Systems Simulation and Modeling for Cloud Computing and Big Data Applications

Systems Simulation and Modeling for Cloud Computing and Big Data Applications
Author: Dinesh Peter,Steven L. Fernandes
Publsiher: Academic Press
Total Pages: 182
Release: 2020-02-26
ISBN 10: 0128197803
ISBN 13: 9780128197806
Language: EN, FR, DE, ES & NL

Systems Simulation and Modeling for Cloud Computing and Big Data Applications Book Review:

Systems Simulation and Modelling for Cloud Computing and Big Data Applications provides readers with the most current approaches to solving problems through the use of models and simulations, presenting SSM based approaches to performance testing and benchmarking that offer significant advantages. For example, multiple big data and cloud application developers and researchers can perform tests in a controllable and repeatable manner. Inspired by the need to analyze the performance of different big data processing and cloud frameworks, researchers have introduced several benchmarks, including BigDataBench, BigBench, HiBench, PigMix, CloudSuite and GridMix, which are all covered in this book. Despite the substantial progress, the research community still needs a holistic, comprehensive big data SSM to use in almost every scientific and engineering discipline involving multidisciplinary research. SSM develops frameworks that are applicable across disciplines to develop benchmarking tools that are useful in solutions development. Examines the methodology and requirements of benchmarking big data and cloud computing tools, advances in big data frameworks and benchmarks for large-scale data analytics, and frameworks for benchmarking and predictive analytics in big data deployment Discusses applications using big data benchmarks, such as BigDataBench, BigBench, HiBench, MapReduce, HPCC, ECL, HOBBIT, GridMix and PigMix, and applications using big data frameworks, such as Hadoop, Spark, Samza, Flink and SQL frameworks Covers development of big data benchmarks to evaluate workloads in state-of-the-practice heterogeneous hardware platforms, advances in modeling and simulation tools for performance evaluation, security problems and scalable cloud computing environments

Modeling and Simulation in HPC and Cloud Systems

Modeling and Simulation in HPC and Cloud Systems
Author: Joanna Kołodziej,Florin Pop,Ciprian Dobre
Publsiher: Springer
Total Pages: 155
Release: 2018-01-30
ISBN 10: 3319737678
ISBN 13: 9783319737676
Language: EN, FR, DE, ES & NL

Modeling and Simulation in HPC and Cloud Systems Book Review:

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.

Strategic Engineering for Cloud Computing and Big Data Analytics

Strategic Engineering for Cloud Computing and Big Data Analytics
Author: Amin Hosseinian-Far,Muthu Ramachandran,Dilshad Sarwar
Publsiher: Springer
Total Pages: 226
Release: 2017-03-15
ISBN 10: 3319524917
ISBN 13: 9783319524917
Language: EN, FR, DE, ES & NL

Strategic Engineering for Cloud Computing and Big Data Analytics Book Review:

This book demonstrates the use of a wide range of strategic engineering concepts, theories and applied case studies to improve the safety, security and sustainability of complex and large-scale engineering and computer systems. It first details the concepts of system design, life cycle, impact assessment and security to show how these ideas can be brought to bear on the modeling, analysis and design of information systems with a focused view on cloud-computing systems and big data analytics. This informative book is a valuable resource for graduate students, researchers and industry-based practitioners working in engineering, information and business systems as well as strategy.

High Performance Modelling and Simulation for Big Data Applications

High Performance Modelling and Simulation for Big Data Applications
Author: Joanna Kołodziej,Horacio González-Vélez
Publsiher: Springer
Total Pages: 352
Release: 2019-03-25
ISBN 10: 3030162729
ISBN 13: 9783030162726
Language: EN, FR, DE, ES & NL

High Performance Modelling and Simulation for Big Data Applications Book Review:

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.

High Performance Modelling and Simulation for Big Data Applications

High Performance Modelling and Simulation for Big Data Applications
Author: Joanna Kołodziej,Horacio González-Vélez
Publsiher: Springer
Total Pages: 352
Release: 2019-03-25
ISBN 10: 3030162729
ISBN 13: 9783030162726
Language: EN, FR, DE, ES & NL

High Performance Modelling and Simulation for Big Data Applications Book Review:

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.

