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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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CNS Lock: Compact NUMA-aware Lock with a Standard Interface

CNS Lock: Compact NUMA-aware Lock with a Standard Interface

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Brahmaiah Gandham Praveen Alapati École Centrale School of Engineering Mahindra University Hyderabad India

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

In recent years, multi-core systems with NonUniform Memory Access (NUMA) architectures are becoming prevalent. Multithreaded applications that execute on NUMA architectures play a pivotal role in getting better performance. The difficulties associated with multi-threaded applications are more pronounced because of compatibility issues with synchronization objects and the underlying NUMA architectures. Locks are fundamental synchronization primitives to avoid data races and achieve high performance in multi-core systems. With the increasing performance demands, locks have been refined and optimized with the architectural features of the NUMA systems. This paper proposes a novel synchronization object, namely CNS Lock (Compact NUMA-aware lock with a Standard interface) for NUMA systems. The CNS lock utilizes a single queue irrespective of the number of NUMA nodes and minimizes the number of atomic operations required for lock acquisition and release by prioritizing threads based on their NUMA node affinity. It considers the current thread’s NUMA node number to get the efficiency of a NUMA-aware design. CNS lock provides a standard interface to facilitate seamless integration into existing applications without knowing the internals. The CNS Lock strategically optimizes lock handovers and minimizes memory latency by employing a unified queue system across NUMA nodes. Our experimental results show that the CNS lock significantly outperforms the state-of-the-art locking mechanisms and makes it one of the essential tools of systems with NUMA architectures for better synchronization.

关键词： Multicore processing Instruction sets Memory architecture Handover Synchronization Spinning Resource management Standards

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PA-Star2: Fast Optimal Multiple Sequence Alignment for Asymmetric Multicore Processors

PA-Star2: Fast Optimal Multiple Sequence Alignment for Asymm...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Daniel Sundfeld George Teodoro Alba C. M. A. Melo Faculty of Science & Tech. in Engineering University of Brasilia (UnB) Brasilia Brazil Department of Computer Science Federal University of Minas Gerais (UFMG) Belo Horizonte Brazil Department of Computer Science University of Brasilia (UnB) Brasilia Brazil

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Multiple Sequence Alignment (MSA) is an important operation in Bioinformatics, used to simultaneously compare 3 or more sequences. The MSA problem was proven NP-Hard, so strategies have been proposed to reduce the search space and solve it in parallel. Recently, asymmetric multicore processors (AMPs) have become popular, with performance and energy-efficient cores, like the P-Cores and E-cores from Intel. However, parallel MSA applications have complex access patterns and adapting them for AMPs can be challenging. In this paper, we propose PA-Star2 1 , an asymmetric-aware strategy based on A-Star, which computes optimal MSAs taking asymmetry into account when distributing the search space among threads. Our experimental results show that the proposed optimizations can reduce considerably the average execution time of PA-Star2 achieving a speedup of up to 7.70×. We also show that the asymmetric-aware strategy can reduce the average execution time for one of the hardest sequences set from the BAliBASE benchmark, when compared to the symmetric counterpart. Finally, we show that our approach is energy-efficient. 1 1PA-Star2 is open source and the code is publicly available at1PA-Star2 is open source and the code is publicly available at https://***/danielsundfeld/astar_msa

关键词： Codes Multicore processing Instruction sets Benchmark testing Search problems Energy efficiency Bioinformatics Optimization

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Programming and Mapping for Mixed Heterogeneous Devices: The Case of Optical Flow

Programming and Mapping for Mixed Heterogeneous Devices: The...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Sergio Alonso Pascual Arturo Gonzalez-Escribano Departamento de Informática Universidad de Valladolid. ETSII Valladolid Spain

