An Introduction To High - Performance Scientific Computing

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High-Performance Scientific Computing: First Jara-HPC Symposium, Jhpcs 2016, Aachen, Germany, October 4-5, 2016, Revised Selected Papers

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Cuda for Engineers: An Introduction to High-Performance Parallel Computing

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Mathematical Modelling and Computing in Physics, Chemistry and Biology Springer, Berlin

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This book  keeps an eye in the direction of applications of advanced and high performance scientific computing in  describing the behavior of natural and constructed systems, e.g. chaos, bifurcation, fractal, Lyapunov exponent, period doubling, Poincaré map, strange attractor etc. With the aid of powerful computers the modem theory of chaos and its geometry, the fractals, and attractors are developed. The concepts of object oriented computing are introduced early in the text and steadily expanded as one progresses through the chapters. The beginning of each chapter is of an introductory nature, followed by practical applications, the discussion of numerical results, theoretical investigations on nonlinear stability and convergence.This is the first complete introduction to process modeling and computing that fully integrates software tools - enabling professionals and students to master critical techniques hands on through computer simulations based on the popular MATLAB environment. The book offers a simple tool for all those oscillations that are travelling through the world, helping them discover its hidden beauty.Many applications as well as results of computer simulations are presented. The center of concern is set on existing as well as emerging continuous methods of investigations useful for researchers, engineers and practitioners active in many and often interdisciplinary fields, where physics, electrochemistry, biology and medicine play a key role. Coverage includes:- Dynamic behavior of nonlinear systems,- Fundamental descriptions of processes exhibiting nonlinear oscillations,- Mechanism and function of structures of nonlinear oscillations' patterns,- Analysis of dynamical oscillations in electric circuits and systems,- Artificial intelligence models of natural systems- Nonlinear oscillations in chemistry, biology and medicine,- Oscillations in mechanics and transport systems,- Oscillations in fractional-order systems,- Energy harvesting systems from the surrounding environment.With an insatiable appetite for exploring the surrounding world and doing research, this book can help readers quickly find ways to use new computers and facilitate the quest for greater knowledge and understanding of reality. The reach of novelty of the book ranges from new mathematical ideas to motivating questions and science issues in many subject areas

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Primer on Scientific Programming with Python Springer-Verlag Berlin and Heidelberg GmbH & Co....

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The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science.§§From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. §§F. H. Wild III, Choice, Vol. 47 (8), April 2010§§Those of us who have learned scientific programming in Python 'on the streets' could be a little jealous of students who have the opportunity to take a course out of Langtangen's Primer."§ John D. Cook, The Mathematical Association of America, September 2011§§This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science.§ Alex Small, IEEE, CiSE Vol. 14 (2), March _ /April 2012 §§"This fourth edition is a§wonderful, inclusive textbook that covers pretty much everything one needs to§know to go from zero to fairly sophisticated scientific programming in Python..."§Joan Horvath, Computing Reviews, March§2015 §§

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Data Science and Predictive Analytics Springer, Berlin

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This textbook integrates important mathematical foundations, efficient computational algorithms, applied statistical inference techniques, and cutting-edge machine learning approaches to address a wide range of crucial biomedical informatics, health analytics applications, and decision science challenges. Each concept in the book includes a rigorous symbolic formulation coupled with computational algorithms and complete end-to-end pipeline protocols implemented as functional R electronic markdown notebooks. These workflows support active learning and demonstrate comprehensive data manipulations, interactive visualizations, and sophisticated analytics. The content includes open problems, state-of-the-art scientific knowledge, ethical integration of heterogeneous scientific tools, and procedures for systematic validation and dissemination of reproducible research findings.Complementary to the enormous challenges related to handling, interrogating, and understanding massive amounts of complex structured and unstructured data, there are unique opportunities that come with access to a wealth of feature-rich, high-dimensional, and time-varying information. The topics covered in Data Science and Predictive Analytics address specific knowledge gaps, resolve educational barriers, and mitigate workforce information-readiness and data science deficiencies. Specifically, it provides a transdisciplinary curriculum integrating core mathematical principles, modern computational methods, advanced data science techniques, model-based machine learning, model-free artificial intelligence, and innovative biomedical applications. The book's fourteen chapters start with an introduction and progressively build foundational skills from visualization to linear modeling, dimensionality reduction, supervised classification, black-box machine learning techniques, qualitative learning methods, unsupervised clustering, model performance assessment, feature selection strategies, longitudinal data analytics, optimization, neural networks, and deep learning. The second edition of the book includes additional learning-based strategies utilizing generative adversarial networks, transfer learning, and synthetic data generation, as well as eight complementary electronic appendices. This textbook is suitable for formal didactic instructor-guided course education, as well as for individual or team-supported self-learning. The material is presented at the upper-division and graduate-level college courses and covers applied and interdisciplinary mathematics, contemporary learning-based data science techniques, computational algorithm development, optimization theory, statistical computing, and biomedical sciences. The analytical techniques and predictive scientific methods described in the book may be useful to a wide range of readers, formal and informal learners, college instructors, researchers, and engineers throughout the academy, industry, government, regulatory, funding, and policy agencies. The supporting book website provides many examples, datasets, functional scripts, complete electronic notebooks, extensive appendices, and additional materials.