Big Data

Big Data
Author: Kuan-Ching Li,Hai Jiang,Laurence T. Yang,Alfredo Cuzzocrea
Publsiher: CRC Press
Total Pages: 498
Release: 2015-09-15
ISBN 10: 1498760406
ISBN 13: 9781498760409
Language: EN, FR, DE, ES & NL

Big Data Book Review:

As today’s organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages. Presenting the contributions of leading experts in their respective fields, Big Data: Algorithms, Analytics, and Applications bridges the gap between the vastness of Big Data and the appropriate computational methods for scientific and social discovery. It covers fundamental issues about Big Data, including efficient algorithmic methods to process data, better analytical strategies to digest data, and representative applications in diverse fields, such as medicine, science, and engineering. The book is organized into five main sections: Big Data Management—considers the research issues related to the management of Big Data, including indexing and scalability aspects Big Data Processing—addresses the problem of processing Big Data across a wide range of resource-intensive computational settings Big Data Stream Techniques and Algorithms—explores research issues regarding the management and mining of Big Data in streaming environments Big Data Privacy—focuses on models, techniques, and algorithms for preserving Big Data privacy Big Data Applications—illustrates practical applications of Big Data across several domains, including finance, multimedia tools, biometrics, and satellite Big Data processing Overall, the book reports on state-of-the-art studies and achievements in algorithms, analytics, and applications of Big Data. It provides readers with the basis for further efforts in this challenging scientific field that will play a leading role in next-generation database, data warehousing, data mining, and cloud computing research. It also explores related applications in diverse sectors, covering technologies for media/data communication, elastic media/data storage, cross-network media/data fusion, and SaaS.

Simulation for Cyber Physical Systems Engineering

Simulation for Cyber Physical Systems Engineering
Author: José L. Risco Martín,Saurabh Mittal,Tuncer Ören
Publsiher: Springer Nature
Total Pages: 451
Release: 2020-11-07
ISBN 10: 3030519090
ISBN 13: 9783030519094
Language: EN, FR, DE, ES & NL

Simulation for Cyber Physical Systems Engineering Book Review:

This comprehensive book examines a range of examples, prepared by a diverse group of academic and industry practitioners, which demonstrate how cloud-based simulation is being extensively used across many disciplines, including cyber-physical systems engineering. This book is a compendium of the state of the art in cloud-based simulation that instructors can use to inform the next generation. It highlights the underlying infrastructure, modeling paradigms, and simulation methodologies that can be brought to bear to develop the next generation of systems for a highly connected society. Such systems, aptly termed cyber-physical systems (CPS), are now widely used in e.g. transportation systems, smart grids, connected vehicles, industrial production systems, healthcare, education, and defense. Modeling and simulation (M&S), along with big data technologies, are at the forefront of complex systems engineering research. The disciplines of cloud-based simulation and CPS engineering are evolving at a rapid pace, but are not optimally supporting each other’s advancement. This book brings together these two communities, which already serve multi-disciplinary applications. It provides an overview of the simulation technologies landscape, and of infrastructure pertaining to the use of cloud-based environments for CPS engineering. It covers the engineering, design, and application of cloud simulation technologies and infrastructures applicable for CPS engineering. The contributions share valuable lessons learned from developing real-time embedded and robotic systems deployed through cloud-based infrastructures for application in CPS engineering and IoT-enabled society. The coverage incorporates cloud-based M&S as a medium for facilitating CPS engineering and governance, and elaborates on available cloud-based M&S technologies and their impacts on specific aspects of CPS engineering.

Big Data

Big Data
Author: Rajkumar Buyya,Rodrigo N. Calheiros,Amir Vahid Dastjerdi
Publsiher: Morgan Kaufmann
Total Pages: 494
Release: 2016-06-07
ISBN 10: 0128093463
ISBN 13: 9780128093467
Language: EN, FR, DE, ES & NL

Big Data Book Review:

Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications. To help realize Big Data’s full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues. Covers computational platforms supporting Big Data applications Addresses key principles underlying Big Data computing Examines key developments supporting next generation Big Data platforms Explores the challenges in Big Data computing and ways to overcome them Contains expert contributors from both academia and industry

Encyclopedia of Cloud Computing

Encyclopedia of Cloud Computing
Author: San Murugesan,Irena Bojanova
Publsiher: John Wiley & Sons
Total Pages: 744
Release: 2016-08-01
ISBN 10: 1118821971
ISBN 13: 9781118821978
Language: EN, FR, DE, ES & NL

Encyclopedia of Cloud Computing Book Review:

The Encyclopedia of Cloud Computing comprehensively cover all aspects of cloud computing. It provides IT professionals, educators, researchers and students a compendium of cloud computing knowledge – concepts, principles, architecture, technology, security, privacy and regulatory compliance, applications, adoption, business, and social and legal aspects. Containing contributions from a spectrum of subject matter experts in industry and academia, this unique publication also addresses questions related to technological trends and developments, research opportunities, best practices, standards, and cloud adoption that stakeholders might have in the context of development, operation, management, and use of clouds, providing multiple perspectives. Furthermore, itexamines cloud computing's impact now and in the future. The encyclopedia is logically organised into 10 sections amd each section into a maximum of 12 chapters, each covering a major topic/area with cross-references as required. The chapters consist of tables, illustrations, side-bars as appropriate. In additon, it also includes highlights at the beginning of each chapter, as well as backend material references and additional resources for further information (including relevant websites, videos and software tools). The encyclopedia also contains illustrations and case studies. A list of acronyms are provided in the beginning and a comprehensive and informative glossary at the end.