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Current parallel systems are increasingly heterogeneous, mixing devices of different types and computing capabilities. Exploiting multiple different devices for the same application continues to be a challenge that ranges from technical problems related to synchronizing and communicating diverse devices to problems of load distribution and flexibility to adjust the computation to the platform resources. In this work, we study the problem of using and extending a heterogeneous portability layer to program and adapt HSOpticalFlow to heterogeneous platforms. HSOpticalFlow is a streaming application to estimate the apparent movement of objects in a sequence of images. It is a simple but characteristic example of the structure of applications based on multilevel ILS (Iterative Loop Stencil), also known as multi-grid methods, applied to a sequence of inputs. Starting from the original CUDA reference code, we present a methodology and programming techniques based on the Controller programming model to implement it as a pipeline among multiple devices. We discuss a technique to determine a proper work partition and mapping for a set of devices. This allows for building very efficient parallel solutions, using similar devices or taking advantage of devices with lower computing power, to reduce the load and increase the productivity of more powerful ones. We present the results of an experimental study using several GPUs of different vendors, architectures, and generations, showing that this solution allows combinations of devices to be efficiently exploited to improve performance. Specifically, the results include speedups of 1.91x using two NVIDIA A100 GPUs and 1.21x using one NVIDIA V100 GPU and one AMD WX9100 GPU, which is about $3 x$ slower than the NVIDIA GPU for this application.

关键词： Productivity Performance evaluation Computational modeling Pipelines Graphics processing units Computer architecture Programming Streaming media Optical flow Tuning

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Contributions to Accelerating a Numerical Simulation of Free Flow parallel to a Porous Plane

Contributions to Accelerating a Numerical Simulation of Free...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Claudio Schepke Roberta A. Spigolon José Rufino Cesar F. Da C. Cristaldo Glener L. Pizzolato Laboratory of Advances Studies in Computation (LEA) Federal University of Pampa (UNIPAMPA) Alegrete Brazil Research Centre in Digitalization and Intelligent Robotics (CeDRI) Laboratório Associado para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC) Instituto Politécnico de Bragancá Bragança Portugal Laboratory of Computational Fluid Dynamics and Atmospheric Turbulence (LFCTA) Federal University of Pampa (UNIPAMPA) Alegrete Brazil

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Flow models over flat porous surfaces have applications in natural processes, such as material, food, chemical processing, or mountain mudflow simulations. The development of simplified analytical or numerical models can predict characteristics such as velocity, pressure, deviation length, and even temperature of such flows for geophysical and engineering purposes. In this context, there is considerable interest in theoretical and experimental models. Mathematical models to represent such phenomena for fluid mechanics have continuously been developed and implemented. Given this, we propose a mathematical and simulation model to describe a free-flowing flow parallel to a porous material and its transition zone. The objective of the application is to analyze the influence of the porous matrix on the flow under different matrix properties. We implement a Computational Fluid Dynamics scheme using the Finite Volume Method to simulate and calculate the numerical solutions for case studies. However, computational applications of this type demand high performance, requiring parallel execution techniques. Due to this, it is necessary to modify the sequential version of the code. So, we propose a methodology describing the steps required to adapt and improve the code. This approach decreases 5.3% the execution time of the sequential version of the code. Next, we adopt OpenMP for parallel versions and instantiate parallel code flows and executions on multi-core. We get a speedup of 10.4 by using 12 threads. The paper provides simulations that offer the correct understanding, modeling, and construction of abrupt transitions between free flow and porous media. The process presented here could expand to the simulations of other porous media problems. Furthermore, customized simulations require little processing time, thanks to parallel processing.

关键词： Codes Temperature Computational modeling Computational fluid dynamics Media parallel processing Numerical simulation Mathematical models Numerical models Surface treatment

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A Multi-holder Role and Strange Attractor-Based Data Possession Proof in Medical Clouds 24th

A Multi-holder Role and Strange Attractor-Based Data Possess...

