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

共 24639 条记录，以下是341-350 订阅

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Safe Execution of parallel Component Applications on an Unstable Heterogeneous Cluster Platform 4

Safe Execution of Parallel Component Applications on an Unst...

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4th international conference on Applied Mathematics, Modeling and Computer Simulation, AMMCS 2024

作者： Peng, Yunfeng Shi, Congming Gao, Guowei Wang, Jianan Liu, Hai School of Software Engineering Anyang Normal University Henan Anyang455000 China

ISBN: (纸本)9781643685519

parallel component technology improves the development efficiency and performance of parallel software. parallel component applications often need to be deployed on unstable heterogeneous cluster platforms. By analyzing the running mechanism of parallel component applications, this paper realizes the method of optimizing the deployment and running management of parallel components on the basis of modelling and managing the computing resources of heterogeneous platforms. This method can select nodes with light load to deploy parallel component code, and monitor the status of computing resources during the component operation. Our method can find the unavailable computing resources in time, and redeploy the parallel components running on them to other nodes with light load, which reduces the adverse impact of computing resource failure on the operation of component applications, and ensures the safe execution of parallel component applications on unstable heterogeneous platforms and achieves the expected results. © 2024 The Authors.

关键词： failure handling parallel component parallel computing Resource management

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Resiliency Measurement Framework for distributed Energy Resource Integrated Distribution Networks

Resiliency Measurement Framework for Distributed Energy Reso...

引用

2024 international conference on advances in computing, Communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Kuriakose, Eldho Aziz, Asma Qays, Md Ohirul Hossain, Md. Liton Hasan, Rasedul Sohan, Moshiur Rahman School of Engineering Edith Cowan University JoondalupWA6027 Australia University of Liberal Arts Bangladesh Department of Electrical and Electronic Engineering Dhaka1207 Bangladesh Aurecon Australasia North SydneyNSW2060 Australia

ISBN: (纸本)9798350350289

External and internal disruptions into power system stability motivates to research on a qualified grid resilience system. With this, indispensability of electricity infrastructure emphasizes the critical need for power system resilience in facing interruptions, especially extreme incidents e.g. natural disasters, deliberate attacks etc. Thus, this study concentrates on distribution networks, emphasizing the effect of natural disasters and integration of distributed energy resources to the grid. It offers a contemporary overview of grid resilience, introducing an advanced framework to assess distribution network resilience and analyse relevant terminologies. An adaptable grid resiliency framework derived from a meticulous examination of existing metric structures is presented in this study. PSCAD software is further utilized to present the real-world grid system analysis. The proposed model is, additionally, assessed by applying into an IEEE 9 bus test system to elucidate its potential impacts and feasible solution. The designed circuit demonstrate the recovery of faulty bus from potential blackout conditions with the help of integration of renewable energy sources. © 2024 IEEE.

关键词： Electric power distribution

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Exact distributed Stochastic Block Partitioning 25

Exact Distributed Stochastic Block Partitioning

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25th IEEE international conference on Cluster computing (CLUSTER)

作者： Wanye, Frank Gleyzer, Vitaliy Kao, Edward Feng, Wu-chun Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA MIT Lincoln Lab Lexington MA USA

ISBN: (纸本)9798350307924

Stochastic block partitioning (SBP) is a community detection algorithm that is highly accurate even on graphs with a complex community structure, but its inherently serial nature hinders its widespread adoption by the wider scientific community. To make it practical to analyze large real-world graphs with SBP, there is a growing need to parallelize and distribute the algorithm. The current state-of-the-art distributed SBP algorithm is a divide-and-conquer approach that limits communication between compute nodes until the end of inference. This leads to the breaking of computational dependencies, which causes convergence issues as the number of compute nodes increases and when the graph is sufficiently sparse. To address this shortcoming, we introduce EDiSt - an exact distributed stochastic block partitioning algorithm. Under EDiSt, compute nodes periodically share community assignments during inference. Due to this additional communication, EDiSt improves upon the divide-and-conquer algorithm by allowing it to scale out to a larger number of compute nodes without suffering from convergence issues, even on sparse graphs. We show that EDiSt provides speedups of up to 26.9x over the divide-and-conquer approach and speedups up to 44.0x over shared memory parallel SBP when scaled out to 64 compute nodes.

关键词： community detection graph clustering stochastic blockmodels bayesian inference asynchronous Gibbs MPI

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Island Energy Autonomy: A Techno-Economic Assessment of a Virtual Power Plant in Bangladesh

Island Energy Autonomy: A Techno-Economic Assessment of a Vi...

