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检索条件"任意字段=International Conference on Parallel and Distributed Processing Techniques and Applications"

共 11287 条记录，以下是31-40 订阅

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distributed k-Hop Query Powered by an Asynchronous Framework 25th

Distributed k-Hop Query Powered by an Asynchronous Framewo...

引用

25th international conference on Web Information Systems Engineering, WISE 2024

作者： Zheng, Jinlong Lu, Yujie Zheng, Weiguo School of Data Science Fudan University Shanghai China

ISBN: (纸本)9789819605781

The k-hop query represents a fundamental challenge in various graph applications, often supported by numerous distributed systems. The conventional approach to this query paradigm typically involves iterative layer-by-layer expansion, which inevitably increases redundant vertices as the hop count grows. Moreover, issues such as master node idle waiting and workload imbalances across computing nodes contribute to the wastage of computational resources and time. To tackle these challenges, this paper introduces an asynchronous framework for k-hop queries, namely ADFQ, designed for seamless integration into any distributed system. Diverging from the traditional vertex-centric techniques, this framework employs distributed machines to store graph blocks and process queries without waiting during deduplication between hops. By ensuring comprehensive deduplication at each hop’s conclusion and efficiently expanding frontiers, the framework significantly improves query performance. Experimental results demonstrate superior performance compared to the classic Bulk Synchronous parallel paradigm, particularly as graph imbalances intensify. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Structured Query Language

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Fast Maximal Independent Sets on Dynamic Graphs

Fast Maximal Independent Sets on Dynamic Graphs

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Prajjwal Nijhara Aditya Trivedi Dip Sankar Banerjee Department of Computer Science and Engineering Indian Institute of Technology Jodhpur NH62 Karwar Jodhpur Rajasthan India

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Finding the Maximal Independent Set (MIS) in a graph is a well-known problem with applications in resource allocation, load balancing, and routing optimization. This task is particularly challenging for large graphs as it requires multiple iterations over the entire set of vertices. Recently, there has been significant interest in developing techniques to maintain the MIS dynamically in evolving graphs rather than re-computing from scratch. In this paper, we propose new data structures and techniques for computing MIS in parallel on dynamic graphs. We specifically propose techniques to handle insertions and deletions in a batched setting. We conducted detailed experiments on shared memory multicore CPUs using graphs ranging from 50 million to ${1. 2}$ billion edges. Our results show that using our technique for insertions and deletions can provide up to 15.64x and 10.57x speedups on average over comparable baselines. Additionally, the final MIS we produce varies by only about ${0. 1 8 \%}$ in cardinality compared to the existing state-of-the-art.

关键词： Multicore processing Scalability Graphics processing units Routing Load management Data structures Real-time systems Distance measurement Resource management Optimization

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A Multi-Level parallel Algorithm for Detection of Single Scatterers in SAR Tomography

A Multi-Level Parallel Algorithm for Detection of Single Sca...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Massimiliano Russo Mehwish Nisar Antonio Pauciullo Pasquale Imperatore Marco Lapegna Diego Romano Dept. of Mathematics and Applications University of Naples Federico II Naples Italy Institute for the Electromagnetic Sensing of the Environment (IREA) National Research Council Naples Italy Inst. for High Performance Computing and Networking National Research Council Naples Italy

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Synthetic Aperture Radar (SAR) tomography is an advanced technique for monitoring deformations of the Earth’s surface. However, the computational complexity of SAR tomography algorithms often restricts their application to large-scale datasets. To address this issue, we introduce a multi-level parallel implementation of a single scatterer detection algorithm specifically designed to exploit the capabilities of modern heterogeneous High-Performance Computing (HPC) systems. By efficiently distributing the computational workload at different levels across multiple processing units, our parallel approach significantly reduces processing time, facilitating the analysis of extensive SAR datasets. We assess the performance of our parallel implementation using real-world SAR data, showcasing its effectiveness in enhancing both the efficiency and scalability of SAR tomography. Our work contributes to advancing remote sensing techniques and offers valuable insights into the application of HPC for large-scale environmental monitoring.

关键词： High performance computing Scalability Graphics processing units Tomography Performance analysis parallel algorithms Synthetic aperture radar Surface treatment Remote sensing Optimization

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Low-Carbon Geographically distributed Cloud-Edge Task Scheduling 24th

Low-Carbon Geographically Distributed Cloud-Edge Task Schedu...