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

作者： Guo, Jinyuan Sun, Lijuan Wu, Jingchen Chu, Chiawei Gao, Yutong Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing China School of Cybersecurity Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance Ministry of Education Minzu University Beijing China Intellectual Property Information Service Center BHU Beihang University Beijing China City University of Macau Taipa China Li’an International Education Innovation Pilot Zone Hainan International College of Minzu University of China Hainan Beijing China

ISBN: (纸本)9789819615278

Proof of Data Possession is a technique for ensuring the integrity of data stored in cloud storage. However, most audit schemes assume only one role for data owners, which is not suitable for complex Smart Healthcare Network with multiple roles. In such schemes addressing the risk of third-party auditors (TPA) colluding with other entities, blockchain is typically employed. However, this necessitates extensive computation, resulting in unacceptably high energy consumption and prolonged verification times. In this paper, we propose a Proof of Data Possession scheme tailored for medical network environments, which incorporates protocols designed for both healthcare professionals and patients, considering the diverse roles that generate data within medical network applications and the varying performance of the devices they use. During the generation of metadata for verification, the protocol incorporates the varying security risk levels associated with medical data. For subsequent metadata selection, an audit block extraction strategy based on strange attractors is employed, effectively mitigating the risk of collusion by third-party TPA, thereby enhancing the security and efficiency of the scheme. Additionally, we conducted experimental analysis and comparisons, demonstrating higher security and practical applicability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data integrity

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Optimizing the pollution routing problem with CUDA accelerated discrete particle swarm optimization algorithm

Optimizing the pollution routing problem with CUDA accelerat...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Donald Davendra Magdalena Metlicka Computer Science Department Central Washington University Ellensburg USA R&D Division URC Systems s.r.o. Brno Czech Republic

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

A major contributor to global greenhouse gas (GHG) emission is the transportation sector, where vehicle load, fuel type and speed, amongst others, are key factors. The pollution routing problem (PRP) is an extension of the capacitated vehicle routing problem (CVRP), whose objective is to model the greenhouse emission. This paper looks at the evaluation of the PRP problem using discrete particle swarm optimization algorithm (DPSO) for CUDA platform. The DPSO algorithm, while very powerful, generally suffers from long execution time due to its inherent metaheuristic structure. This makes solving large and scalable applications time prohibitive. This novel approach utilizing GPGPU programming, looks at the low-level optimization of the DPSO algorithm in the CUDA framework. Thread and memory hierarchy are optimized to be scalable and efficient. Intelligent memory synchronization is implemented to reduce data communication overhead. The emission is selected as the optimization target, as it offers insight on the economies of environmental-friendly vehicle routing. This algorithm is tested on the benchmark data set based on real world data from UK and compared against the non-parallel variant. The results obtained show that the algorithm is very competitive and scalable, thus extending its usage in large scale transportation sector application.

关键词： Pollution Vehicle routing Graphics processing units Transportation Programming Benchmark testing Routing Synchronization Particle swarm optimization Standards

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Natural Language processing in Geographic Information Systems

Natural Language Processing in Geographic Information System...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： Kushmitha S. Jaspher W. Kathrine Abisha M. B. Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

The integration of Geographic Information Systems (GIS) with Natural Language processing (NLP) has transformed how spatial data is accessed and utilized. By enabling GIS interfaces to interpret natural language queries, NLP enhances user experience, democratizes geospatial data, and improves query accuracy. This paper reviews state-of-the-art methodologies for geo-parsing, geo-coding, and spatial query interpretation, addressing challenges like geographic ambiguity, imprecise spatial relationships, and scalability limitations. Key contributions include a systematic literature review identifying research gaps such as insufficient contextawareness and a lack of annotated datasets, alongside case studies demonstrating the benefits of NLP integration in applications like disaster management and urban planning. Future opportunities are explored in leveraging deep learning, multimodal data integration, and adaptive user interfaces to further enhance GIS accessibility and usability. Future opportunities are explored in leveraging deep learning for spatial reasoning, integrating multimodal data sources for enhanced decision-making, and developing adaptive user interfaces tailored for diverse audiences. Furthermore, the paper highlights the potential of NLP in generating geodescriptions for distributed sensor networks, supporting accessibility for impaired users, and enhancing real-time data analysis in smart city initiatives. Addressing these gaps and building scalable frameworks will pave the way for GIS systems that are not only powerful but also inclusive, fostering global accessibility and broader adoption of geospatial technologies.