引用

2024 international conference on advances in computing, Communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Chowdhury, Prangon Yeassin, Rahbaar Tasmia, Israt Jahan Fuad, Abu M. Hasan, Mahmudul Chowdhury, Nahid-Ur-Rahman Ahsanullah University of Science and Technology Department of Electrical and Electronic Engineering Dhaka Bangladesh University of Scholars Department of Electrical and Electronic Engineering Dhaka Bangladesh Northern University Bangladesh Department of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350350289

Owing to population growth and industrialization, the need for electricity is at its apex, which creates stress on the grid due to the continuous consumption of power. To produce energy, natural resources are utilized ceaselessly, depleting the re-serve for the future. The consistent use of conventional resources is causing global warming along with several natural issues. Therefore, shifting to distributed energy resources (DERs) is a convenient solution. Although many of the developed countries have already implemented virtual power plants (VPP) and are pondering over their improvements, Bangladesh is lacking in this area. Therefore, this paper delves into existing energy scenarios and renewable energy (RE) prospects to design a VPP combining solar and wind for Hatiya Island in Bangladesh, to provide a continuous power supply to the whole region and remove the stress on the grid. The infrastructure of the whole system is developed in MATLAB/SIMULINK, and the techno-economic analysis is also carried out. The simulation outcomes illustrate that the Net Present Cost is 39550818 USD and the Levelized Cost of Energy is 0.03 USDlkWh. © 2024 IEEE.

关键词： distributed power generation

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Designing a Sustainable Serverless Graph Processing Tool on the computing Continuum

Designing a Sustainable Serverless Graph Processing Tool on ...

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29th international conference on parallel and distributed computing (Euro-Par)

作者： Farahani, Reza Ristov, Sashko Prodan, Radu Alpen Adria Univ Klagenfurt Klagenfurt Austria Univ Innsbruck Innsbruck Austria

ISBN: (纸本)9783031488023;9783031488030

Graph processing has become increasingly popular and essential for solving complex problems in various domains, like social networks. However, the processing of graphs on a massive scale poses critical challenges, such as inefficient utilization of resources and energy. To bridge such challenges, the Graph-Massivizer project, funded by the Horizon Europe research and innovation program, conducts research and develops a high-performance, scalable, and sustainable platform for information processing and reasoning based on the massive graph (MG) representation of extreme data. This paper presents an initial architectural design for the Graph-Choreographer, one of the five Graph-Massivizer tools. We explain Graph-Choreographer's components and demonstrate how Graph-Choreographer can adopt the emerging serverless computing paradigm to process Basic Graph Operations (BGOs) as serverless functions across the computing continuum efficiently. We also present an early vision of our federated Function-as-a-Service (FaaS) testbed, which will be used to conduct experiments and assess the tool's performance.

关键词： computing Continuum Serverless FaaS Massive Graph

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Fast and Energy-Efficient N-Body Simulation on FPGA through High-Level Synthesis 33

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

引用

33rd Euromicro international conference on parallel, distributed, and Network-Based Processing, PDP 2025

作者： Palazzari, Paolo Faltelli, Marco Iannone, Francesco Pascarella, Francesco ENEA Lungotevere Thaon di Revel 76 Rome00196 Italy

ISBN: (纸本)9798331524937

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. © 2025 IEEE.

关键词： Energy Efficiency FPGA High-Level Synthesis NBody parallel computing

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Adaptive Control and Optimization Techniques for Microgrid Energy Management 4

Adaptive Control and Optimization Techniques for Microgrid E...

引用

4th international conference on advances in Electrical, computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Sahu, Vishnu Kumar Singh, Mahesh Tiwari, Shruti Ralhan, Shimpy Shri Shankaracharya Technical Campus Department of Ee Chhattisgarh Bhilai India Shri Shankaracharya Technical Campus Department of Eee Chhattisgarh Bhilai India

ISBN: (纸本)9798350343670

In the era marked by rapid advancements in "green energy"and storage technologies, microgrids integrated with distributed generation principles emerge as a promising avenue for efficient power management. DC microgrids have attracted significant interest among researchers and engineers owing to the escalating adoption of renewable energy sources coupled with energy storage systems, improved utilization of DC power electronics devices, and the additional benefits of mitigating harmonics and synchronization challenges. A crucial aspect necessitates the establishment of an efficient, optimized, and dependable control system for the integrated infrastructure. This article introduces a versatile and adaptable control system for microgrid resources, aimed at fulfilling the local households' electricity demand while addressing economic considerations. The proposed approach adopts a decentralized control structure, deploying controllers in each household, leveraging open-source optimizers and cost-effective hardware. To mitigate the likelihood of failure, the authors developed a redundant solution, incorporating redundant communication channels and hot standby control devices. A comprehensive validation process was conducted via simulations on a sample microgrid encompassing diverse methods of generation and storage, ensuring robustness and reliability. © 2024 IEEE.

