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检索条件"任意字段=9th International Conference on Parallel and Distributed Computing, Applications and Technologies"

共 1770 条记录，以下是101-110 订阅

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Allocation of distributed Generators Using parallel Grey Wolf Optimization 9

Allocation of Distributed Generators Using Parallel Grey Wol...

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9th international conference on Modern Power Systems (MPS)

作者： Younesi, Soheil Ahmadi, Bahman Ceylan, Oguzhan Ozdemir, Aydogan Istanbul Tech Univ Dept Elect Engn Istanbul Turkey Kadir Has Univ Management & Informat Syst Dept Istanbul Turkey

ISBN: (纸本)9781665433815

this paper solves the allocation problem of distributed generators (DGs) in smart grids utilizing a grey wolf optimization (GWO) algorithm. By parallelizing GWO, it presents the impact of using various number of processors on speedup, efficiency. To decrease the computation time required to perform the simulations, different migration rates are applied for different number of processors. Moreover, the accuracy obtained using different number of processors is analyzed. the simulations are performed for a 33-bus distribution test system using MATLAB's parallel computing toolbox. From the simulation results it is observed that parallel GWO can be used as a tool for distribution system optimization.

关键词： parallel Computation Smart grids distributed generators Optimization Grey Wolf Optimization Algorithm

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Unsatisfiability Proofs for distributed Clause-Sharing SAT Solvers 29th

Unsatisfiability Proofs for Distributed Clause-Sharing SAT S...

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29th international conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS)

作者： Michaelson, Dawn Schreiber, Dominik Heule, Marijn J. H. Kiesl-Reiter, Benjamin Whalen, Michael W. Amazon Web Serv Seattle WA USA Univ Minnesota Minneapolis MN 55455 USA Karlsruhe Inst Technol Karlsruhe Germany Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9783031308222;9783031308239

distributed clause-sharing SAT solvers can solve problems up to one hundred times faster than sequential SAT solvers by sharing derived information among multiple sequential solvers working on the same problem. Unlike sequential solvers, however, distributed solvers have not been able to produce proofs of unsatisfiability in a scalable manner, which has limited their use in critical applications. In this paper, we present a method to produce unsatisfiability proofs for distributed SAT solvers by combining the partial proofs produced by each sequential solver into a single, linear proof. Our approach is more scalable and general than previous explorations for parallel clause-sharing solvers, allowing use on distributed solvers without shared memory. We propose a simple sequential algorithm as well as a fully distributed algorithm for proof composition. Our empirical evaluation shows that for large-scale distributed solvers (100 nodes of 16 cores each), our distributed approach allows reliable proof composition and checking with reasonable overhead. We analyze the overhead and discuss how and where future efforts may further improve performance.

关键词： SAT solving proofs distributed computing

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FederatedMesh: Collaborative Federated Learning for Medical Data Sharing in Mesh Networks 19th

FederatedMesh: Collaborative Federated Learning for Medical...

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19th EAI international conference on Collaborative computing: Networking, applications and Worksharing, CollaborateCom 2023

作者： Shkurti, Lamir Selimi, Mennan Besimi, Adrian Faculty of Contemporary Sciences and Technologies South East European University Tetovo Macedonia Max van der Stoel Institute South East European University Tetovo Macedonia

ISBN: (纸本)9783031545306

Edge computing is a paradigm that involves performing local processing on lightweight devices at the edge of networks to improve response times and reduce bandwidth consumption. While machine learning (ML) models can run on smaller computing devices at the edge, training ML models presents challenges for low-capacity devices. this paper aimed to evaluate the performance of Federated Learning (FL) - a distributed ML framework, when training a medical dataset using Raspberry Pi devices as client nodes. the testing accuracy, CPU usage, RAM memory usage and network performance were measured for different number of clients and epochs. the results showed that increasing the number of devices generally improved the testing accuracy, with the greatest improvement observed in the earlier epochs. However, increasing the number of devices also increased the CPU usage, with a significant increase observed in the later epochs. Additionally, the RAM memory usage increased slightly as the number of clients and epochs increased. the findings suggest that FL can be an effective way to train medical models using distributed devices, but careful consideration must be given to the trade-off between accuracy and computational resources. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Edge computing

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A PGAS-Based Implementation for the parallel Minimum Spanning Tree Algorithm 13th

A PGAS-Based Implementation for the Parallel Minimum Spannin...

