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This book constitutes the revised selected papers of the 21st Smoky Mountains Computational Sciences and Engineering Conference, SMC 2021, held in Oak Ridge, TN, USA*, in October 2021. The 33 full papers and 3 short papers presented were carefully reviewed and selected from a total of 88 submissions. The papers are organized in topical sections of computational applications: converged HPC and artificial intelligence; advanced computing applications: use cases that combine multiple aspects of data and modeling; advanced computing systems and software: connecting instruments from edge to supercomputers; deploying advanced computing platforms: on the road to a converged ecosystem; scientific data challenges. *The conference was held virtually due to the COVID-19 pandemic.
Book Synopsis Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation by : Jeffrey Nichols
Download or read book Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation written by Jeffrey Nichols and published by Springer Nature. This book was released on 2022-03-09 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the revised selected papers of the 21st Smoky Mountains Computational Sciences and Engineering Conference, SMC 2021, held in Oak Ridge, TN, USA*, in October 2021. The 33 full papers and 3 short papers presented were carefully reviewed and selected from a total of 88 submissions. The papers are organized in topical sections of computational applications: converged HPC and artificial intelligence; advanced computing applications: use cases that combine multiple aspects of data and modeling; advanced computing systems and software: connecting instruments from edge to supercomputers; deploying advanced computing platforms: on the road to a converged ecosystem; scientific data challenges. *The conference was held virtually due to the COVID-19 pandemic.
This book constitutes the revised selected papers of the 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, held in Oak Ridge, TN, USA*, in August 2020. The 36 full papers and 1 short paper presented were carefully reviewed and selected from a total of 94 submissions. The papers are organized in topical sections of computational applications: converged HPC and artificial intelligence; system software: data infrastructure and life cycle; experimental/observational applications: use cases that drive requirements for AI and HPC convergence; deploying computation: on the road to a converged ecosystem; scientific data challenges. *The conference was held virtually due to the COVID-19 pandemic.
Book Synopsis Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI by : Jeffrey Nichols
Download or read book Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI written by Jeffrey Nichols and published by Springer Nature. This book was released on 2020-12-22 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the revised selected papers of the 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, held in Oak Ridge, TN, USA*, in August 2020. The 36 full papers and 1 short paper presented were carefully reviewed and selected from a total of 94 submissions. The papers are organized in topical sections of computational applications: converged HPC and artificial intelligence; system software: data infrastructure and life cycle; experimental/observational applications: use cases that drive requirements for AI and HPC convergence; deploying computation: on the road to a converged ecosystem; scientific data challenges. *The conference was held virtually due to the COVID-19 pandemic.
This book constitutes the refereed proceedings of the 22nd Smoky Mountains Computational Sciences and Engineering Conference on Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, SMC 2022, held virtually, during August 23–25, 2022. The 24 full papers included in this book were carefully reviewed and selected from 74 submissions. They were organized in topical sections as follows: foundational methods enabling science in an integrated ecosystem; science and engineering applications requiring and motivating an integrated ecosystem; systems and software advances enabling an integrated science and engineering ecosystem; deploying advanced technologies for an integrated science and engineering ecosystem; and scientific data challenges.
Book Synopsis Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation by : Kothe Doug
Download or read book Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation written by Kothe Doug and published by Springer Nature. This book was released on 2023-01-17 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 22nd Smoky Mountains Computational Sciences and Engineering Conference on Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, SMC 2022, held virtually, during August 23–25, 2022. The 24 full papers included in this book were carefully reviewed and selected from 74 submissions. They were organized in topical sections as follows: foundational methods enabling science in an integrated ecosystem; science and engineering applications requiring and motivating an integrated ecosystem; systems and software advances enabling an integrated science and engineering ecosystem; deploying advanced technologies for an integrated science and engineering ecosystem; and scientific data challenges.
Convergence has been a key topic of discussion about the future of cyberinfrastructure for science and engineering research. Convergence refers both to the combined use of simulation and data-centric techniques in science and engineering research and the possibilities for a single type of cyberinfrastructure to support both techniques. The National Academies of Science, Engineering, and Medicine convened a Workshop on Converging Simulation and Data-Driven Science on May 10, 2018, in Washington, D.C. The workshop featured speakers from universities, national laboratories, technology companies, and federal agencies who addressed the potential benefits and limitations of convergence as they relate to scientific needs, technological capabilities, funding structures, and system design requirements. This publication summarizes the presentations and discussions from the workshop.
Book Synopsis Opportunities from the Integration of Simulation Science and Data Science by : National Academies of Sciences, Engineering, and Medicine
Download or read book Opportunities from the Integration of Simulation Science and Data Science written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-07-31 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: Convergence has been a key topic of discussion about the future of cyberinfrastructure for science and engineering research. Convergence refers both to the combined use of simulation and data-centric techniques in science and engineering research and the possibilities for a single type of cyberinfrastructure to support both techniques. The National Academies of Science, Engineering, and Medicine convened a Workshop on Converging Simulation and Data-Driven Science on May 10, 2018, in Washington, D.C. The workshop featured speakers from universities, national laboratories, technology companies, and federal agencies who addressed the potential benefits and limitations of convergence as they relate to scientific needs, technological capabilities, funding structures, and system design requirements. This publication summarizes the presentations and discussions from the workshop.
