advantages over traditional collaborative design tools in terms of synchronization delay, data transmission speed and number of concurrent users. When multiple design teams collaborate, the design cycle of the platform is shortened by 15 %, the overall work efficiency is improved by more than 20 %, and it can maintain stability and low response time in a high concurrent user environment. In addition, the platform's real-time rendering and version control mechanism also significantly improve the design quality and accuracy.

关键词： Cloud computing Visualization Computational modeling Buildings Collaboration distributed databases Real-time systems Delays Synchronization Security

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A Cloud+HPC hub for astrophysics and cosmology communities

A Cloud+HPC hub for astrophysics and cosmology communities

引用

Euromicro conference on parallel, distributed and Network-Based Processing

作者： Matteo Pasqui ICSC “Centro Nazionale di Ricerca in HPC Big Data and Quantum Computing” INFN Sezione di Roma Tor Vergata

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

The advancement of data-intensive analysis has emphasised the need for extensive, scalable environments that enable easy access to diverse computational resources. This project proposes the development of a Scientific Hub for the astrophysics and cosmology communities, leveraging a global, cloud-based infrastructure that integrates Kubernetes-based offloading to ensure efficient, user-friendly access to High Performance computing (HPC), High Throughput computing (HTC) and cloud resources. This solution introduces “transparent offloading” of containerized workloads using Kubernetes API primitives, creating a unified cloud-native interface that abstracts complexities and optimally allocates resources based on the specific needs of each task. Through the Scientific Hub, users could access JupyterHub-supported environments with configurable resources, persistent data storage and secure authentication, facilitating the execution and sharing of scientific workflows in a robust, scalable manner. This contribution showcases the aims and challenges of the development of the Scientific Hub on ICSC partners’ resources (including the Leonardo supercomputer at CINECA), along with some key use cases.

关键词： Astrophysics High performance computing Memory Logic gates Fasteners Throughput Data processing Supercomputers Computational efficiency Complexity theory

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AI-Driven Network Effects and Tokenization for Next-Gen Communication Networks in Energy Systems

AI-Driven Network Effects and Tokenization for Next-Gen Comm...

引用

Cognitive computing in Engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), international conference on

作者： Mukul Singh Devesh Singh Pal Priyanka Yadav M.A. Ansari Vishwamitra Singh Vikas Beniwal School of Engineering Gautam Buddha University Gautam Budh Nagar India Dept. of Information Technology HIMT Group of Institutions Gautam Budh Nagar India Dept. of Computer Applications HIMT Group of Institutions Gautam Budh Nagar India Indian Institute of Management Kozhikode Kozhikode Kerela India UNSW Engineering University of New South Wales New South Wales Australia

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

The decentralization of energy systems, driven by rapid adoption of renewable energy sources, has posed new challenges in communication, data sharing, and energy trading. Traditional grid structures rarely cope with the fast-changing dynamics of distributed generation resources (DERs), thus demanding smarter and scalable communication networks and mechanisms of synchronizing and optimizing operations. The set of technologies on AI-driven and tokenization-like approaches practically allows for the change. AI-driven networks support this by enabling real-time decision-making and predictive analytics through smart energy distribution and demand forecasting and massively automated grid optimization. Tokenization, reinforced by blockchain technologies, allows the decentralization of energy trading through transparent peer-to-peer (P2P) transactions that ease the encumbrances of the traditional utility. The paper focuses on how AI-driven networks and tokenization integrate to form the future communication networks in energy systems. It highlights their contribution to improving grid efficiency, securing grid infrastructure, diminishing operational costs, and democratizing energy markets. Additionally, it discusses technical challenges, regulatory barriers, and long-term implications while looking ahead and thinking about how these innovations can be used to reorganize energy infrastructures all over the globe and rapidly quicken the shift to decentralized sustainable energy ecosystems.

关键词： Technological innovation Renewable energy sources Tokenization Real-time systems Communications technology Peer-to-peer computing distributed power generation Blockchains Communication networks Predictive analytics

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Research on Traveling Wave Head Detection Algorithm for Wavelet Multi-Scale Information Fusion

Research on Traveling Wave Head Detection Algorithm for Wave...