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13th international conference on Large-Scale ScientificComputations (LSSC)

作者： Bejanyan, Vahag Astsatryan, Hrachya Natl Acad Sci Republ Armenia Inst Informat & Automat Problems 1 Paruyr Sevak St Yerevan 0014 Armenia

ISBN: (纸本)9783030975494;9783030975487

the minimum spanning tree is a critical problem for many applications in network analysis, communication network design, and computer science. the parallel implementation of minimum spanning tree algorithms increases the simulation performance of large graph problems using high-performance computational resources. the minimum spanning tree algorithms generally use traditional parallel programming models for distributed and shared memory systems, like Massage Passing Interface or OpenMP. Furthermore, the partitioned global address space model offers new capabilities in the form of asynchronous computations on distributed shared memory, positively affecting the performance and scalability of the algorithms. the paper aims to present a new minimum spanning tree algorithm implemented in a partitioned global address space model. the experiments with diverse parameters have been conducted to study the efficiency of the asynchronous implementation of the algorithm.

关键词： Minimum spanning tree PGAS model parallel algorithms Large-scale graphs HPC

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Low Latency Execution Guarantee Under Uncertainty in Serverless Platforms 22nd

Low Latency Execution Guarantee Under Uncertainty in Serverl...

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22nd international conference on parallel and distributed computing, applications and technologies (PDCAT 2021)

作者： HoseinyFarahabady, M. Reza Taheri, Javid Zomaya, Albert Y. Tari, Zahir Univ Sydney Ctr Distributed & High Performance Comp Sch Comp Sci Sydney NSW Australia Karlstad Univ Dept Math & Comp Sci Karlstad Sweden RMIT Univ Sch Comp Technol Melbourne Vic Australia

ISBN: (纸本)9783030967727;9783030967710

Serverless computing recently emerged as a new run-time paradigm to disentangle the client from the burden of provisioning physical computing resources, leaving such difficulty on the service provider's side. However, an unsolved problem in such an environment is how to cope with the challenges of executing several co-running applications while fulfilling the requested Quality of Service (QoS) level requested by all application owners. In practice, developing an efficient mechanism to reach the requested performance level (such as p-99 latency and throughput) is limited to the awareness (resource availability, performance interference among consolidation workloads, etc.) of the controller about the dynamics of the underlying platforms. In this paper, we develop an adaptive feedback controller for coping with the buffer instability of serverless platforms when several collocated applications are run in a shared environment. the goal is to support a low-latency execution by managing the arrival event rate of each application when shared resource contention causes a significant throughput degradation among workloads with different priorities. the key component of the proposed architecture is a continues management of server-side internal buffers for each application to provide a low-latency feedback control mechanism based on the requested QoS level of each application (e.g., buffer information) and the worker nodes throughput. the empirical results confirm the response stability for high priority workloads when a dynamic condition is caused by low priority applications. We evaluate the performance of the proposed solution with respect to the response time and the QoS violation rate for high priority applications in a serverless platform with four worker nodes set up in our in-house virtualized cluster. We compare the proposed architecture against the default resource management policy in Apache OpenWhisk which is extensively used in commercial serverless platforms. th

关键词： Dynamic controller of computer systems Serverless computing Virtualized platforms Quality of Service (QoS)

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PRACTICAL MASSIVELY parallel MONTE-CARLO TREE SEARCH APPLIED TO MOLECULAR DESIGN 9

PRACTICAL MASSIVELY PARALLEL MONTE-CARLO TREE SEARCH APPLIED...

