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Author: Ben Youssef, Belgacem
Publisher: IGI Global
ISBN: 1668437961
Category : Computers
Languages : en
Pages : 494
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Book Description
Researchers are increasingly using machine learning (ML) models to analyze data and simulate complex systems and phenomena. Small-scale computing systems used for training, validation, and testing of these ML models are no longer sufficient for grand-challenge problems characterized by large volumes of data generated at a much higher rate than before, surpassing by far the computing capabilities currently available in many cyberinfrastructure platforms. By associating high-performance computing (HPC) with ML environments, scientists and engineers would be able to enhance not only the scalability but also the performance of their predictive ML models. The Handbook of Research on Integrating Machine Learning Into HPC-Based Simulations and Analytics presents recent research efforts in designing and using ML techniques on HPC systems and discusses some of the results achieved thus far by cutting-edge relevant contributions. Covering topics such as data analytics, deep learning, and networking, this major reference work is ideal for computer scientists, academicians, engineers, researchers, scholars, practitioners, librarians, instructors, and students.
Author: Ben Youssef, Belgacem
Publisher: IGI Global
ISBN: 1668437961
Category : Computers
Languages : en
Pages : 494
Get Book Here
Book Description
Researchers are increasingly using machine learning (ML) models to analyze data and simulate complex systems and phenomena. Small-scale computing systems used for training, validation, and testing of these ML models are no longer sufficient for grand-challenge problems characterized by large volumes of data generated at a much higher rate than before, surpassing by far the computing capabilities currently available in many cyberinfrastructure platforms. By associating high-performance computing (HPC) with ML environments, scientists and engineers would be able to enhance not only the scalability but also the performance of their predictive ML models. The Handbook of Research on Integrating Machine Learning Into HPC-Based Simulations and Analytics presents recent research efforts in designing and using ML techniques on HPC systems and discusses some of the results achieved thus far by cutting-edge relevant contributions. Covering topics such as data analytics, deep learning, and networking, this major reference work is ideal for computer scientists, academicians, engineers, researchers, scholars, practitioners, librarians, instructors, and students.
Author: Belgacem Ben Youssef
Publisher:
ISBN: 9781668437964
Category : Computer simulation
Languages : en
Pages : 0
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Book Description
"This edited book aims to present to the reader recent research efforts in designing and using ML techniques on HPC systems, discuss some of the results achieved thus far by cutting-edge relevant contributions. Another objective is to identify research challenges and opportunities in the area spanning the intersection of HPC and ML. In fact, further collaboration between the HPC and ML communities is encouraged for rapid and seamless progress toward an ecosystem that effectively serves both of these communities. Furthermore, new tools and benchmarks are required to overcome the common challenges across HPC and ML applications. The goals of this form of convergence are fourfold: 1. Obtain optimized solutions that show discernible reduction in compute requirements. 2. Facilitate having a more dynamic view of domain sciences. 3. Develop integrated knowledge through interdisciplinary collaboration. 4. Stimulate innovations with deep societal impact through the provisioning of new advances in scientific research spanning many application areas"--
Author: Habib, Maki K.
Publisher: IGI Global
ISBN: 166847686X
Category : Computers
Languages : en
Pages : 435
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Book Description
Smart systems are rapidly evolving and finding ways to influence different aspects of human life, industry, and the environment. Smart systems based on available data should have the ability to predict and be adaptive, which leads to performing reliable, smart actions. Smartness and learning capabilities are essential characteristics describing smart systems besides connectivity and digital virtual cloudification technologies. Perspectives and Considerations on the Evolution of Smart Systems discusses the latest edge development that informs and facilitates the next level of development. It highlights how the evolving technologies and techniques are going to impact the developments in the field considering climate, environment, circular economy, and ecosystems. Covering topics such as dynamic difficulty adjustment, intelligent control, and serious games, this premier reference source is an excellent resource for engineers, computer scientists, IT professionals, developers, data analysts, students and educators of higher education, librarians, researchers, and academicians.