引用

Advances in Electrical, Electronics and computing Technology (EECT), international conference on

作者： Jiahao Lu Chuyang Liu Tong Wu Kaiqi Zhang Jielong Chen Sizhe Chen Foshan Power Supply Bureau Guangdong Power Grid Co Ltd. Foshan China School of Automation Guangdong University of Technology Guangzhou China

ISBN: (数字)9798331541545

ISBN: (纸本)9798331541552

A wavelet transform multi-scale information synthesis algorithm for traveling wave head detection is proposed. Firstly, the fault traveling wave signal is processed using the multi-scale analysis of wavelet transform to obtain the modulus maximum values of wavelet coefficients at various scales. Then, the modulus maximum values are sequentially calibrated in a parallel coordinate system to form a grayscale image. Finally, a convolutional neural network is used to build a wave head detection model. This algorithm cleverly links wavelet transform with convolutional neural network using a parallel coordinate system, combining information from wavelet transform at multiple scales, providing a new approach for detecting traveling wave heads.

关键词： Wavelet transforms Computers Head Gray-scale Wavelet analysis Convolutional neural networks Detection algorithms Wavelet coefficients

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Batch Updates of distributed Streaming Graphs using Linear Algebra 24

Batch Updates of Distributed Streaming Graphs using Linear A...

引用

Proceedings of the SC '24 Workshops of the international conference on High Performance computing, Network, Storage, and Analysis

作者： Elaheh Hassani Md Taufique Hussain Ariful Azad Dept. of Intelligent Systems Engineering Indiana University Bloomington IN USA

ISBN: (纸本)9798350355543

We develop a distributed-memory parallel algorithm for performing batch updates on streaming graphs, where vertices and edges are continuously added or removed. Our algorithm leverages distributed sparse matrices as the core data structures, utilizing equivalent sparse matrix operations to execute graph updates. By reducing unnecessary communication among processes and employing shared-memory parallelism, we accelerate updates of distributed graphs. Additionally, we maintain a balanced load in the output matrix by permuting the resultant matrix during the update process. We demonstrate that our streaming update algorithm is at least 25 times faster than alternative linear-algebraic methods and scales linearly up to 4,096 cores (32 nodes) on a Cray EX supercomputer.

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A synchronization-free incomplete LU factorization for GPUs with level-set analysis

A synchronization-free incomplete LU factorization for GPUs ...

引用

Euromicro conference on parallel, distributed and Network-Based Processing

作者： Manuel Freire Ernesto Dufrechou Pablo Ezzatti Instituto de Computación Facultad de Ingeniería - UDELAR Montevideo Uruguay

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Incomplete factorization methods are powerful algebraic preconditioners widely used to accelerate the convergence of linear solvers. The parallelization of ILU methods has been extensively studied, particularly for GPUs, which are ubiquitous parallel computing devices. In recent years, synchronization-free methods have become the mainstream approach for solving sparse triangular linear *** the sparse triangular solver and ILU factorization are closely related, the application of synchronization-free strategies to ILU factorization has not been explored in the literature to the same extent as the triangular solver. In this work, we present synchronization-free implementations of the ILU-0 preconditioner on GPUs. Specifically, we propose three implementations that vary in how row updates are handled after each coefficient elimination, as well as an additional approach that leverages a prior level-set analysis to optimize the execution schedule.

关键词： Linear systems Schedules parallel processing Synchronization Convergence

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An Optimal SG-MFO Based Renewable Energy Source Power Quality Improvement Using UPQC in DPFC System

An Optimal SG-MFO Based Renewable Energy Source Power Qualit...

引用

Advancements in Electrical, Electronics, Communication, computing and Automation (ICAECA), international conference on

作者： T Dineshkumar P Thirumoorthi M Mathankumar Electrical and Electronics Engineering Kumaraguru College of Technology Coimbatore India Electrical and Electronics Engineering SRM Institute of Science and Technology Tiruchirapalli India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

This work proposes an optimal Stochastic Gradient Moth Flame Optimization (SG-MFO) based renewable energy source power quality improvement using Unified Power Quality Conditioner (UPQC) in a distributed Power Flow Controller (DPFC) system. Power quality issues have become increasingly prevalent due to the growing use of non-linear loads and power electronics devices. The integration of renewable energy sources (RES) into the grid further exacerbates these challenges. To address these concerns, this research introduces a novel approach combining UPQC with an SG-MFO algorithm to enhance power quality in a WSCC 3-machine 9 bus system. The SG-MFO algorithm is employed to optimize the PID controller parameters and improve the Maximum Power Point Tracking (MPPT) mechanism. The proposed system incorporates a photovoltaic (PV) source and aims to mitigate harmonics, voltage sags, and swells while maximizing energy extraction from renewable sources. Experimental results demonstrate significant improvements in grid voltage and current Total Harmonic Distortion (THD). The grid current THD was reduced from 11.2% to 3.03%, while the grid voltage THD decreased from 7.39% to 1.15% after UPQC activation. The system also effectively compensated for voltage sags and swells, maintaining stable grid voltage and current. These results highlight the efficacy of the proposed SG-MFO based UPQC-DPFC system in enhancing power quality.