关键词： DC microgrids distributed energy generation Green energy microgrids

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parallel computing Techniques for Accelerating Machine Learning Algorithms on Big Data

Parallel Computing Techniques for Accelerating Machine Learn...

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2023 international conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Mishra, Rahul Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350357769

In the era of Big Data, the computational demands of machine learning (ML) algorithms have grown exponentially, necessitating the development of efficient parallel computing techniques. This research paper delves into the exploration and evaluation of advanced parallel computing methodologies tailored for accelerating ML algorithms when applied to vast datasets. We commence by providing a comprehensive overview of the existing parallelization paradigms, highlighting their strengths and limitations in the context of ML. Subsequently, we introduce novel techniques that harness the combined power of distributed systems, multicore processors, and graphics processing units (GPUs) to achieve significant speed-ups. Experimental results, derived from processing multi-terabyte datasets, demonstrate that our proposed methods can achieve up to a tenfold increase in computational efficiency compared to traditional approaches. Furthermore, we present a detailed analysis of the scalability, fault-tolerance, and resource utilization of our techniques, providing insights for practitioners aiming to deploy ML algorithms on large-scale data infrastructures. This work not only paves the way for faster ML computations but also offers a blueprint for the next generation of scalable, parallel ML systems. © 2023 IEEE.

关键词： Big Data distributed Systems Machine Learning Acceleration parallel computing Scalability

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A new parallel algorithm for transient structural analysis based on heterogeneous multi-core processor architecture

A new parallel algorithm for transient structural analysis b...

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2023 international conference on Computer Network Security and Software Engineering, CNSSE 2023

作者： Yu, Gaoyuan Wu, Xiaojun Dong, Hang Qin, Chuan Jin, Xianlong School of Mechanical Engineering Shanghai Jiaotong University Shanghai200240 China Aerospace System Engineering Shanghai Shanghai201108 China School of Aerospace Mechanical and Mechatronic Engineering University of Sydney NSW2006 Australia

ISBN: (数字)9781510666528

ISBN: (纸本)9781510666511

A new hierarchical communication parallel computing algorithm for transient structural analysis is introduced based on the architecture characteristics of heterogeneous multi-core processors in order to increase the parallel efficiency of the transient analysis of the entire extensive structure system carried out by heterogeneous multi-core processors and distributed memory parallel computers. With the two-layer parallelization of the computational process, this approach remarkably increases the memory access rate through distributed storage of a considerable quantity of data and significantly accelerates the communication rate. By fully utilizing the architectural features of heterogeneous multi-core and distributed memory parallel computers, it is possible to increase the efficiency rates of parallel computing for large-scale transient analysis. In the end, the accuracy and effectiveness of the suggested method were proved using typical numerical experiments. Specifically, a high-rise building's parallel transient analysis was conducted using ten thousand core processors with more than ten million degrees of freedom. © 2023 SPIE.

关键词： Transient analysis

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Towards Optimal Serverless Function Scaling in Edge computing Network

Towards Optimal Serverless Function Scaling in Edge Computin...

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IEEE international conference on Communications (IEEE ICC)

作者： Bensalem, Mounir Carpio, Francisco Jukan, Admela Tech Univ Carolo Wilhelmina Braunschweig Braunschweig Germany

ISBN: (纸本)9781538674628

Serverless computing has emerged as a new execution model which gained a lot of attention in cloud computing thanks to the latest advances in containerization technologies. Recently, serverless has been adopted at the edge, where it can help overcome heterogeneity issues, constrained nature and dynamicity of edge devices. Due to the distributed nature of edge devices, however, the scaling of serverless functions presents a major challenge. We address this challenge by studying the optimality of serverless function scaling. To this end, we propose Semi-Markov Decision Process-based (SMDP) theoretical model, which yields optimal solutions by solving the serverless function scaling problem as a decision making problem. We compare the SMDP solution with practical, monitoring-based heuristics. We show that SMDP can be effectively used in edge computing networks, and in combination with monitoring-based approaches also in real-world implementations.

关键词： SMDP scaling edge computing serverless

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