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Software Automatic Tuning Springer-Verlag New York Inc.

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Automatic Performance Tuning is a new software paradigm which enables software to be high performance in any computing environment. Its methodologies have been developed over the past decade, and it is now rapidly growing in terms of its scope and applicability, as well as in its scientific knowledge and technological methods. Software developers and researchers in the area of scientific and technical computing, high performance database systems, optimized compilers, high performance systems software, and low-power computing will find this book to be an invaluable reference to this powerful new paradigm.

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Numerical Simulation in Science and Engineering Friedrich Vieweg & Sohn Verlagsgesellschaft mbH

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Founded in April, 1992 and financed by the State of Bavaria and the Bavarian Re search Foundation, the Bavarian Consortium for High Performance Scientific Comput ing (FORTWIHR) consists of more than 40 scientists working in the fields of engineer ing sciences, applied mathematics, and computer science at the Technische Universitat Munchen and at the Friedrich-Alexander-Universitat Erlangen-Nurnberg. Its inter disciplinary concept is based on the recognition that the increasing significance of the yet young discipline High Performance Scientific Computing (HPSC) can only be given due consideration if the technical knowledge of the engineer, the numerical methods of the mathematician, and the computers and up to date methods of computer science are all applied equally. Besides the aim to introduce HPSC into the graduate degree program at the universi ties, there is a strong emphasis on cooperation with industry in all areas of research. Direct cooperation and a transfer of knowledge through training courses and confer ences take place in order to ensure the rapid utilization of all results of research. In this spirit, FORTWIHR annually organizes symposiums on High Performance Scientific Computing and Numerical Simulation in Science and Engineering.

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CUDA Fortran for Scientists and Engineers Elsevier Science & Technology

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CUDA Fortran for Scientists and Engineers shows how high-performance application developers can leverage the power of GPUs using Fortran, the familiar language of scientific computing and supercomputer performance benchmarking. The authors presume no prior parallel computing experience, and cover the basics along with best practices for efficient GPU computing using CUDA Fortran. To help you add CUDA Fortran to existing Fortran codes, the book explains how to understand the target GPU architecture, identify computationally intensive parts of the code, and modify the code to manage the data and parallelism and optimize performance. All of this is done in Fortran, without having to rewrite in another language. Each concept is illustrated with actual examples so you can immediately evaluate the performance of your code in comparison. You can leverage the power of GPU computing with PGI's CUDA Fortran compiler. You can gain insights from members of the CUDA Fortran language development team. It includes multi-GPU programming in CUDA Fortran, covering both peer-to-peer and message passing interface (MPI) approaches.It includes full source code for all the examples and several case studies. You can download source code and slides from the book's companion website.

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MATHEMATICA (R) Book, Version 4 Cambridge University Press

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With over a million users around the world, the Mathematica software system created by Stephen Wolfram has defined the direction of technical computing for the past decade. The enhanced text and hypertext processing and state-of-the-art numerical computation features will ensure that Mathematica 4, takes scientific computing into the next century.The Mathematica Book continues to be the definitive reference guide to this revolutionary software package and is released in this new edition to coincide with the release of the new version of Mathematica.The Mathematica Book is a must-have purchase for anyone who wants to understand the opportunities in science, technology, business, and education made possible by Mathematica 4. This encompasses a broad audience of scientists and mathematicians; engineers; computer professionals; financial analysts; medical researchers; and students at high-school, college, and graduate levels. Written by the creator of the system, The Mathematica Book includes both a tutorial introduction and complete reference information, and contains comprehensive description of how to take advantage of Mathematica's ability to solve myriad technical computing problems and its powerful graphical and typesetting capabilities.