This is an open access book. The 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) was held on April 28–30, 2023 at the Xiamen, China. With the development of science and technology, information technology and information resources should be actively developed and fully applied in all fields of education and teaching, so as to promote the modernization of education and cultivate talents to meet the needs of society. From the technical point of view, the basic characteristics of educational informatization are digitalization, networking, intelligentization and multi-media. From the perspective of education, the basic characteristics of educational information are openness, sharing, interaction and cooperation. With the advantage of the network, it can provide students with a large amount of information and knowledge by combining different knowledge and information from various aspects in a high frequency. Therefore, we have intensified efforts to reform the traditional teaching methods and set up a new teaching concept, from the interaction between teachers and students in the past to the sharing between students. In short, it forms a sharing learning mode. For all students, strive to achieve students' learning independence, initiative and creativity. To sum up, we will provide a quick exchange platform between education and information technology, so that more scholars in related fields can share and exchange new ideas. The 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) was held on April 28-30, 2023 in Xiamen, China. IEIT 2023 is to bring together innovative academics and industrial experts in the field of Internet, Education and Information Technology to a common forum. The primary goal of the conference is to promote research and developmental activities in Internet, Education and Information Technology and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in international conference on Internet, Education and Information Technology and related areas.
Book Synopsis Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) by : Dhananjay Kumar
Download or read book Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) written by Dhananjay Kumar and published by Springer Nature. This book was released on 2023-09-01 with total page 1409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an open access book. The 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) was held on April 28–30, 2023 at the Xiamen, China. With the development of science and technology, information technology and information resources should be actively developed and fully applied in all fields of education and teaching, so as to promote the modernization of education and cultivate talents to meet the needs of society. From the technical point of view, the basic characteristics of educational informatization are digitalization, networking, intelligentization and multi-media. From the perspective of education, the basic characteristics of educational information are openness, sharing, interaction and cooperation. With the advantage of the network, it can provide students with a large amount of information and knowledge by combining different knowledge and information from various aspects in a high frequency. Therefore, we have intensified efforts to reform the traditional teaching methods and set up a new teaching concept, from the interaction between teachers and students in the past to the sharing between students. In short, it forms a sharing learning mode. For all students, strive to achieve students' learning independence, initiative and creativity. To sum up, we will provide a quick exchange platform between education and information technology, so that more scholars in related fields can share and exchange new ideas. The 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) was held on April 28-30, 2023 in Xiamen, China. IEIT 2023 is to bring together innovative academics and industrial experts in the field of Internet, Education and Information Technology to a common forum. The primary goal of the conference is to promote research and developmental activities in Internet, Education and Information Technology and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in international conference on Internet, Education and Information Technology and related areas.
The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.
Book Synopsis Big Data Technologies and Applications by : Borko Furht
Download or read book Big Data Technologies and Applications written by Borko Furht and published by Springer. This book was released on 2016-09-16 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.
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.
Book Synopsis Modeling and Simulation in HPC and Cloud Systems by : Joanna Kołodziej
Download or read book Modeling and Simulation in HPC and Cloud Systems written by Joanna Kołodziej and published by Springer. This book was released on 2018-01-30 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
This volume constitutes the proceedings of the 18th Asia Simulation Conference, AsiaSim 2018, held in Kyoto, Japan, in August 2018. The 45 revised full papers presented in this volume were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections on modeling and simulation technology; soft computing and machine learning; high performance computing and cloud computing; simulation technology for industry; simulation technology for intelligent society; simulation of instrumentation and control application; computational mathematics and computational science; flow simulation; visualization and computer vision to support simulation.
Book Synopsis Methods and Applications for Modeling and Simulation of Complex Systems by : Liang Li
Download or read book Methods and Applications for Modeling and Simulation of Complex Systems written by Liang Li and published by Springer. This book was released on 2018-10-17 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the proceedings of the 18th Asia Simulation Conference, AsiaSim 2018, held in Kyoto, Japan, in August 2018. The 45 revised full papers presented in this volume were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections on modeling and simulation technology; soft computing and machine learning; high performance computing and cloud computing; simulation technology for industry; simulation technology for intelligent society; simulation of instrumentation and control application; computational mathematics and computational science; flow simulation; visualization and computer vision to support simulation.
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.
Book Synopsis High-Performance Modelling and Simulation for Big Data Applications by : Joanna Kołodziej
Download or read book High-Performance Modelling and Simulation for Big Data Applications written by Joanna Kołodziej and published by Springer. This book was released on 2019-03-25 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas.
Book Synopsis Big Data in Engineering Applications by : Sanjiban Sekhar Roy
Download or read book Big Data in Engineering Applications written by Sanjiban Sekhar Roy and published by Springer. This book was released on 2018-05-02 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas.
