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共 34220 条记录，以下是131-140 订阅

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MARO: Enabling Full MPI Automatic Refactoring in DSL-Based Programming Framework 24th

MARO: Enabling Full MPI Automatic Refactoring in DSL-Based ...

引用

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

作者： Lei, Tong Chen, Zongjing Che, Yonggang Xu, Chuanfu Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789819615445

Currently, the landscape of computer hardware architecture presents the characteristics of heterogeneity and diversity, prompting widespread attention to cross-platform portable parallel programming techniques. Most existing portable programming approaches adopt the "MPI+X" strategy, focusing mainly on node-level "X" parallelism, while inter-node parallelization still relies on manual MPI programming. OP2 is a domain-specific language-based portable parallel programming framework for unstructured mesh applications that supports the automatic generation of MPI parallel code. However, programmers must manually write pre-processing code during code refactoring, such as handling the mapping relationship between global and process-local variables and the initial distribution of process-local data. In this paper, we propose MARO (MPI Automatic Refactoring for OP2), an automatic refactoring method for generating pre-processing code targeting MPI code generation within the OP2 programming framework for unstructured mesh applications. This method automatically generates the pre-processing code required for MPI parallelism through the source-to-source translator, enabling OP2 to generate MPI parallel code without requiring users to write MPI-related code manually. We compare the automatically refactored OP2 applications using the proposed method with those manually refactored to validate its effectiveness. The proposed method enhances OP2’s automatic parallel code generation capability, enabling it to achieve fully automatic MPI parallelization. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Automatic programming

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Modal-Centric Insights Into Multimodal Federated Learning for Smart Healthcare: A Survey 24th

Modal-Centric Insights Into Multimodal Federated Learning fo...

引用

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

作者： Wang, Di Liu, Wenjian Gao, Longxiang Qu, Y. Neil. Zhang, Hu Shi, Jihong The Faculty of Data Science City University of Macau Macau China Jinan China Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China Medical Integration and Practice Center Shandong University Jinan China

ISBN: (纸本)9789819615476

Federated Learning (FL) has progressed, providing a distributed mechanism where data need not be consolidated, thereby enhancing the privacy and security of sensitive healthcare data. Recent advancements in multimodal machine learning have empowered the development of accurate and robust AI systems in the medical domain, especially within centralized database systems. Multimodal federated learning (MFL) combines federated learning’s distributed nature with the flexibility to work with various data types. This capability is particularly relevant in medical contexts, where healthcare data can range from electronic health records (EHR) to radiology imaging, genomic data, and wearable device information. The key advantage of MFL in medical settings is the ability to create robust models without centralizing sensitive patient information. However, there are no existent research to comprehensively review the application status of MFL in smart healthcare systems from the modal-centric aspect. Motivated by this, we explore the systematization of knowledge about multimodal federated learning on medical data, find the challenges of this area and related solutions. With this research, we hope to provide a systematical review of this under-explored domain and provide insights for forthcoming researchers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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A Cluster-Based Platoon Formation Scheme for Realistic Automated Vehicle Platooning 20th

A Cluster-Based Platoon Formation Scheme for Realistic Auto...

引用

20th IFIP WG 10.3 international conference on Network and parallel computing, NPC 2024

作者： Liu, Ziye Chen, Chen Zhang, Qizhong Wang, Zhiyi Choon Chang, Yoong Liu, Lei Pei, Qingqi Wan, Shaohua School of Telecommunications Engineering Xidian University Xi’an China State Grid Jilin Province Electric Power Company Limited Information Communication Company Changchun China Lee Kong Chian Faculty of Engineering & Science Universiti Tunku Abdul Rahman Kajang Bandar Sungai Long Malaysia Xidian Guangzhou Institute of Technology Xidian University Guangzhou China Xidian Hangzhou Institute of Technology Xidian University Hangzhou China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen China

ISBN: (纸本)9789819628292

In response to the burgeoning interest in Vehicle-to-Everything (V2X) communications and its pivotal role in enhancing road transportation efficiency and safety, this paper presents a novel scheme for the formation of vehicle platoons, addressing the critical need for realistic implementation strategies. Recognizing the limitations of existing research that often relies on idealized assumptions, this work proposes a platoon formation method utilizing the real-world dataset. The method combines the robustness of Random Forest algorithms for feature selection with the adaptability of Fuzzy K-Means (FKM) clustering to effectively group vehicles with similar characteristics into platoons. This approach ensures the consistency of speed and acceleration within platoons, a crucial aspect for maintaining platoon integrity and stability. Validated through the Kaggle dataset, the scheme not only showcases the feasibility of forming efficient vehicle platoons in realistic scenarios but also introduces a velocity and acceleration-based Cooperative Adaptive Cruise Control (CACC) strategy to prove the formatted platoon stability. © IFIP international Federation for Information Processing 2025.

关键词： K-means clustering

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Performance Evaluation of NLP Models for European Portuguese: Multi-GPU/Multi-node Configurations and Optimization Techniques 24th

Performance Evaluation of NLP Models for European Portugue...

