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| Author | : Jue Wang |
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| Release | : 2016 |
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| Author | : Jue Wang |
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| Total Pages | : 0 |
| Release | : 2017 |
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| Author | : Vinai K. Singh |
| Publisher | : Springer |
| Total Pages | : 503 |
| Release | : 2019-02-14 |
| Genre | : Computers |
| ISBN | : 3030024873 |
This special volume of the conference will be of immense use to the researchers and academicians. In this conference, academicians, technocrats and researchers will get an opportunity to interact with eminent persons in the field of Applied Mathematics and Scientific Computing. The topics to be covered in this International Conference are comprehensive and will be adequate for developing and understanding about new developments and emerging trends in this area. High-Performance Computing (HPC) systems have gone through many changes during the past two decades in their architectural design to satisfy the increasingly large-scale scientific computing demand. Accurate, fast, and scalable performance models and simulation tools are essential for evaluating alternative architecture design decisions for the massive-scale computing systems. This conference recounts some of the influential work in modeling and simulation for HPC systems and applications, identifies some of the major challenges, and outlines future research directions which we believe are critical to the HPC modeling and simulation community.
| Author | : Joanna Kołodziej |
| Publisher | : Springer |
| Total Pages | : 171 |
| Release | : 2018-01-30 |
| Genre | : Technology & Engineering |
| ISBN | : 3319737678 |
This book consists of eight chapters, five of which provide a summary of the tutorials and workshops organised as part of the cHiPSet Summer School: High-Performance Modelling and Simulation for Big Data Applications Cost Action on “New Trends in Modelling and Simulation in HPC Systems,” which was held in Bucharest (Romania) on September 21–23, 2016. As such it offers a solid foundation for the development of new-generation data-intensive intelligent systems. Modelling and simulation (MS) in the big data era is widely considered the essential tool in science and engineering to substantiate the prediction and analysis of complex systems and natural phenomena. MS offers suitable abstractions to manage the complexity of analysing big data in various scientific and engineering domains. Unfortunately, big data problems are not always easily amenable to efficient MS over HPC (high performance computing). Further, MS communities may lack the detailed expertise required to exploit the full potential of HPC solutions, and HPC architects may not be fully aware of specific MS requirements. The main goal of the Summer School was to improve the participants’ practical skills and knowledge of the novel HPC-driven models and technologies for big data applications. The trainers, who are also the authors of this book, explained how to design, construct, and utilise the complex MS tools that capture many of the HPC modelling needs, from scalability to fault tolerance and beyond. In the final three chapters, the book presents the first outcomes of the school: new ideas and novel results of the research on security aspects in clouds, first prototypes of the complex virtual models of data in big data streams and a data-intensive computing framework for opportunistic networks. It is a valuable reference resource for those wanting to start working in HPC and big data systems, as well as for advanced researchers and practitioners.
| Author | : Joanna Kołodziej |
| Publisher | : Springer |
| Total Pages | : 364 |
| Release | : 2019-03-25 |
| Genre | : Computers |
| ISBN | : 3030162729 |
This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.
| Author | : Maciej Pietrzyk |
| Publisher | : Butterworth-Heinemann |
| Total Pages | : 388 |
| Release | : 2015-07-14 |
| Genre | : Technology & Engineering |
| ISBN | : 0124167241 |
Computational Materials Engineering: Achieving High Accuracy and Efficiency in Metals Processing Simulations describes the most common computer modeling and simulation techniques used in metals processing, from so-called "fast" models to more advanced multiscale models, also evaluating possible methods for improving computational accuracy and efficiency. Beginning with a discussion of conventional fast models like internal variable models for flow stress and microstructure evolution, the book moves on to advanced multiscale models, such as the CAFÉ method, which give insights into the phenomena occurring in materials in lower dimensional scales. The book then delves into the various methods that have been developed to deal with problems, including long computing times, lack of proof of the uniqueness of the solution, difficulties with convergence of numerical procedures, local minima in the objective function, and ill-posed problems. It then concludes with suggestions on how to improve accuracy and efficiency in computational materials modeling, and a best practices guide for selecting the best model for a particular application. Presents the numerical approaches for high-accuracy calculations Provides researchers with essential information on the methods capable of exact representation of microstructure morphology Helpful to those working on model classification, computing costs, heterogeneous hardware, modeling efficiency, numerical algorithms, metamodeling, sensitivity analysis, inverse method, clusters, heterogeneous architectures, grid environments, finite element, flow stress, internal variable method, microstructure evolution, and more Discusses several techniques to overcome modeling and simulation limitations, including distributed computing methods, (hyper) reduced-order-modeling techniques, regularization, statistical representation of material microstructure, and the Gaussian process Covers both software and hardware capabilities in the area of improved computer efficiency and reduction of computing time
| Author | : Stephen A. Jarvis |
| Publisher | : Springer |
| Total Pages | : 303 |
| Release | : 2014-09-30 |
| Genre | : Computers |
| ISBN | : 3319102141 |
This book constitutes the refereed proceedings of the 4th International Workshop, PMBS 2013 in Denver, CO, USA in November 2013. The 14 papers presented in this volume were carefully reviewed and selected from 37 submissions. The selected articles broadly cover topics on massively parallel and high-performance simulations, modeling and simulation, model development and analysis, performance optimization, power estimation and optimization, high performance computing, reliability, performance analysis, and network simulations.
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| Release | : 2007 |
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| Total Pages | : 9 |
| Release | : 1993 |
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Advanced mathematical techniques and computer simulation play a major role in providing enhanced understanding of conventional materials processing operations such as welding and joining. Many of these numerical models are highly compute-intensive. It is not unusual for an analysis to require several hours of computational time on current supercomputers despite the simplicity of the models being studied. As computer simulations and materials databases grow in complexity, massively parallel computers have become important tools. This paper briefly describes massively parallel computational research at the ORNL with the objective of providing fundamental insight into the welding process.
| Author | : Hans Georg Bock |
| Publisher | : Springer Nature |
| Total Pages | : 402 |
| Release | : 2020-12-01 |
| Genre | : Mathematics |
| ISBN | : 3030552403 |
This proceedings volume highlights a selection of papers presented at the 7th International Conference on High Performance Scientific Computing, which took place in Hanoi, Vietnam, during March 19-23, 2018. The conference has been organized by the Institute of Mathematics of the Vietnam Academy of Science and Technology, the Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University and the Vietnam Institute for Advanced Study in Mathematics. The contributions cover a broad, interdisciplinary spectrum of scientific computing and showcase recent advances in theory, methods, and practical applications. Subjects covered include numerical simulation, methods for optimization and control, machine learning, parallel computing and software development, as well as the applications of scientific computing in mechanical engineering, airspace engineering, environmental physics, decision making, hydrogeology, material science and electric circuits.