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

作者： Zhu, Yingjie Qi, Ji Wang, Zehao Wei, Shengjie Chen, Yan Cao, Tuo Luo, Gangyi Qian, Zhuzhong State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Software Technology Co. Ltd. Jiangsu Suzhou China

ISBN: (纸本)9789819615506

Edge computing is a rapidly developing research area known for its ability to reduce latency and improve energy efficiency, and it also has a potential for green computing. Many geographically distributed edge servers are powered by renewable energy sources, due to the difficulties of using traditional power supplies or because of advancements in energy harvesting technologies. These green edge servers can cut down carbon emissions by processing tasks locally, but the inherent limitations of their computing capacity result in some tasks having to be uploaded to a data center to meet service-level agreement (SLA) requirements. To further reduce carbon emissions in cloud-edge systems, scheduling tasks to those low-carbon data centers while meeting latency constraints is highly beneficial. In this paper, we propose a low-carbon cloud-edge scheduling algorithm that utilizes Lyapunov optimization techniques and Markov approximation to address the long-term optimization problem of carbon emissions. Our algorithm guarantees provable performance, and simulation results demonstrate its effectiveness in striking a balance between carbon emissions and task latency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Carbon sequestration

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Containerized Data-Flow processing for Scalable Real-Time Analytics on Edge Devices 25th

Containerized Data-Flow Processing for Scalable Real-Time A...

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25th international conference on parallel and distributed Computing, applications and Technologies, PDCAT 2024

作者： HoseinyFarahabady, MohammadReza Y. Zomaya, Albert School of Computer Science Center for Distributed and High Performance Computing The University of Sydney SydneyNSW2006 Australia

ISBN: (纸本)9789819642069

The increasing demand for real-time data analysis in Internet of Things (IoT) ecosystems has created several challenges, particularly in environments where resources are limited, and minimizing data processing latency is critical. This paper investigates the use of Linux Containerization (LXC) as a lightweight, resource-efficient alternative to traditional virtual machine managers for accelerating data-flow processing applications. We propose an architecture that integrates Linux Containerization (LXC) with a Proportional-Integral-Derivative (PID) controller to dynamically manage I/O resource allocation, ensuring Quality of Service (QoS) for I/O-intensive data analytics workloads. The proposed PID controller continuously monitors system performance and dynamically adjusts I/O resource allocation to mitigate performance degradation. Through a series of experiments, we demonstrate that LXC-based solutions outperform traditional methods in managing I/O-intensive data analytics workloads in IoT and edge ecosystems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Quality of service

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parallel Execution Strategies for Cellular Automata on Shared Memory Architectures

Parallel Execution Strategies for Cellular Automata on Share...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Andrea Giordano Alessio De Rango Giuseppe Mendicino Donato D’Ambrosio Davide Macrì Luigi Rizzo Rocco Rongo William Spataro ICAR-CNR Rende Italy Department of Environmental Engineering University of Calabria Italy Department of Mathematics and Computer Science University of Calabria Italy

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Cellular Automata (CA) are extensively utilized for modeling and simulating complex systems due to their simplicity, flexibility, and ability to represent diverse phenomena. However, the computational intensity of CA models, particularly in large-scale applications, demands the development of efficient parallel execution techniques. This is especially critical when targeting shared memory architectures, where resource management and thread coordination play pivotal roles in achieving optimal performance. In this study, we examine a range of parallel execution strategies specifically designed to enhance the efficiency and scalability of CA models. The experimental evaluation highlights good scalability in execution time and resource utilization, making these strategies highly suitable for extensive simulations across various domains. Additionally, the results emphasize that imbalance conditions—often arising during CA computations—can considerably influence the effectiveness of choosing a given strategy.

关键词： Computational modeling Scalability Instruction sets Memory architecture Automata parallel processing Resource management Synchronization Optimization Load modeling

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A Comparative Evaluation of Zero Knowledge Proof techniques

A Comparative Evaluation of Zero Knowledge Proof Techniques

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10th international conference on Internet of Things, Big Data and Security, IoTBDS 2025

作者： Rostamkolaei Motlagh, Seyed Mohsen Pahl, Claus Barzegar, Hamid R. El Ioini, Nabil Free University of Bozen-Bolzano Bolzano39100 Italy University of Nottingham Semenyih43500 Malaysia