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

作者： Santos, Daniel Miquelina, Nuno Schmidt, Daniela Quaresma, Paulo Nogueira, Vítor Beires VISTA Lab ALGORITMI Research Center University of Évora Évora Portugal

ISBN: (纸本)9789819615506

Natural Language Processing (NLP) research has predominantly focused on the English language, leading to a wealth of resources and advancements tailored to English. However, there is a growing need to extend these capabilities to other languages, such as European Portuguese, to ensure the inclusivity and accessibility of NLP technologies. In this study, we explore the evaluation of NLP models in the European Portuguese language using a multi-GPU/multi-node machine. We utilized various tools such as PyTorch, Accelerate, Transformers, and DeepSpeed with ZeRO Stage 3 to handle the computational demands of large-scale model training. We provide all the key aspects of our methodology to evaluate various models on translated GLUE tasks. Additionally, we introduce AiBERTa, a base model with 110 million parameters, developed and pre-trained on a corpus tailored for European Portuguese. This research highlights the effectiveness of advanced tools and distributed computing in scaling NLP model training, providing a foundation for future enhancements in European Portuguese language processing. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： distributed computer systems

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STB-GraCapsNet: A Novel Capsule Network Structure with Swin Transformer Block 25th

STB-GraCapsNet: A Novel Capsule Network Structure with Swin...

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

作者： Zhang, Chunying Dong, Ziao Wang, Liya Liu, Lu Ren, Jing Ma, Jiang Liu, Bin College of Science North China University of Science and Technology 21 Bohai Road Caofeidian Xincheng Hebei Tangshan063210 China Big data and Social Computing Research Center Hebei University of Science and Technology Hebei Shijiazhuang0500198 China

ISBN: (纸本)9789819642069

Capsule network is a new type of neural network encoding features into capsules and constructing the part-whole relationships, which demonstrated good performance in image classification. However, it has some issues such as weak feature extraction ability and large number of training parameters, leading to performance decline when processing images with complex background. To address these issues, this article proposes a novel capsule network structure called STB-GraCapsNet, with key improvements as follows: 1) It uses Swin Transformer Block with the shift window attention mechanism for data preprocessing to obtain richer features;2) the features are then processed through Linear Embedding and passed into the Primary Capsule Layer to generate high-dimension feature capsules, which reduces primary capsules number and improves feature extraction ability of the network. Ablation and comparative experiments based on multiple datasets show that STB-GraCapsNet performs better on complex datasets: 77.8% and 36.2% reduction in parameters number of capsule structure, and 12.07% and 5.22% improvement in model accuracy, as compared to CapsNet and GraCapsNet, respectively. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Signal encoding

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parallel Acceleration of Transportation Problem Solving Using SpMV in the Industrial Chain Context 25th

Parallel Acceleration of Transportation Problem Solving Usi...

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

作者： Dong, De Lin, Guanyu Xu, Yicheng Ma, Ruikang Xia, Chenliang Fan, Jianping Li, Fuchong Southern University of Science and Technology Guangdong Shenzhen China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China University of Chinese Academy of Sciences Beijing China Jinan Industrial Development Park Technology Development Co. Ltd. Shandong Jinan China

ISBN: (纸本)9789819642069

As modern industrial chains grow increasingly complex and time-sensitive, traditional transportation planning methods face efficiency bottlenecks. To address this, we propose a parallelization method based on Sparse Matrix-Vector Multiplication (SpMV) to accelerate the Transportation Simplex Algorithm (TSA) for large-scale transportation problems. Existing approaches primarily leverage data parallelism but underutilize GPU computational potential. This study transforms sequential algorithms into matrix-based representations, combining SpMV and parallel graph algorithms to enhance TSA performance. Key contributions include mapping performance bottlenecks—potential vector calculation and closed-loop search—onto SpMV operations, and converting branch logic into matrix operations to reduce divergence. Experiments on a 10000×10000 dataset demonstrate a 20.8x speedup for the parallelized MODI algorithm and a 28x overall speedup for solving the Transportation Problem, significantly improving efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Graph algorithms

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Advances on P2P, parallel, grid, Cloud and Internet computing: Proceedings of the 11th international conference 1

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丛书名： Lecture Notes on Data Engineering and Communication Technologies 1

2016年

作者： Fatos Xhafa, Leonard Barolli, Flora Amato (eds.)

ISBN: (纸本)3319491083;9783319491080

P2P, grid, Cloud and Internet computing technologies have been very fast established as breakthrough paradigms for solving complex problems by enabling aggregation and sharing of an increasing variety of distributed computational resources at large scale. The aim of this volume is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to P2P, grid, Cloud and Internet computing as well as to reveal synergies among such large scale computing paradigms. This proceedings volume presents the results of the 11th international conference on P2P, parallel, grid, Cloud And Internet computing (3PGCIC-2016), held November 5-7, 2016, at Soonchunhyang University, Asan, Korea

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Job Scheduler-Driven Power Gateway for High Performance computing

Job Scheduler-Driven Power Gateway for High Performance Comp...