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New Polymeric Products

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New Polymeric Products: Fundamentals, Forming Methods and Applications mainly introduces some applications of polymer materials in new fields, including new products and new processing methods. For instance, the spherical tires using magnetic suspension show many intelligent characteristics; the nanofibrous catalyst layer provided fuel cell better performance; the new bacteriostatic mask will protect strongly from Covid-19. This book is rich in content and creativity. It introduces the development history, characteristics, and existing processing methods of polymer materials, comprehensive and systematic. It is also very suitable for interdisciplinary research related to the polymer. The latest achievements are introduced from the aspects of future travel, energy problems, special environment, lens materials and biomedicine, which are the most concerning areas of human society today. It introduces forming principles, methods, achievements, and development prospects from shallow to profound. It will benefit the researchers and new academic participants and broaden their vision. Further, it will bring creative ideas to the readers by elaborating on the brand-new polymeric products. In detail, the book is divided into six chapters. The first is the introduction, which is divided into three sections. The first section mainly introduces the development history and prospect of polymer materials. The second section introduces polymer materials, including new materials, characteristics, synthesis, naming, and functional. The third section introduces new processing and forming methods, which are introduced from three parts: plastic, rubber, and fiber according to different product types. The second chapter is rubber and spherical tires, which mainly introduces special rubber and its preparation, new bio-based rubber, tire production technology, spherical tire, and its 3D printing preparation method. The third chapter presents the energy-related polymer materials and forming processes, including fuel cell proton exchange membrane, fuel cell fiber catalyst layer, lithium electronic battery diaphragm materials, organic polymer electrode supercapacitors. The fourth chapter is the preparation of high-performance fibers, including carbon fibers, aramid fibers, ultra-high molecular weight polyethylene fibers, nanofibers and their production equipment, and high-performance impact-resistant airbags. The fifth chapter is the new lens materials and molding process, including resin lens materials and new contact lens materials and their preparation process. The sixth chapter is the biomedical application of polymer materials. It mainly introduces the material selection requirements, preparation methods and research results of artificial blood vessels, drug-carrying fibers of antituberculosis bacteria, wound dressing containing dragon's blood, fiber plaster, controlled-release fibers, and bacteriostatic masks. The content is novel and unique. Besides the brand-new products that just or will appear in the market, the whole book is composed of relevant research results of the author's team, general basic knowledge, and the latest research in relevant fields. Combining theory with practice, there are few such books on the market The content is selected and systematic. It introduces basic knowledge such as polymer development history, material characteristics and forming principles. The book arranges trivial contents such as polymer development history in tables to make it clearer and easier to understand. The rich pictures and tables give readers a clearer understanding of products, processing equipment and processes It is suitable for teaching materials full of scientific research ethics and humanistic care. The products introduced in the book are designed to solve the problems encountered in real life, such as energy issues. Combined with current events and adding an antibacterial mask, the new Coronavirus problem that all humanity needs to care about is introduced The cutting-edge chapters, such as the fuel cell assembly and future applications, such as the spherical tire, will ignite the academic reader's new ideas and promote the advancement of their research

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Neural Data Science Elsevier Science Publishing Co Inc

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While MATLAB remains a dominant computer language for scientific computing and analysis in neuroscience, it has become prohibitively expensive. This has created an opportunity for uptake of an alternative yet similar programming language - Python. This volume provides a beginner

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Application of FPGA to Real-Time Machine Learning Springer International Publishing AG

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This book lies at the interface of machine learning - a subfield of computer science that develops algorithms for challenging tasks such as shape or image recognition, where traditional algorithms fail - and photonics - the physical science of light, which underlies many of the optical communications technologies used in our information society. It provides a thorough introduction to reservoir computing and field-programmable gate arrays (FPGAs). Recently, photonic implementations of reservoir computing (a machine learning algorithm based on artificial neural networks) have made a breakthrough in optical computing possible. In this book, the author pushes the performance of these systems significantly beyond what was achieved before. By interfacing a photonic reservoir computer with a high-speed electronic device (an FPGA), the author successfully interacts with the reservoir computer in real time, allowing him to considerably expand its capabilities and range of possible applications. Furthermore, the author draws on his expertise in machine learning and FPGA programming to make progress on a very different problem, namely the real-time image analysis of optical coherence tomography for atherosclerotic arteries.

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CUDA Application Design and Development Elsevier Books

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As the computer industry retools to leverage massively parallel graphics processing units (GPUs), this book is designed to meet the needs of working software developers who need to understand GPU programming with CUDA and increase efficiency in their projects. "CUDA Application Design and Development" starts with an introduction to parallel computing concepts for readers with no previous parallel experience, and focuses on issues of immediate importance to working software developers: achieving high performance, maintaining competitiveness, analyzing CUDA benefits versus costs, and determining application lifespan. This book then details the thought behind CUDA and teaches how to create, analyze, and debug CUDA applications. Throughout, the focus is on software engineering issues: how to use CUDA in the context of existing application code, with existing compilers, languages, software tools, and industry-standard API libraries. Using an approach refined in a series of well-received articles at "Dr Dobb's Journal", author Rob Farber takes the reader step-by-step from fundamentals to implementation, moving from language theory to practical coding.Thsi title includes multiple examples building from simple to more complex applications in four key areas: machine learning, visualization, vision recognition, and mobile computing. It addresses the foundational issues for CUDA development: multi-threaded programming and the different memory hierarchy. It includes teaching chapters designed to give a full understanding of CUDA tools, techniques and structure. It presents CUDA techniques in the context of the hardware they are implemented on as well as other styles of programming that will help readers bridge into the new material.

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Python Data Analytics Springer, Berlin

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Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. This third edition is fully updated for the latest version of Python and its related libraries, and includes coverage of social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulationAuthor Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Third Edition is an invaluable reference with its examples of storing, accessing, and analyzing data.What You'll LearnUnderstand the core concepts of data analysis and the Python ecosystemGo in depth with pandas for reading, writing, and processing dataUse tools and techniques for data visualization and image analysisExamine popular deep learning libraries Keras, Theano,TensorFlow, and PyTorchWho This Book Is ForExperienced Python developers who need to learn about Pythonic tools for data analysis

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