关键词： Deep learning Visualization Scalability Urban planning Disaster management User interfaces Natural language processing Spatial databases Geospatial analysis Usability

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Mitigating Security Challenges in Edge Computing: Attacks, Defence Strategies, and Algorithms

Mitigating Security Challenges in Edge Computing: Attacks, D...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： Venkata Durga Rao Matta V.V.R. Maheswara Rao Venkata Sai Jayasurya Battula Mahesh Babu Addagatla Computer Science and Engineering Department Vishnu Institute of Technology Bhimavaram Andhra Pradesh India Computer Science and Engineering Department Shri Vishnu Engineering College for Women Bhimavaram Andhra Pradesh India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

Edge computing has emerged as a crucial paradigm to fulfill the increasing demand for rapid data processing, low latency, and efficient resource utilization, particularly in applications such as the Internet of Things (IoT), smart cities, autonomous vehicles, and automated industrial systems. By processing data closer to its source, edge computing minimizes reliance on centralized cloud infrastructures, thereby improving response times and optimizing bandwidth. However, this transition also presents significant security challenges, including heightened risks of distributed Denial of Service (DDoS) attacks, data breaches, and unauthorized physical access to edge nodes. This paper conducts a comprehensive analysis of these security vulnerabilities, presenting a framework that integrates advanced defence mechanisms and algorithms tailored to enhance data protection and resource management in edge environments. Our findings indicate that the proposed strategies effectively mitigate identified threats while maintaining system performance. Furthermore, we outline ongoing challenges related to scalability, interoperability, and data governance, providing insights into future research avenues aimed at fortifying edge computing systems against evolving security threats. This study contributes to a deeper understanding of the critical role edge computing plays in the domain of next-generation computing technologies.

关键词： Technological innovation Scalability Data processing Real-time systems Security Resource management Internet of Things Interoperability Next generation networking Edge computing

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Real-Time Analytics for Big Data in Smart City applications: Transforming Urban Environments with Data-Driven Insights

Real-Time Analytics for Big Data in Smart City Applications:...

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3rd IEEE international conference on Automation and Computation, AUTOCOM 2025

作者： Khanderi, Avinash Rajaram, Gnanajeyaraman Hussein, Ramy Riad Johri, Prashant Mohanraj, T. Balamurugan, M. Walmart Inc. BentonvilleAR United States Simats Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Cse Chennai India College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq School of Computing Science and Engineering Galgotias University Greater Noida India Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore India Excel Engineering College Department of Eee Komarapalayam India

ISBN: (纸本)9798331542375

This paper offers an overview of real-time analytics for smart cities proposing a framework for real-time data processing to improve the urban landscape. In the proposed system, large-scale data-streams can be processed using advanced machine learning algorithms, edge computing, and distributed data storage. Analyzing the outcomes of the evaluation procedure evidences reportable performance enhancements in the areas of smart city applications. Average traffic speed in transportation systems in the same period rose by 60%, concurrency and response to incidents likewise cut down by 40% and 53% respectively. The energy management systems responded with a 16% decrease in maximum energy load and the waste reduction was by 50%, while the costs savings was by 25% increase. Public safety applications alone realised a 60% decrease in the time taken to detect a crime and a 28.6% increase in efficiency on disaster resources with an overall spike in public satisfaction of 25.7%. Such findings improve the understanding of how this framework can increase urban efficiency, sustainability, and quality of life, which makes the solution usable in future smart city projects. © 2025 IEEE.

关键词： Urban transportation

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