引用

ISC High Performance 2025 Research Paper Proceedings (40th international conference)

作者： Matthew Sgambati Matthew Anderson Idaho National Laboratory Idaho USA

ISBN: (数字)9783982633619

Power gateways in the form of a microgrid can incorporate multiple distributed energy resources (DER) in either grid forming or grid following mode and support high performance computing (HPC) power profiles including the large load-follow requirements observed in multi-user HPC systems. The microgrid's flexibility to operate in either grid forming or grid following mode and to actively switch between these modes enables baseline power from multiple non-baseline DER while maintaining high power quality metrics for the HPC system. But this enormous flexibility in demand response and time of use shifting is generally programmed independently of any integration with an HPC job scheduler, which can better inform the load shaping by the microgrid. While there are many existing approaches where the HPC job scheduler takes in information from the grid to make queue scheduling decisions, this work takes the opposite view and explores three strategies where the forecast of jobs in the queue can change the settings of the grid. Three strategies are tested where the forecast of jobs in the queue adjusts the settings of a microgrid designed for a datacenter, in this case with three classes of HPC architectures. The strategies are demonstrated using a microgrid with 64 kW of solar capacity and 320 kWh of battery over a period of 21 days operating with significant load-follow swings, a throttled grid, cloudy conditions, switching between grid following and grid forming modes, and a wide range of battery states-of-charge, all while maintaining high quality power metrics. The strategies presented provide a mechanism for the forecast of jobs in the queue to influence and adjust the settings of a microgrid and to improve HPC power outcomes such as maximizing renewable energy usage.

关键词： Measurement Renewable energy sources High performance computing Microgrids Switches Logic gates distributed power generation Batteries Time factors grid forming

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Research on Cable Vibration Measurement System Based on Michelson Interference Principle 1

Research on Cable Vibration Measurement System Based on Mich...

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1st international conference on Intelligent Manufacturing and Cloud computing, ICIMCC 2024

作者： Kou, Hanpeng Bu, Tianlong Zhang, Dapei Nie, Dayu Feng, Zhenghua Huang, Kaiyang Mengdong Power Grid Company Hohhot120022 China Changchun University of Science and Technology Changchun130022 China

ISBN: (纸本)9781643685779

Extra-high voltage transmission lines and cables are subject to irregular vibration due to icing or unusual weather conditions, which is potentially hazardous to the safety of the towers and the structural strength of the wires. Most of the current monitoring methods use electronic acceleration sensors, which have low sensitivity, poor signal-to-noise ratio, troublesome installation process, need for additional power supply and other issues. distributed fibre optic vibration demodulation method is currently more advanced sensing technology, can achieve long distance, large scale, multi-dimensional online monitoring and structural safety warning. The laser fibre sensing distributed Michaelson coherent technology is used to develop a cable vibrate sensor, which can achieve the vibrate monitoring of cables and towers. The sensor consists of an elastic thin-walled cylinder, a mass ring, a fixed ring, and a sensing fibre, which uses a highly sensitive fine optical fibre and a coupler to build a laser-fibre Michelson coherent optical path, which is very sensitive to vibration signals, and encapsulates the interferometer into a specific metal casing to achieve the encapsulation and integration of the vibrate monitoring sensor. The optical system of this laser fibre sensor has the advantages of high sensitivity and high signal-to-noise ratio. Using the differential cross-multiplication demodulation algorithm for many experiments and results analysis, the demodulation output of the linear correlation coefficient of up to 0.95 in the frequency of 10Hz ~ 200Hz under the conditions of the vibrate, suitable for high-voltage towers and cables for online monitoring of the vibrate. © 2025 The Authors.

关键词： Optical fibers

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Optimizing Transitive Closure Computation for High Performance computing and Security

Optimizing Transitive Closure Computation for High Performan...

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Euromicro conference on parallel, distributed and Network-Based Processing

作者： Elio Masciari Enea Vincenzo Napolitano DIETI University of Naples Federico II Naples Italy

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Transitive closure computation is a fundamental operation in graph theory with applications in various domains. However, the increasing size and complexity of real-world graphs make traditional algorithms inefficient, especially when dealing with large datasets. This paper investigates the optimisation of transitive closure algorithms for high performance computing (HPC) applications. We implement and compare three different methods for computing the adjacency matrix of the transitive closure, based on three different Python libraries (NetworkX, PyTorch and NumPy). Our approach is benchmarked on seven real-world datasets of varying size and density to evaluate performance and scalability. The results show that NumPy achieves the best performance for large and dense graphs. The paper concludes with a discussion of the potential benefits of algorithmic optimization in HPC and security.

关键词： Heuristic algorithms High performance computing Scalability Memory management Data structures Real-time systems Computational efficiency Security Sparse matrices Optimization

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