ISBN: (纸本)9789897587504

Common to many distributed systems such as the Internet-of-Things (IoT) is decentralisation, often with a growing number of devices with diverse computational capabilities and security requirements. If integrated into critical applications, ensuring secure communication and data integrity is critical. In particular, privacy and security concerns are growing with the rise of these architectures. Zero-Knowledge Proof (ZKP) techniques are solutions to improve security without compromising on privacy. While the advantages of ZKP techniques are well-documented, it is important to consider the inherent limitations of these distributed environments, such as restricted processing power, memory capacity, and energy constraints, when aiming to solve security concerns. Here, we select two prominent ZKP techniques, Bulletproof and zk-STARK, and experimentally compare a number of their variants for a set of architecture-specific assessment criteria. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： parallel processing systems

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Fault-Tolerant Architectures for distributed Big Data Analytics 1

Fault-Tolerant Architectures for Distributed Big Data Analyt...

引用

1st international conference on Advances in Computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Sudhakaran, Sunil Shah, Samarth Mishra, Manas Kumar Natarajan, Vignesh Bhatt, Jay Goel, Om Mahatma Gandhi University Kerala Kottayam India University at Albany AlbanyNY12222 United States G.L. Bajaj Institute of Technology and Management Department of Computer Science and Engineering Greater Noida201306 India Arizona State University AZ United States Northeastem University BostonMA United States ABES Engineering College U.P. Ghaziabad India

ISBN: (纸本)9798331518578

It has created challenges in the processing of data and analysis, which need to go beyond the traditional centralized architecture to solve the current data volume, speed, and types. To address these challenges, fault-tolerant architectures have become one of the keys to meeting the needs of distributed big data analytics. Failure is a normal part of systems;these architectures are meant to accommodate failures of individual components so that the entire system does not need to stop working or, worse, give false results. They make use of several nodes to operate and retain data in a distributed fashion, which supplies excessive scalability and fault tolerance. This means that even if some nodes fail, a fault-tolerant architecture can still provide redundancy by replicating data across many nodes, giving the system redundancy. Fault-tolerant architectures also utilize efficient data processing techniques like partitioning and data parallel processing, to achieve high performance. This allows real-time and near-real-time analysis of streaming data. © 2025 IEEE.

关键词： Data Analytics

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Concurrent FFT Execution on GPUs in Real-Time

Concurrent FFT Execution on GPUs in Real-Time

引用

Euromicro conference on parallel, distributed and Network-Based processing

作者： Syed W. Ali Joseph Goh Joshua Bakita Samarjit Chakraborty James H. Anderson Department of Computer Science University of North Carolina at Chapel Hill

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Fourier transforms are vital for a broad range of signal-processing applications. Accelerating FFTs with GPUs offers an orders-of-magnitude improvement vs. CPU-only FFT computation. However, two problems arise when executing FFT tasks with other GPU work. First, concurrent GPU use introduces unpredictability in the form of lengthy response times. Second, it is unclear how to best parameterize and schedule FFT tasks to meet the throughput and timeliness constraints of real-time signal processing. This work investigates how FFT and other GPU-using tasks can concurrently access a GPU while maintaining bounded response-time guarantees without sacrificing throughput. In our experiments, the techniques proposed by this work result in an up to 17% improvement in worst-case FFT response times.

关键词： Schedules Accuracy Fast Fourier transforms Graphics processing units Signal processing Throughput Real-time systems Hardware Sensors Time factors

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A Preliminary Study on Performance Modeling at Scale for Geophysical applications

A Preliminary Study on Performance Modeling at Scale for Geo...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Fabrice Dupros Sylvain Jubertie Hideo Aochi Intel Corporation Paris France Brgm Orléans France

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Modeling the performance of real-world applications at scale is essential for designing next-generation platforms and shaping the development of future algorithms. However, accurately capturing the complexity of application execution graphs and their interaction with large-scale hardware environments remains a significant challenge. In recent years, several frameworks have been developed to tackle this issue by providing tools to simulate and analyze complex workloads on distributed systems. This paper focuses on seismic wave propagation problems as a representative use case to explore the challenges of modeling at scale. We employ the SimGrid simulation toolkit, a versatile framework for simulating distributed systems, to analyze the performance of large-scale applications. Particular emphasis is placed on the role of critical networking characteristics, such as bandwidth and topology, in influencing overall scalability and performance.

关键词： Network topology Scalability Bandwidth Hardware Topology Complexity theory Seismic waves Next generation networking

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