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16th international conference on Ambient Systems, Networks and Technologies Networks, ANT 2025 / 8th international conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Shahin, Mahtab Rahimpour, Saeed Ghasempouri, Tara Bauk, Sanja Fahringer, Thomas Draheim, Dirk Estonian Maritime Academy Tallinn University of Technology Tallinn Estonia Department of Computer Systems Tallinn University of Technology Tallinn Estonia Distributed and Parallel Systems Group University of Innsbruck Tirol Austria Information Systems Group Tallinn University of Technology Tallinn Estonia

This paper presents an optimized implementation of the Apriori algorithm tailored for large-scale data mining in cloud-native, serverless environments, utilizing real-world fuel datasets. Our approach achieves a 28% reduction in execution time and a 22% decrease in memory consumption compared to traditional distributed Apriori methods. The study leverages high-dimensional fuel datasets, spanning from 2020 to 2050, to evaluate scalability and efficiency in processing energy-related data. By employing advanced synchronization and deferred partitioning strategies, communication overhead is significantly reduced, improving performance while effectively balancing computational loads across distributed nodes. Security measures, including AES-256 encryption and role-based access control (RBAC), are incorporated to safeguard data confidentiality and ensure compliance with regulatory frameworks. The proposed solution scales efficiently for datasets up to 1 million records, demonstrating applicability across domains such as transportation and logistics. Future work will explore adaptive partitioning techniques, hybrid cloud architectures, and AI-driven predictive analytics to further enhance scalability and operational efficiency in serverless multi-cloud systems. © 2025 Elsevier B.V.. All rights reserved.

关键词： Apriori Algorithm Big Data Cloud-Native Architectures Data Mining distributed Computing Maritime Serverless Computing

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24th international conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2024

24th International Conference on Embedded Computer Systems: ...

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24th international conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2024

ISBN: (纸本)9783031783760

The proceedings contain 38 papers. The special focus in this conference is on Embedded Computer Systems: Architectures, Modeling, and Simulation. The topics include: QCEDA: Using Quantum Computers for EDA;Real-Time Linux on RISC-V: Long-Term Performance Analysis of PREEMPT_RT Patches;RV-VP2: Unlocking the Potential of RISC-V Packed-SIMD for Embedded processing;A Novel System Simulation Framework for HBM2 FPGA Platforms;ONNX-To-Hardware Design Flow for Adaptive Neural-Network Inference on FPGAs;efficient Post-training Augmentation for Adaptive Inference in Heterogeneous and distributed IoT Environments;pooling On-the-Go for NoC-Based Convolutional Neural Network Accelerator;Vitamin-V: Serverless Cloud Computing Porting on RISC-V;Design and Implementation of an Open Source OpenGL SC 2.0.1 Installable Client Driver and Offline Compiler;Plan Your Defense: A Comparative Analysis of Leakage Detection Methods on RISC-V Cores;iVault: Architectural Code Concealing techniques to Protect Cryptographic Keys;I2DS: FPGA-Based Deep Learning Industrial Intrusion Detection System;ACRA: A Cutting-Edge Analytics Platform for Advanced Real-Time Corruption Risk Assessment and Investigation Prioritization;post Quantum Cryptography Research Lines in the Italian Center for Security and Rights in Cyberspace;advancing Future 5G/B5G Systems: The Int5Gent Approach;RISC-V Accelerators, Enablement and applications for Automotive and Smart Home in the ISOLDE Project;PMDI: An AI-Enabled Ecosystem for Cooperative Urban Mobility;Open Source Software Randomisation Framework for Probabilistic WCET Prediction on Multicore CPUs, GPUs and Accelerators;a Hypervisor Based Platform for the Development and Verification of Reliable Software applications.

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24th international conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2024

24th International Conference on Embedded Computer Systems: ...

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24th international conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2024

ISBN: (纸本)9783031783791

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Edge AI in 6G: Vision, Technologies, and applications

Edge AI in 6G: Vision, Technologies, and Applications

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2025 international conference on Pervasive Computational Technologies, ICPCT 2025

作者： Centeno, Vanessa Azucena Monzon Caballero, Jesus Emilio Agustin Padilla Garcia, Claudia Rossana Poma Flores, Jonathan Orihuela Malca, Wilmer Amado Huaman Gomez, Carlos Alberto Ferrando Universidad César Vallejo Escuela de Posgrado Lima Peru Universidad Nacional de Educación Enrique Guzmán y Valle Pregrado Lima Peru Universidad Nacional Del Callao Pregrado Callao Peru

ISBN: (纸本)9798331508685

The development of wireless connections is being pushed by an unprecedented rise of artificial intelligence (AI) software, with 6G becoming a game-changing technology. However advanced artificial intelligence (AI) needs a lot of connectivity and processing power, which causes delays, energy waste, network traffic, and privacy breaches. By combining sensing, interaction, computing, and intellect, Edge AI - which incorporates model learning and reasoning capacities at the connection's edge - offers an innovative approach for 6G network deployments. With an emphasis on distributed machine learning algorithms and incorporated wireless networking protocols, this article offers a vision for sustainable and reliable edge artificial intelligence (AI) systems. To fit edge AI, the article also covers novel design concepts, service-driven utilization techniques for optimizing, and a complete end-to-end system framework. © 2025 IEEE.