Data Processing Techniques and Applications for Cyber Physical Systems DPTA 2019

Data Processing Techniques and Applications for Cyber Physical Systems  DPTA 2019
Author: Chuanchao Huang,Yu-Wei Chan,Neil Yen
Publsiher: Springer Nature
Total Pages: 2059
Release: 2020-02-03
ISBN 10: 9811514682
ISBN 13: 9789811514685
Language: EN, FR, DE, ES & NL

Data Processing Techniques and Applications for Cyber Physical Systems DPTA 2019 Book Review:

This book covers cutting-edge and advanced research on data processing techniques and applications for Cyber-Physical Systems. Gathering the proceedings of the International Conference on Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019), held in Shanghai, China on November 15–16, 2019, it examines a wide range of topics, including: distributed processing for sensor data in CPS networks; approximate reasoning and pattern recognition for CPS networks; data platforms for efficient integration with CPS networks; and data security and privacy in CPS networks. Outlining promising future research directions, the book offers a valuable resource for students, researchers and professionals alike, while also providing a useful reference guide for newcomers to the field.

Systems Modeling Methodologies and Tools

Systems Modeling  Methodologies and Tools
Author: Antonio Puliafito,Kishor S. Trivedi
Publsiher: Springer
Total Pages: 323
Release: 2018-10-16
ISBN 10: 3319923781
ISBN 13: 9783319923789
Language: EN, FR, DE, ES & NL

Systems Modeling Methodologies and Tools Book Review:

This book covers ideas, methods, algorithms, and tools for the in-depth study of the performance and reliability of dependable fault-tolerant systems. The chapters identify the current challenges that designers and practitioners must confront to ensure the reliability, availability, and performance of systems, with special focus on their dynamic behaviors and dependencies. Topics include network calculus, workload and scheduling; simulation, sensitivity analysis and applications; queuing networks analysis; clouds, federations and big data; and tools. This collection of recent research exposes system researchers, performance analysts, and practitioners to a spectrum of issues so that they can address these challenges in their work.

Intelligence in Big Data Technologies Beyond the Hype

Intelligence in Big Data Technologies   Beyond the Hype
Author: J. Dinesh Peter,Steven L. Fernandes,Amir H. Alavi
Publsiher: Springer Nature
Total Pages: 636
Release: 2020-07-25
ISBN 10: 9811552851
ISBN 13: 9789811552854
Language: EN, FR, DE, ES & NL

Intelligence in Big Data Technologies Beyond the Hype Book Review:

This book is a compendium of the proceedings of the International Conference on Big-Data and Cloud Computing. The papers discuss the recent advances in the areas of big data analytics, data analytics in cloud, smart cities and grid, etc. This volume primarily focuses on the application of knowledge which promotes ideas for solving problems of the society through cutting-edge big-data technologies. The essays featured in this proceeding provide novel ideas that contribute for the growth of world class research and development. It will be useful to researchers in the area of advanced engineering sciences.

Big Data Management and Processing

Big Data Management and Processing
Author: Kuan-Ching Li,Hai Jiang,Albert Y. Zomaya
Publsiher: CRC Press
Total Pages: 469
Release: 2017-05-19
ISBN 10: 1498768083
ISBN 13: 9781498768085
Language: EN, FR, DE, ES & NL

Big Data Management and Processing Book Review:

From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies." ---Sartaj Sahni, University of Florida, USA "Big Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students, researchers and seasoned practitioners in Big Data fields. --Hai Jin, Huazhong University of Science and Technology, China Big Data Management and Processing explores a range of big data related issues and their impact on the design of new computing systems. The twenty-one chapters were carefully selected and feature contributions from several outstanding researchers. The book endeavors to strike a balance between theoretical and practical coverage of innovative problem solving techniques for a range of platforms. It serves as a repository of paradigms, technologies, and applications that target different facets of big data computing systems. The first part of the book explores energy and resource management issues, as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co-scheduling for high performance computing applications. The second part of the book includes comprehensive coverage of Hadoop and Spark, along with security, privacy, and trust challenges and solutions. The latter part of the book covers mining and clustering in Big Data, and includes applications in genomics, hospital big data processing, and vehicular cloud computing. The book also analyzes funding for Big Data projects.