Author: Monaco, Francisco José
Publisher: IGI Global
ISBN: 1668447878
Category : Computers
Languages : en
Pages : 358
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Book Description
Since its emergence in the mid-1980s through the protagonism of free software and open source movements, the concept of freely shareable technology has steadily established itself in the following decades to enter the 21st century as a leading industrial paradigm. From the original ambit of software technology, the principles of collaborative construction of publicly accessible knowledge grounding the open source paradigm have been extended to embrace any intellectual artifact made available under non-exclusive rights of utilization, development, and distribution. It is noteworthy, however, that whilst on one hand it is not difficult to enumerate advantages of the use of open source products by individuals and organizations—whether related to cost reduction, socio-technological inclusion, governance of technology development, security and privacy transparency, among others—on the other hand, it is not as immediate to identify their motivation to develop open source technology. While there may surely be initiatives driven by either ethical grounds, personal avocation, or public policies, those reasons alone do not explain the lasting success of many large community-driven projects, nor why large commercial enterprises massively invest in open source development. Business Models and Strategies for Open Source Projects investigates the rationales and the strategy underlying companies’ decisions to produce and release open source products as well as which business models have succeeded. Covering topics such as embedded systems, open source ecosystems, and software companies, this premier reference source is a valuable resource for entrepreneurs, business leaders and managers, students and educators of higher education, librarians, software developers, researchers, and academicians.
Author: Revathy, G.
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 393
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Book Description
The interaction of various service models, including edge computing and cloud computing, are quickly changing to better support microservices. This intricate weave of technology and information sharing is necessary to build systems that run faster and more efficiently. The interplay between these computing methods and microservices is emerging as the field of Osmotic Computing. Experts can now embark on an intellectual journey into data-driven exploration and ingenuity with the guidance of the book, Advanced Applications in Osmotic Computing. As ethical considerations become rising concerns, the potential biases, privacy encumbrances, and equitable conundrums of osmotic computing are investigated. This book offers judicious strategies to navigate these quandaries conscientiously, adding a layer of responsibility to the discourse. Within these pages, the very fabric of understanding in IoT, Cloud, Edge, Fog, and Machine Learning is redefined, marking a pivotal shift in the paradigm of technological comprehension. This book is an epicenter for the latest evolutions in osmotic computing, unfurling unconventional methodologies that shape the trajectory of data-driven decision-making. Readers will plunge into the theoretical bedrock, simultaneously witnessing pragmatic applications that adeptly bridge the schism between the theoretical constructs and pragmatic realization. The intended audience is multifaceted, encompassing data scientists, machine learning engineers, researchers, academics, educators, students, industry practitioners, interdisciplinary experts, and technology and business leaders.
Author: Singla, Babita
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 239
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Book Description
Academia is grappling with a pressing challenge in the 21st century that mirrors the seismic shifts taking place in the business world. These two sides of one issue are both asking the same question; how can we seamlessly incorporate metaverse platforms into the complex web of omnichannel business models? Scholars and academics are confronted with the urgent need to understand and adapt to this new digital frontier. With the rise of metaverse technologies, the boundaries between physical and virtual realms are blurring, making it increasingly vital for scholars to bridge the gap between theory and practical application. This challenge not only touches on the fields of marketing, finance, HR, supply chain, and economics but also extends to the broader implications for industries and customer experiences as we know them. At the forefront of addressing this formidable challenge is Omnichannel Approach to Co-Creating Customer Experiences Through Metaverse Platforms. This groundbreaking book tackles this pressing issue head-on, offering a comprehensive solution to the challenges that academic scholars face. By providing a holistic perspective that covers a multitude of disciplines, the book demystifies the complexities of integrating metaverse platforms into omnichannel business models. It offers a roadmap, not only for understanding these emerging technologies but also for harnessing their transformative power to create immersive and empowered customer experiences.
Author: Michèle Weiland
Publisher: Springer Nature
ISBN: 3031737164
Category :
Languages : en
Pages : 493
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Book Description
Author: Jeffrey Nichols
Publisher: Springer Nature
ISBN: 3030964981
Category : Computers
Languages : en
Pages : 474
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Book Description
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.
Author: Laurens M. Bouwer
Publisher: Springer Nature
ISBN: 3030995461
Category : Science
Languages : en
Pages : 158
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Book Description
This open access book presents the results of three years collaboration between earth scientists and data scientist, in developing and applying data science methods for scientific discovery. The book will be highly beneficial for other researchers at senior and graduate level, interested in applying visual data exploration, computational approaches and scientifc workflows.
Author: Gintautas Dzemyda
Publisher: Springer Nature
ISBN: 3031244532
Category : Technology & Engineering
Languages : en
Pages : 260
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Book Description
This book provides an overview of a wide range of relevant applications and reveals how to solve them. Many of the latest applications in finance, technology, education, medicine and other important and relevant fields are data-driven. The volumes of data are enormous. Specific methods need to be developed or adapted to solve a particular problem. It illustrates data science in applications. These applications have in common the discovery of knowledge in data and the use of this knowledge to make real decisions. The set of examples presented serves as a recipe book for their direct application to similar problems or as a guide for the development of new, more sophisticated approaches. The intended readership is data scientists looking for appropriate solutions to their problems. In addition, the examples provided serves as material for lectures at universities.