关键词： Maximum power point trackers Renewable energy sources Total harmonic distortion Power quality Fires Harmonic analysis Power electronics Telecommunication computing Voltage control Optimization

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A Comparative Analysis of Microgrid Integration with Single Inverter and parallel Inverters for grid Connection

A Comparative Analysis of Microgrid Integration with Single ...

引用

Smart Systems for applications in Electrical Sciences (ICSSES), international conference on

作者： Karthik RP Shobha Shankar Avinash R Pramod Bhat Nempu Dept of Electrical and Electronics Engineering Vidyavardhaka College of Engineering Mysuru Dept of Electrical and Electronics Engineering Nitte Mahalinga Adyantaya Memorial Institute of Technology NITTE (deemed to be university) Nitte

ISBN: (数字)9798331507671

ISBN: (纸本)9798331507688

This work focuses on renewable energy based microgrid (MG) consisting of two kinds of inverter connection topologies. The MG has two different Renewable Energy Sources (RES) and one Energy Storage System (ESS), which supports the microgrid to share power with the utility grid. The proposed work focuses on comparison of both single inverter and parallel inverter connection topology by considering most of the possible technical feasibility and economic aspects. The MG is a hybrid system involving Wind/PV/Battery system. The Perturb & Observe technique for boost converter is implemented for the maximum power traction. The whole idea of this work is conducted in MATLAB/Simulink model. The comparative analysis ensures the proper architecture of MG to utilize most of the renewable and distributed energy based on control aspects, reliability and economics.

关键词： Economics Renewable energy sources Redundancy Microgrids Smart systems Inverters Stability analysis Topology Synchronization Voltage control

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Federated Meta Continual Learning for Efficient and Autonomous Edge Inference 24th

Federated Meta Continual Learning for Efficient and Autono...

引用

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

作者： Li, Bingze Ho, Stella Qu, Youyang Xu, Chenhao Luan, Tom H. Gao, Longxiang Jinan China Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China Department of Biomedical Engineering The University of Melbourne VIC Melbourne Australia School of Information Technology Deakin University VIC Geelong Australia School of Cyber Engineering Xidian University Xi’an China

ISBN: (纸本)9789819615476

With an increasing volume of data being collected and processed on edge, Federated Learning (FL) has become a dominant approach to train shared global models on distributed data held by diverse edge clients without exposing privacy. However, with expectations of high-quality user experience, instantaneous intelligent decisions must be made at the network edge to meet performance, security, and latency requirements. Intuitively, this challenge becomes more daunting as edge devices are constrained by limited computing and storage resources. Furthermore, edge clients need to continuously acquire, update, accumulate, and apply knowledge in domains requiring the processing of sensitive data and long-term model training. It has been proven that edge clients often forget previous tasks knowledge after learning new tasks, resulting in catastrophic forgetting. To mitigate this, we propose a Federated Meta Continual Learning (FMCL) approach. It requires edge clients not only to learn new tasks quickly but also to memorize rapidly. Specifically, we adopted a MAML (Model-Agnostic Meta-Learning) framework with memory replay, setting up buffers at edge clients to consolidate old tasks. In such a way, the model learns optimal initialization to quickly adapt to all seen tasks while preventing catastrophic forgetting. Extensive evaluation results indicate that FMCL performs well in alleviating catastrophic forgetting and achieves a good balance between learning new tasks and remembering existing tasks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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Introduction to parallel and distributed Programming using N-Body Simulations 24

Introduction to Parallel and Distributed Programming using N...

引用

Proceedings of the SC '24 Workshops of the international conference on High Performance computing, Network, Storage, and Analysis

作者： Alexander Van Craen Marcel Breyer Dirk Pflüger University of Stuttgart IPVS SC Stuttgart Germany

ISBN: (纸本)9798350355543

This paper describes how we use n-body simulations as an interesting and visually compelling way to teach efficient, parallel, and distributed programming. Our first course focuses on bachelor students introducing them to algorithmic complexities and their implications in real-world problems and state-of-the-art tools like Git, remote development, or C++, by simulating the collision of two galaxies. This project teaches the mapping of mathematical functions into code, efficient implementations, and the pitfalls around complexity and scaling. Our second course targets master students introducing them to intra- and inter-node parallelization. Here, the students simulate our solar system using OpenMP and MPI. The master students further deepen their knowledge of parallelization and scientific computing by choosing custom projects like simulating water molecules or implementing an interactive live visualization using *** courses are structured such that they can easily be adapted by other instructors. All our material is publicly available at https://***/orgs/SCTeaching-NBody.

关键词： education

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