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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8678卷 70-79页

作者： Obeid, Mohammad F. Chemlal, Salim Rechowicz, Krzysztof J. Heo, Eun-Sil Kelly, Robert E. McKenzie, Frederic D. Dept. of Modeling Simulation and Visualization Engineering Old Dominion University Norfolk United States Dept. of Electrical and Computer Engineering Old Dominion University Norfolk United States Virginia Modeling Analysis and Simulation Center Old Dominion University Norfolk United States Pediatric Surgery Children’s Hospital of The King’s Daughters and Eastern Virginia Medical School Norfolk United States

With rapid development of minimally invasive surgery, proficiency with intricate skills is becoming a greater concern. Consequently, the use of out-of-operating room training has increased significantly through employing high-fidelity and anatomically-correct graphics and haptic interfaces in virtual reality simulations. The effort in developing surgical simulators for generic minimally invasive procedures is still, however, suboptimal for many haptic implementations. A main aspect of such simulations is the pivoting behavior of the surgical tool realized using the haptic device. This paper investigates the limitation of a fullyvirtual implementation of the pivot and the ability to augment haptic interfaces to achieve a natural representation of forces. The design and implementation of two surgical tool pivoting techniques are introduced. Furthermore, a phantom is constructed from synthesized components to be used to measure and reproduce realistic mechanical properties of the anatomical model and pivot behavior. © Springer International Publishing Switzerland 2014.

关键词： Augmented reality

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Scalable replay with partial-order dependencies for message-logging fault tolerance

Scalable replay with partial-order dependencies for message-...

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IEEE International Conference on Cluster Computing

作者： Jonathan Lifflander Esteban Meneses Harshitha Menon Phil Miller Sriram Krishnamoorthy Laxmikant V. Kalé Department of Computer Science University of Illinois Urbana-Champaign Center for Simulation and Modeling University of Pittsburgh Department of Computer Science University of Illinois at Urbana-Champaign Advanced Computing Mathematics and Data Division Pacific Northwest National Laboratory

Deterministic replay of a parallel application is commonly used for discovering bugs or to recover from a hard fault with message-logging fault tolerance. For message passing programs, a major source of overhead during forward execution is recording the order in which messages are sent and received. During replay, this ordering must be used to deterministically reproduce the execution. Previous work in replay algorithms often makes minimal assumptions about the programming model and application to maintain generality. However, in many applications, only a partial order must be recorded due to determinism intrinsic in the program, ordering constraints imposed by the execution model, and events that are commutative (their relative execution order during replay does not need to be reproduced exactly). In this paper, we present a novel algebraic framework for reasoning about the minimum dependencies required to represent the partial order for different orderings and interleavings. By exploiting this framework, we improve on an existing scalable message-logging fault tolerance scheme that uses a total order. The improved scheme scales to 131,072 cores on an IBM BlueGene/P with up to 2× lower overhead.

关键词： Fault tolerance Fault tolerant systems Programming Debugging Program processors Electronic mail Benchmark testing

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A Hybrid Web-Based Toolkit for Human modeling

A Hybrid Web-Based Toolkit for Human Modeling

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IEEE Scientific Visualization Conference (SciVis)

作者： M. Bender R. Klein A. Ebert H. Rodrian Computer Graphics Group Department of Computer Science University of Kaiserslautern Germany Human Modeling Department TECMATH GmbH and Company KG Kaiserslautern Germany Intelligent Visualization and Simulation Systems German Research Center for Artificial Intelligence Germany

Modern web-based Scientific Visualization applications try to overcome common limitations imposed by limited internet bandwidth, server bottlenecks or network latency. A further aspect is the desire to gain platform independence by solely using instruments which are platform independent by conception: the programming language Java, the Virtual Reality modeling Language (VRML), or the 3D API *** present a prototype of a hybrid web-based Scientific Visualization system which makes use of the increasing computational power of modern desktop workstations and personal computers on the client side, and the superior performance provided by a powerful machine on the server side. In order to achieve high interaction rates and to balance computational load the user can dynamically assign selected tasks to his client or to the *** the scientific field of human modeling we have implemented a hybrid web-based toolkit for the modeling of human muscles and skin. Our application allows the on-line generation and manipulation of three-dimensional implicit muscle models in a heterogeneous network and it offers various parameters to adjust computation and response time versus rendering quality.

