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

共 24638 条记录，以下是141-150 订阅

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parallel computing: advances And Current Issues, Proceedings Of The international conference Parco2001 1st

引用

2002年

作者： Gerhard R Joubert A Murli

ISBN: (数字)9781860949630

ISBN: (纸本)9781860943157

The near future will see the increased use of parallel computing technologies at all levels of mainstream computing. Computer hardware increasingly employs parallel techniques to improve computing power for the solution of large scale and computer intensive applications. Cluster and grid technologies make possible high speed computing facilities at vastly reduced *** developments can be expected to result in the extended use of all types of parallel computers in virtually all areas of human endeavour. Computer intensive problems in emerging areas such as financial modelling, data mining and multimedia systems, in addition to traditional application areas of parallel computing such as scientific computing and simulation, will lead to further progress. parallel computing as a field of scientific research and development has already become one of the fundamental computing *** book gives an overview of new developments in parallel computing at the start of the 21st century, as well as a perspective on future developments.

关键词： Computer Science

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A Performance Analysis of Autovectorization on RVV RISC-V Boards

A Performance Analysis of Autovectorization on RVV RISC-V Bo...

引用

Euromicro conference on parallel, distributed and Network-Based Processing

作者： Lorenzo Carpentieri Mohammad VazirPanah Biagio Cosenza Department of Computer Science University of Salerno Italy

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

The RISC-V instruction set architecture has become increasingly popular due to its open source and extensible design, making it a competitive choice in high-performance computing and embedded systems. The RISC-V Vector extension (RVV) empowers RISC-V processors with length-agnostic vectorization capabilities, a critical feature for efficiently handling parallel processing demands across different hardware. Compiler support for autovectorization allows to generate vector instructions automatically without requiring any effort to programmers. Given the limited yet evolving compiler support for RVV, this paper offers an in-depth examination of autovectorization capabilities in GCC and LLVM, for RVV version 0.7 and 1.0. We evaluated the autovectorization performance of LLVM, LLVM-EPI and GCC compilers across 151 loops from the Test Suite for Vectorizing Compilers (TSVC) ans seven real-world applications on the AllWinner D1 and BananaPi-F3 boards, representing RISC-V vector hardware. Our study focuses on quantifying and comparing the level of vectorization each compiler achieves across a diverse range of vectorization patterns and workloads, providing insight into their strengths and limitations with respect to RISC-V RVV. Our findings highlight that the LLVM-19 compiler outperforms GCC-14 in 76 out of 151 loops, and its performance is more sensitive to the selection of vector length. Additionally, tuning the vector Length Multiplier (LMUL) parameter can lead to performance improvements of up to $3 x$, and leveraging knowledge of the vector length can further enhance LMUL optimization in compilers.

关键词： Embedded systems Instruction sets High performance computing parallel processing Vectors Hardware Registers Performance analysis Tuning Optimization

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DNA computing: A Breakthrough in Image Cryptography - A Comprehensive Review

DNA Computing: A Breakthrough in Image Cryptography - A Comp...

引用

international CSI Computer conference, CSICC

作者： Hesam Noorpoor Asadollah Shahbahrami Department of Computer Engineering University of Guilan Rasht Iran

ISBN: (数字)9798331523114

ISBN: (纸本)9798331523121

Deoxyribonucleic acid-DNA computing, an interdisciplinary field at the frontier between molecular biology and computer science, has become a revolutionary field. DNA computation provides a new approach to data computation and cryptography. The inherent properties of DNA include high parallelism, excellent data density, and stability; it can hence be considered one of the ideal candidates in cryptographic applications, especially in image encryption. This review provides recent advances in DNA-based cryptographic algorithms, their fusion with chaotic systems, and also their applications to practical scenarios that enhance data security. Different algorithms are studied that exploit the encoding capability of DNA, such as substitution, transposition, and hybrid models including crossover and mutation. It also discusses DNA for secure image transmission in applications like healthcare, industrial IoT, and cloud environments. The latter presents scalability challenges and problems regarding key generation along with certain implementation constraints, while at the same time pointing future research toward a perspective of opening up for stronger cryptography.

关键词： Reviews Scalability DNA Medical services parallel processing Stability analysis Encryption Molecular biology Computer security DNA computing

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From Local to Remote: Scaling VisIVO Visual Analytics for Large-Scale Astrophysical Data Visualization

From Local to Remote: Scaling VisIVO Visual Analytics for La...