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9th international conference on Learning Representations, ICLR 2021

作者： Yang, Xiufeng Aasawat, Tanuj Kr Yoshizoe, Kazuki Chugai Pharmaceutical Co. Ltd Japan Parallel Computing Lab - India Intel Labs India RIKEN Center for Advanced Intelligence Project Japan

It is common practice to use large computational resources to train neural networks, known from many examples, such as reinforcement learning applications. However, while massively parallel computing is often used for training models, it is rarely used to search solutions for combinatorial optimization problems. this paper proposes a novel massively parallel Monte-Carlo Tree Search (MP-MCTS) algorithm that works efficiently for a 1,000 worker scale on a distributed memory environment using multiple compute nodes and applies it to molecular design. this paper is the first work that applies distributed MCTS to a real-world and non-game problem. Existing works on large-scale parallel MCTS show efficient scalability in terms of the number of rollouts up to 100 workers. Still, they suffer from the degradation in the quality of the solutions. MP-MCTS maintains the search quality at a larger scale. By running MP-MCTS on 256 CPU cores for only 10 minutes, we obtained candidate molecules with similar scores to non-parallel MCTS running for 42 hours. Moreover, our results based on parallel MCTS (combined with a simple RNN model) significantly outperform existing state-of-the-art work. Our method is generic and is expected to speed up other applications of MCTS. © 2021 ICLR 2021 - 9th international conference on Learning Representations. All rights reserved.

关键词： Reinforcement learning

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IMpart: A Partitioning-based parallel Approach to Accelerate Influence Maximization 29

IMpart: A Partitioning-based Parallel Approach to Accelerate...

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29th Annual IEEE international conference on High Performance computing, Data, and Analytics (HiPC)

作者： Barik, Reet Minutoli, Marco Halappanavar, Mahantesh Kalyanaraman, Ananth Washington State Univ Pullman WA 99164 USA Pacific Northwest Natl Lab Richland WA 99352 USA

ISBN: (纸本)9781665494236

Influence maximization (IM) is a fundamental operation among graph problems that involve simulating a stochastic diffusion process on real-world networks. Given a graph G(V, E), the objective is to identify a small set of key influential "seeds"i.e., a fixed-size set of k nodes, which when influenced is likely to lead to the maximum number of nodes in the network getting influenced. the problem has numerous applications including (but not limited to) viral marketing in social networks, epidemic control in contact networks, and in finding influential proteins in molecular networks. Despite its importance, application of influence maximization at scale continues to pose significant challenges. While the problem is NP-hard, efficient approximation algorithms that use greedy hill climbing are used in practice. However those algorithms consume hours of multithreaded execution time even on modest-sized inputs with hundreds of thousands of nodes. In this paper, we present IMpart, a partitioning-based approach to accelerate greedy hill climbing based IM approaches on both shared and distributed memory computers. In particular, we present two parallel algorithmsone that uses graph partitioning (IMpart-metis) and another that uses community-aware partitioning (IMpart-gratis)with provable guarantees on the quality of approximation. Experimental results show that our approaches are able to deliver two to three orders of magnitude speedup over a state-of-the-art multithreaded hill climbing implementation with negligible loss in quality. For instance, on one of the modest-sized inputs (Slashdot: 73K nodes;905K edges), our partitioning-based shared memory implementation yields 4610x speedup, reducing the runtime from 9h 36m to 7 seconds on 128 threads. Furthermore, our distributed memory implementation enhances problem size reach to graph inputs with x10(6) nodes and x10(8) edges and enables sub-minute computation of IM solutions.