关键词： Humans Visualization Delay Java Muscles IP networks Bandwidth Network servers Web server Performance gain

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An Auto-Parallel Method for Deep Learning Models Based on Genetic Algorithm 29

An Auto-Parallel Method for Deep Learning Models Based on Ge...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Zeng, Yan Huang, Chengchuang Ni, Yijie Zhou, Chunbao Zhang, Jilin Wang, Jue Zhou, Mingyao Xue, Meiting Zhang, Yunquan Hangzhou Dianzi University School of Computer Science and Technology Hangzhou310018 China Ministry of Education Key Laboratory for Modeling and Simulation of Complex Systems Hangzhou310018 China Data Security Governance Zhejiang Engineering Research Center Hangzhou310018 China Hangzhou Dianzi University School of ITMO Joint Institute Hangzhou310018 China Institute of Computer Network Information Center of the Chinese Academy of Sciences Beijing100086 China HuaWei China Institute of Computing Technology of the Chinese Academy of Sciences State Key Laboratory of Computer Architecture Beijing100086 China

ISBN: (纸本)9798350330717

As the size of datasets and neural network models increases, automatic parallelization methods for models have become a research hotspot in recent years. The existing auto-parallel methods based on machine learning or graph algorithms still have issues with search efficiency and applicability. This paper proposes an automatic parallel method based on a dual-population genetic algorithm, TGA, which transforms model partitioning and placement into an integer linear programming problem and constructs a cost model to evaluate the solution. The solution space is built using the neural network's dataflow graph and device cluster's topology, and the dual-population genetic algorithm is used to search for the optimal model parallel strategy. Experiments with various models show that the proposed method can improve single-step execution time by up to 42% compared to the Baechi method and up to 37.7% compared to the Hierarchical method. © 2023 IEEE.

关键词： Auto-Parallel Distributed machine learning Genetic algorithm Integer linear programming Model parallelism

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Application of combined discrete-event simulation and optimization models in semiconductor enterprise manufacturing systems 07

Application of combined discrete-event simulation and optimi...

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simulation Winter Conference

作者： Gary Godding Hessam Sarjoughian Karl Kempf Arizona Center for Integrative Modeling & Simulation Computer Science and Engineering Department Arizona State University Tempe AZ USA Corporate Planning and Logistics Group Intel Corporation Chandler AZ USA

ISBN: (纸本)9781424413065

It is a common practice to use simulation for validating different types of control and planning algorithms. However, the science of how to rigorously integrate simulation and decision models is not well understood and becomes critically important as the complexity and scale of these models increase. In our research, we have developed a methodology for integrating different types of models using a Knowledge Interchange Broker (KIB). In this paper we describe a supply-chain semiconductor application where the KIB has been used as an integral part of developing and deploying a commercial Model Predictive Control model for use in operating a multi-billion dollar supply chain. The simulation based experiments facilitated developing and validating the controller design and data automation for a real-world semiconductor manufacturing system.

关键词： Discrete event simulation Manufacturing systems Predictive models Semiconductor device manufacture Computational modeling Predictive control Virtual manufacturing Application software Manufacturing automation Discrete event systems

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Conceptions of curriculum for simulation education

Conceptions of curriculum for simulation education

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simulation Winter Conference

作者： H. Szczerbicka J. Banks R.V. Rogers T.I. Oren H.S. Sarjoughian B.P. Zeigler Institute for Computer Science Fachbereich Mathematik und Informatik University of Hannover Hanover Germany AutoSimulations A Brooks Automation company Marietta GA USA Department of Engineering Management Virginia Modeling Analysis and Simulation Center Old Dominion University Norfolk VA USA Turkish Science and Technical Research Council Marmara Research Center Information Technologies Research and Development Center Gebze Kocaeli Turkey Arizona Center for Integrative Modeling and Simulation Department of Electrical and Computer Engineering University of Arizona Tucson Tucson AZ USA

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FedECCR: Federated Learning Method with Encoding Comparison and Classification Rectification 19th

FedECCR: Federated Learning Method with Encoding Comparison...

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19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Zeng, Yan Zheng, Hui Wang, Xin Zhang, Beibei Zhou, Mingyao Zhang, Jilin Ren, YongJian School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory for Modeling and Simulation of Complex Systems Ministry of Education Hangzhou310018 China Data Security Governance Zhejiang Engineering Research Center Hangzhou310018 China Zhejiang Lab Hangzhou311100 China Hangzhou Huawei Communication Technology Co. Ltd. Hangzhou310052 China

ISBN: (纸本)9783031545306

Federated learning is a distributed training method that integrates multi-party data information using privacy-preserving technologies through dispersed client data sets to jointly construct a global model under the coordination of a central server. However, in practical applications, there is a high degree of data distribution skewness among clients, which causes the optimization direction of the client models to diverge, resulting in model bias and reducing the accuracy of the global model. Existing methods require the calculation and transmission of much information to correct the optimization direction of the client models, or only roughly limit the deviation of the client models end-to-end, ignoring targeted processing of the internal structure of the model, resulting in unclear improvement effects. To address these problems, we propose a federated optimization algorithm FedECCR based on encoding contrast and classification correction. This algorithm divides the model into an encoder and a classifier. It utilizes prototype contrastive training of the model encoder and unbiased classification correction of the classifier. This approach notably improves the accuracy of the global model while maintaining low communication costs. We conducted experiments on multiple data sets to evaluate the validity of our method, and the quantified results showed that FedECCR can improve the global model classification accuracy by approximately 1% to 6% compared to FedAvg, FedProx, and MOON. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Classification (of information)