引用

Euromicro conference on parallel, distributed and Network-Based Processing

作者： Giuseppe Tudisco Fabio Vitello Eva Sciacca Ugo Becciani Osservatorio Astrofisico di Catania Istituto Nazionale di Astrofisica (INAF) Catania Italy

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

As the Square Kilometre Array (SKA) radio telescopes approach full operation, they are set to generate hundreds of petabytes of data annually, offering unprecedented resolution and detail in astrophysical observations. This massive influx of data presents significant challenges in terms of storage, processing, analysis and visualization. Scientific visualization becomes essential in this context, enabling researchers to interpret complex, high-dimensional datasets and extract valuable insights. This paper presents the latest developments of VisIVO Visual Analytics, an interactive visualization tool that is evolving to meet the needs of the SKA and similar large-scale astrophysical projects such as the James Webb Space Telescope and the Atacama Large Millimeter/submillimeter Array (ALMA). Originally designed as a desktop application, VisIVO is transitioning to a client-server architecture, allowing it to efficiently run remote visualization pipelines on remote servers. This shift significantly enhances the tool’s ability to handle large scale datasets, facilitating real-time, interactive analysis of complex data. This work also explores how VisIVO Visual Analytics can distribute computational workloads across multiple nodes in high-performance computing (HPC) clusters for parallel visualization pipelines, enabling advanced and interactive techniques to derive meaningful insights from the vast volumes of data generated by next-generation observatories.

关键词： Radio astronomy Visual analytics High performance computing Pipelines Data visualization Computer architecture Telescopes Arrays Servers Usability

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Anomaly Detection in Microservices Architecture Using Graph Neural Networks

Anomaly Detection in Microservices Architecture Using Graph ...

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Euromicro conference on parallel, distributed and Network-Based Processing

作者： Matthias Osswald Timothy Schönenberger Gokcan Cantali Wissem Soussi Gürkan Gür Zurich University of Applied Sciences (ZHAW) InIT Winterthur Switzerland Communication Systems Group CSG University of Zürich UZH Zürich Switzerland

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

The rise of cloud computing has transformed application development and deployment, with Kubernetes emerging as a key platform for managing containerized applications. This paper explores the use of Graph Neural Networks (GNNs) to detect anomalies in Kubernetes clusters and proposes GNN-based Anomaly Detection in Kubernetes (GATAKU), which is instrumental in maintaining security and performance. Our work involves integrating Cilium for detailed network monitoring and data collection, setting up a Kubernetes cluster with k3s and Traefik, and simulating attack scenarios to generate realistic data. Data preprocessing and feature engineering prepare this data for the GNN training. We present the GATAKU model’s performance, highlighting metrics such as accuracy, precision, recall, and F 1 -score and compare it to baseline ML models, namely Support Vector Machine (SVM) and Random Forest (RF). Moreover, we discuss these findings and emerging challenges, including handling high-dimensional data, and explore practical implications for cybersecurity.

关键词： Support vector machines Training Cloud computing Analytical models Accuracy Computer architecture Graph neural networks Computer security Anomaly detection Tuning

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Fault-Tolerant Architectures for distributed Big Data Analytics

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

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advances in Computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), international conference on

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

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

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.

关键词： Scalability Fault tolerant systems Redundancy distributed databases Computer architecture Big Data Data processing Real-time systems Complexity theory Physical design

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A Finite Control Set based Model Predictive Controller for Load Power Sharing Applications in Inverter Fed Microgrids

A Finite Control Set based Model Predictive Controller for L...

引用

Power, Control and computing Technologies (ICPC2T), conference on

作者： Devarapalli Vimala B. Lokeshgupta V. Naresh Kumar Department of Electrical and Electronics Engineering SRM University Andhra Pradesh

ISBN: (数字)9798331530402

ISBN: (纸本)9798331530419

Microgrids have gained more attention in recent days due to the efficient integration of various distributed energy resources. However, the load power sharing between the distribution generators (DGs) in the microgrids is one of the major challenges, especially at the peak load demand condition. This paper proposes a finite control set-based model predictive controller (FCS-MPC) for the DG-fed inverters in microgrid applications. A universal droop controller model is also considered into account to generate the reference values for the proposed FCS-MPC controller for improved power sharing. The main goal of this paper is to efficiently regulate the power flow from/to the parallel DGs in a microgrid environment. The proposed control method is able to share equal load power, though there is a mismatch in line impedances in the AC microgrid network. In this study, the microgrid test system with two parallel DGs is used to evaluate the performance of the proposed model. To show the effectiveness of the proposed control method, the simulation results of the proposed model have also been compared with the conventional droop control technique. The proposed model has superior performance compared to the conventional droop controller in terms of load power sharing and maintaining tolerance limits, as evidenced by the simulation results.

关键词： Simulation Computational modeling Power control Microgrids Predictive models Inverters Generators distributed power generation Load modeling Load flow

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Enhancing Air Quality Monitoring: A Brief Review of Federated Learning advances 2nd

Enhancing Air Quality Monitoring: A Brief Review of Federate...