关键词： community detection graph partitioning greedy hill climbing Influence maximization parallel seed selection

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Mathematical Modeling of Transaction Latency on Ethereum 12

Mathematical Modeling of Transaction Latency on Ethereum

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12th IEEE international conference on Joint Cloud computing (IEEE JCC) / 9th IEEE international conference on Mobile Cloud computing, Services, and Engineering (IEEE MobileCloud)

作者： Guo, Jinyan Jiang, Zigui Li, Li Bian, Jing Sun Yat Sen Univ Sch Math Guangzhou 510006 Peoples R China Sun Yat Sen Univ Sch Software Engn Guangzhou 510006 Peoples R China Guangdong Inst Sci & Technol Informat Guangzhou 510030 Peoples R China Parallel & Distributed Proc Lab PDL Sci & Technol Changsha 410073 Peoples R China

ISBN: (纸本)9781665434799

applications on blockchain are currently limited by the relatively poor performance of the blockchain network such as low TPS, high latency and the resulting high transaction fees. Hence, performance optimization is one crucial problem of blockchain. Focusing on the most prosperous public blockchain Ethereum, we model the on-chain transaction confirmation process with the knowledge of Poisson process and queueing theory, derives the mean transaction-confirmation time, and explores the effect of different transaction fees on latency. We also conduct a numeric simulation of the model, which indicates that the model fits in well with the real world blockchain.

关键词： Blockchain Ethereum Mathematical modeling Stochastic process Queueing theory

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ComFaaS distributed: Edge computing with Function-as-a-Service in parallel Cloud Environments

ComFaaS Distributed: Edge Computing with Function-as-a-Servi...

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international conference on Information and Computer technologies (ICICT)

作者： Jaden Jinu Lee Judah Nava Hanku Lee Computer Science and Information Systems Minnesota State University Moorhead Moorhead MN

ISBN: (数字)9798350385625

ISBN: (纸本)9798350385632

Function-as-a-Service (FaaS) has emerged as a revolutionary service platform, abstracting the complexities of hardware, operating systems, and web hosting services. this allows developers to focus solely on implementing their service applications, making FaaS an ideal platform for the scalable manipulation of large data sets. Traditionally deployed on the cloud, FaaS now faces a new frontier: the network edge. Leveraging the edge offers several potential benefits, including reduced latency and improved resource utilization, making it a promising approach for efficient FaaS deployment. As the daily volume and complexity of data we handle continues to grow, adopting a parallel computing paradigm has become increasingly important to ensure fast and efficient execution of computational tasks. Addressing this need, ComFaaS distributed embarks on a comprehensive comparison of the capabilities of parallelized edge and cloud environments for FaaS deployment. Utilizing benchmark programs meticulously crafted to simulate event-triggered scenarios, ComFaaS distributed aims to provide valuable insights into the performance and potential of FaaS at the edge, paving the way for a future where parallel computing empowers the efficient and scalable processing of ever-growing data volumes.

关键词： Cloud computing Computer architecture parallel processing Benchmark testing Computational efficiency Complexity theory Web sites

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Design and Analysis of Proposed Smartphone-based distributed parallel Processing System

Design and Analysis of Proposed Smartphone-based Distributed...

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international Engineering conference (IEC)

作者： Nashma Taha Muhammed Zryan Najat Rashid Subhi R. M. Zeebaree Yousif Sufyan Jghef Rowaida Khalil Ibrahim Teba Mohammed Ghazi Sami IT Department Sulaimani Polytechnic University Sulaymani Iraq Computer Network Department Sulaimani Polytechnic University Sulaymani Iraq Energy Eng. Department Duhok Polytechnic University Duhok Iraq Computer Eng. Department Knowledge University Erbil Iraq Computer Science Department University of Zakho Duhok Iraq

Online storage and use of digital assets and applications are both aspects of cloud computing. through a computer network, distributed information systems store and transmit data. Data and effort have both grown for studying and keeping track of outcomes. Cloud-based parallel processing techniques must be improved. Our research hastens the resolution of interactive composite jobs. In this innovative architecture, cell phones act as servers for distributed parallel processing and cloud computing. Users with restricted availability could find the update useful for completing challenging jobs. the recommended strategy is supported by cloud computing, which may expand to infinity servers (webserver). Servers between clients and servers are automatically registered by web servers. Cloud storage and client-side matrices (web server). To ensure timely completion, the server distributes matrix algebra assignments to all subscribed workstations. Before transmitting results to the user, the server uploads them to the cloud. A large number of sets of two-dimensional matrices were requested from the user, and the responses were compared to the total number of servers that were available.

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