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Scalable atomistic simulation algorithms for materials research

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Scientific Programming 2002年第4期10卷 263-270页

作者： Nakano, Aiichiro Kalia, Rajiv K. Vashishta, Priya Campbell, Timothy J. Ogata, Shuji Shimojo, Fuyuki Saini, Subhash Department of Computer Science Dept. of Mat. Sci. and Engineering University of Southern California Los Angeles CA 90089 United States Concurrent Computing Lab. for MS Biol. Comp. and Visualization Center Louisiana State University Baton Rouge LA 70803 United States Department of Applied Sciences Yamaguchi University Ube 755-8611 Japan Faculty of Integrated Arts and Sci. Hiroshima University Higashi-Hiroshima 739-0046 Japan IT Modeling and Simulation NASA Ames Research Center Moffett Field CA 94035-1000 United States

A suite of scalable atomistic simulation programs has been developed for materials research based on space-time multiresolution algorithms. Design and analysis of parallel algorithms are presented for molecular dynamics (MD) simulations and quantum-mechanical (QM) calculations based on the density functional theory. Performance tests have been carried out on 1,088-processor Cray T3E and 1,280-processor IBM SP3 computers. The linear-scaling algorithms have enabled 6.44-billion-atom MD and 111,000-atom QM calculations on 1,024 SP3 processors with parallel efficiency well over 90%. The production-quality programs also feature wavelet-based computational-space decomposition for adaptive load balancing, spacefilling-curve-based adaptive data compression with user-defined error bound for scalable I/O, and octree-based fast visibility culling for immersive and interactive visualization of massive simulation data.

关键词： Parallel algorithms

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Electro-magneto-hydrodynamic Eyring-Powell fluid flow through micro-parallel plates with heat transfer and non-Darcian effects

Electro-magneto-hydrodynamic Eyring-Powell fluid flow throug...

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作者： Bhatti, Muhammad Mubashir Doranehgard, Mohammad Hossein Ellahi, Rahmat College of Mathematics and Systems Science Shandong University of Science and Technology Qingdao China Department of Mechanical and Aerospace Engineering Hong Kong University of Science and Technology Clear Water Bay Hong Kong Center for Modeling & Computer Simulation Research Institute King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Department of Mathematics and Statistics International Islamic University Islamabad Pakistan

The Eyring-Powell fluid flow between two micro-parallel plates in the context of electro-magneto-hydrodynamic is the focus of the article. The Lorentz force, which is generated by the interactions of a vertical magnetic field and an externally imposed horizontal electrical field, is presumed to be unilateral and one-dimensional. Using the Darcy-Brinkman-Forchheimer model, the medium of the micro-parallel plates is assumed to be porous. The energy equation evaluates the effect of viscous dissipation and joule heating as well. To solve the nonlinear coupled differential equations, analytical solutions are derived using the multi-step differential transform method. For the velocity and temperature profiles, the impact of all evolving variables is explored and illustrated in graphs and tables. It can be seen from the graphical results that the Darcy parameter, and also the magnetic field, are oppositional to both fluid motion and temperature profile. Additionally, the thermal Grashof number improves the velocity and temperature profiles of the system. On the velocity and temperature profiles, the outcomes for both fluid parameters are nearly identical. © 2022 John Wiley & Sons Ltd.

关键词： Temperature control

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Parallel Verification of UML Using DiVinE Tool

Parallel Verification of UML Using DiVinE Tool

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International Conference on computer Science and Information Technology

作者： Muhammad Abdul Basit-Ur-Rahim Jamil Ahmad Fahim Arif Department of Computer Software Engineering Military College of Signals National University of Science & Technology Islamabad Pakistan Research Center for Modeling and Simulation Military College of Signals National University of Science & Technology Islamabad Pakistan

ISBN: (纸本)9781467356107

Unified modeling Language is being used for modeling of business processes, real-time systems, embedded systems and hybrid systems. In software engineering, there are different techniques for verification of such systems. Model checking is one of the techniques for the automatic verification of software models. Earlier, these model were verified by sequential model checking tools. For very large complex systems, parallel verification can save verification time. DiVinE is a model checking tool for both CPUs and GPUs clusters to perform parallel linear time logic (LTL) verification of systems. In this paper, we propose a parallel verification methodology for UML models using DiVinE tool. We explain this methodology by the case study example of fuel filling machine.

关键词： UML Verification DiVinE Parallel Verification UML Verification checking tools central processing units Parallel Lines Complex systems hybrid systems Model checking Business process management Software engineering program verification modelling languages FILLING MACHINE Case studies

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