引用

2nd international conference on Intelligent Manufacturing and Robotics, ICIMR 2024

作者： Yarham, Sara Behjati, Mehran Alobaidy, Haider A. H. Majeed, Anwar P. P. Abdul Zheng, Yufan Department of Computing and Information Systems School of Engineering and Technology Sunway University Bandar Sunway47500 Malaysia Department of Information and Communications Engineering College of Information Engineering Al-Nahrain University Baghdad64046 Iraq Suzhou Taicang215400 China

ISBN: (纸本)9789819639489

Monitoring air quality and environmental conditions is crucial for public health and effective urban planning. Current environmental monitoring approaches often rely on centralized data collection and processing, which pose significant privacy, security, and scalability challenges. Federated Learning (FL) offers a promising solution to these limitations by enabling collaborative model training across multiple devices without sharing raw data. This decentralized approach addresses privacy concerns while still leveraging distributed data sources. This paper provides a comprehensive review of FL applications in air quality and environmental monitoring, emphasizing its effectiveness in predicting pollutants and managing environmental data. However, the paper also identifies key limitations of FL when applied in this domain, including challenges such as communication overhead, infrastructure demands, generalizability issues, computational complexity, and security vulnerabilities. For instance, communication overhead, caused by the frequent exchange of model updates between local devices and central servers, is a notable challenge. To address this, future research should focus on optimizing communication protocols and reducing the frequency of updates to lessen the burden on network resources. Additionally, the paper suggests further research directions to refine FL frameworks and enhance their applicability in real-world environmental monitoring scenarios. By synthesizing findings from existing studies, this paper highlights the potential of FL to improve air quality management while maintaining data privacy and security, and it provides valuable insights for future developments in the field. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Environmental monitoring

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FEniCSx-Based Effective Scheme for the Cahn-Hilliard Equation

FEniCSx-Based Effective Scheme for the Cahn-Hilliard Equatio...

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advances in Electrical, computing, Communication and Sustainable Technologies (ICAECT), international conference on

作者： Harsh Bhutra Bettina Ann Thomas K Shreya Shri T.V. Smitha Nizampatnam Neelima Department of Electronics and Communication Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India Computational Science Lab Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

The Cahn-Hilliard equation is a fourth-order parabolic partial differential equation that is challenging and time-intensive to solve using conventional methods. Although the equation is difficult to solve, it finds its use cases in many aspects of science including but not limited to the study of phase separation in the binary, isotropic and isothermal mixtures of materials such as molten alloys. Some of the other applications are Bioinformatics, Computational Biology, Biomedical informatics, human activity recognition, Healthcare, computer vision, Climate Science and Natural Language Processing. Many researchers have come up with a way to deal with partial differential equations, but very few works and methods deal with different orders of partial differential equations. In this article, a novel and effective scheme for solving the Cahn-Hilliard equation is proposed using FEniCS. The time of execution and relative tolerance of the solutions of this equation are computed from methods of direct computation and parallel processing which is carried out for the equation with higher-order finite element method for various boundary conditions to demonstrate the efficiency of the proposed approach. The solution thus obtained helps in understanding the non-linear behaviour of the equation with the help of a three-dimensional heatmap plot. This work solves the Cahn Hilliard equation by using the in-built libraries, Dolphin an open-source software called FEniCS and Message Passing Interface (MPI). The MPI is responsible for achieving parallelism in high-performance computing environments and breaks down the problem into four smaller parts making it faster to get to the solution. The obtained results demonstrate that this approach outperforms the existing literature by achieving a forty percent faster computational speed. The approach will be very useful in solving many similar problems arising in the field of science and engineering.

关键词： Heating systems Accuracy Three-dimensional displays Partial differential equations parallel processing Boundary conditions Mathematical models Libraries Computational efficiency Bioinformatics

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Fast and Energy-Efficient N-Body Simulation on FPGA through High-Level Synthesis

Fast and Energy-Efficient N-Body Simulation on FPGA through ...

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Euromicro conference on parallel, distributed and Network-Based Processing

作者： Paolo Palazzari Marco Faltelli Francesco Iannone Francesco Pascarella ENEA Lungotevere Thaon di Revel 76 Rome Italy

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

The N -body problem is a classical computational challenge that involves integrating the motion equations of a system of interacting bodies. This problem is computationally demanding and, as power consumption becomes a critical issue in computing systems, increasing the energy efficiency of solutions is essential. To address this, we use FPGA accelerators to implement the acceleration computation, the most demanding part of the integration algorithm. FPGAs are known for their low power requirements and high internal parallelism, but they traditionally require hardware programming skills. With High-Level Synthesis (HLS) now well established, we leverage the AMD Vitis HLS toolchain to implement the acceleration computation for the N-body problem. After analyzing the various forms of parallelism at different levels of granularity in the acceleration computation, we design a parallel architecture, implemented on an FPGA using the HLS flow. The speed and energy efficiency of our solution are compared against high-end CPU implementations, showing substantial improvements. Our FPGA implementation achieves 30.4 GPair/s and $697\ \mathrm{MPair} / \mathrm{s} / \mathrm{W}$, significantly outperforming previous FPGA and CPU solutions in both speed and power consumption.

关键词： Power demand Multicore processing parallel processing Programming Energy efficiency Mathematical models Hardware Computational efficiency Field programmable gate arrays

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