关键词： Adversarial machine learning

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Special issue on advances in techniques for assessment performance portability of HPC applications

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Future Generation Computer Systems 2025年 171卷

作者： Marowka, Ami Stpiczyński, Przemyslaw Wyrzykowski, Roman Parallel Research Lab Petach Tikva49729 Israel Institute of Computer Science Maria Curie-Sklodowska University Lublin20-033 Poland Department of Computer Science Czestochowa University of Technology Czestochowa42-201 Poland

This special issue aims to present new developments and advances in techniques for assessment performance portability of high performance computing applications. It contains revised and extended versions of selected papers presented at the 10th Workshop on Language-Based parallel Programming Models, WLPP 2024, which was a part of 15th international conference on parallel processing and Applied Mathematics, PPAM 2024, held on September 8–11, 2024, in Ostrava, Czech Republic. © 2025

关键词： HPC applications parallel programming languages Performance portability

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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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AFMA-Track: Adaptive Fusion of Motion and Appearance for Robust Multi-object Tracking 27th

AFMA-Track: Adaptive Fusion of Motion and Appearance for ...

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27th international conference on Pattern Recognition, ICPR 2024

作者： Liao, Wei Luo, Lei Zhang, Chunyuan College of Computer Science and Technology National University of Defence Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory College of Computer Science and Technology National University of Defense Technology Changsha China

ISBN: (纸本)9783031784439

Motion and appearance cues play a crucial role in Multi-object Tracking (MOT) algorithms for associating objects across consecutive frames. While most MOT methods prioritize accurate motion modeling and distinctive appearance representations, the use of appearance and motion cues is often confined to simplistic association techniques. For instance, fixed weights are commonly employed to combine the intersection-over-union (IoU) matrix and appearance similarity matrix, yielding an association cost matrix. To harness the full potential of motion and appearance cues across diverse scenarios, we propose an innovative approach that dynamically balances motion and appearance cues based on scene and object information during the association process. Furthermore, we introduce a new mechanism for updating appearance representations, effectively mitigating noise introduced by occlusion. Our method demonstrates state-of-the-art performance on the MOT17 and MOT20 test sets. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Object detection

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NPB-PSTL: C++ STL Algorithms with parallel Execution Policies in NAS parallel Benchmarks

NPB-PSTL: C++ STL Algorithms with Parallel Execution Policie...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Júnior Löff Renato B. Hoffmann Arthur S. Bianchessi Leonardo Mallmann Dalvan Griebler Walter Binder Faculty of Informatics Università della Svizzera italiana (USI) Lugano Switzerland Pontifical Catholic University of Rio Grande do Sul (PUCRS) Porto Alegre Brazil

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

The C++ language continually evolves through formal specifications established by its standards committee, proposing new features to maintain $\mathrm{C}++$ as a relevant programming language while improving usability, performance, and portability across platforms. With the addition of parallel Standard Template Library (STL) algorithms in C++17, programmers can now leverage parallel processing capabilities via vendor-neutral parallel execution policies. This study presents an adaptation of the NAS parallel Benchmarks (NPB)—a well-established suite of applications for evaluating parallel architectures-by porting its sequential C-style code to use C++ STL abstractions and performance-portable parallelism features. Our goals are to (1) assess the suitability of C++ STL for scientific applications like the ones in the NPB and (2) provide a comparative performance and portability of STL algorithms’ parallel execution policies across different multicore architectures (x86 and AArch64). Results indicate that the performance of parallel STL algorithms is often close to that of optimized handwritten versions (OpenMP, Intel TBB, and FastFlow) on different architectures, with notable shortfalls. Across all NPB benchmarks, the STL algorithms’ geometric mean shows sequential execution times that are between 3.76% and $\mathrm{6. 9 \%}$ higher, while parallel executions may reach a geometric mean of up to $\mathrm{2 1. 2 1 \%}$ higher execution time.

关键词： parallel programming Multicore processing Software algorithms C++ languages Benchmark testing parallel processing Data structures Libraries Hardware Standards

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Meta-Heuristic Approaches to parallel processing in Signal Representation and Real-Time Analysis

Meta-Heuristic Approaches to Parallel Processing in Signal R...

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Automation and Computation (AUTOCOM), international conference on

作者： Harisha Naik N T Sudhanshu Dev Aniket Shivam Neelesh Singh Shreenidhi H S Awakash Mishra Department of Computer Applications (DCA) Presidency College Bengaluru India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Engineering and Technology Computer Science and Engineering JAIN (Deemed to be University) Bangalore Karnataka Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Meta-heuristic techniques have been popular in solving highly complex optimization problems. parallel processing is very important in signal representation and real-time analysis, as it helps lower the time required for the data process so that algorithms can perform faster. The biggest challenge with the traditional parallel processing techniques is load balancing and higher communication overhead, which may need to scale up to a larger extent. Meta-heuristic techniques reduce the complexity of problems that are NP-complete or NP-hard by providing satisfactory solutions and approximate answers to difficult ones. This has helped in parallel processing for signal representation and real-time analysis. parallel processing has also been useful in using meta-heuristic algorithms like genetic algorithms, ant colony optimization, and particle swarm optimization. Meta-heuristic algorithms produce flexible, adaptive mechanisms for solving complex problems.

关键词： Heuristic algorithms Metaheuristics Signal processing algorithms parallel processing Signal processing Approximation algorithms Load management Real-time systems Signal representation Particle swarm 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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