Advances in Modeling and Simulation

Advances in Modeling and Simulation
Author: Andreas Tolk,John Fowler,Guodong Shao,Enver Yücesan
Publsiher: Springer
Total Pages: 355
Release: 2017-08-27
ISBN 10: 3319641824
ISBN 13: 9783319641829
Language: EN, FR, DE, ES & NL

Advances in Modeling and Simulation Book Review:

​This broad-ranging text/reference presents a fascinating review of the state of the art of modeling and simulation, highlighting both the seminal work of preeminent authorities and exciting developments from promising young researchers in the field. Celebrating the 50th anniversary of the Winter Simulation Conference (WSC), the premier international forum for disseminating recent advances in the field of system simulation, the book showcases the historical importance of this influential conference while also looking forward to a bright future for the simulation community. Topics and features: examines the challenge of constructing valid and efficient models, emphasizing the benefits of the process of simulation modeling; discusses model calibration, input model risk, and approaches to validating emergent behaviors in large-scale complex systems with non-linear interactions; reviews the evolution of simulation languages, and the history of the Time Warp algorithm; offers a focus on the design and analysis of simulation experiments under various goals, and describes how data can be “farmed” to support decision making; provides a comprehensive overview of Bayesian belief models for simulation-based decision making, and introduces a model for ranking and selection in cloud computing; highlights how input model uncertainty impacts simulation optimization, and proposes an approach to quantify and control the impact of input model risk; surveys the applications of simulation in semiconductor manufacturing, in social and behavioral modeling, and in military planning and training; presents data analysis on the publications from the Winter Simulation Conference, offering a big-data perspective on the significant impact of the conference. This informative and inspiring volume will appeal to all academics and professionals interested in computational and mathematical modeling and simulation, as well as to graduate students on the path to form the next generation of WSC pioneers.

Big Data Analytics and Cloud Computing

Big Data Analytics and Cloud Computing
Author: Marcello Trovati,Richard Hill,Ashiq Anjum,Shao Ying Zhu,Lu Liu
Publsiher: Springer
Total Pages: 169
Release: 2016-01-12
ISBN 10: 3319253131
ISBN 13: 9783319253138
Language: EN, FR, DE, ES & NL

Big Data Analytics and Cloud Computing Book Review:

This book reviews the theoretical concepts, leading-edge techniques and practical tools involved in the latest multi-disciplinary approaches addressing the challenges of big data. Illuminating perspectives from both academia and industry are presented by an international selection of experts in big data science. Topics and features: describes the innovative advances in theoretical aspects of big data, predictive analytics and cloud-based architectures; examines the applications and implementations that utilize big data in cloud architectures; surveys the state of the art in architectural approaches to the provision of cloud-based big data analytics functions; identifies potential research directions and technologies to facilitate the realization of emerging business models through big data approaches; provides relevant theoretical frameworks, empirical research findings, and numerous case studies; discusses real-world applications of algorithms and techniques to address the challenges of big datasets.

Cloud Computing with E Science Applications

Cloud Computing with E Science Applications
Author: Olivier Terzo,Lorenzo Mossucca
Publsiher: CRC Press
Total Pages: 320
Release: 2020-12-18
ISBN 10: 9780367738532
ISBN 13: 0367738538
Language: EN, FR, DE, ES & NL

Cloud Computing with E Science Applications Book Review:

The amount of data in everyday life has been exploding. This data increase has been especially significant in scientific fields, where substantial amounts of data must be captured, communicated, aggregated, stored, and analyzed. Cloud Computing with e-Science Applications explains how cloud computing can improve data management in data-heavy fields such as bioinformatics, earth science, and computer science. The book begins with an overview of cloud models supplied by the National Institute of Standards and Technology (NIST), and then: Discusses the challenges imposed by big data on scientific data infrastructures, including security and trust issues Covers vulnerabilities such as data theft or loss, privacy concerns, infected applications, threats in virtualization, and cross-virtual machine attack Describes the implementation of workflows in clouds, proposing an architecture composed of two layers--platform and application Details infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a-service (SaaS) solutions based on public, private, and hybrid cloud computing models Demonstrates how cloud computing aids in resource control, vertical and horizontal scalability, interoperability, and adaptive scheduling Featuring significant contributions from research centers, universities, and industries worldwide, Cloud Computing with e-Science Applications presents innovative cloud migration methodologies applicable to a variety of fields where large data sets are produced. The book provides the scientific community with an essential reference for moving applications to the cloud.

Machine Tool Technology Mechatronics and Information Engineering

Machine Tool Technology  Mechatronics and Information Engineering
Author: Zhong Min Wang,Dong Fang Yang,Kun Yang,Liang Yu Guo,Jian Ming Tan
Publsiher: Trans Tech Publications Ltd
Total Pages: 6532
Release: 2014-09-22
ISBN 10: 3038266302
ISBN 13: 9783038266303
Language: EN, FR, DE, ES & NL

Machine Tool Technology Mechatronics and Information Engineering Book Review:

Collection of selected, peer reviewed papers from the 2014 International Conference on Machine Tool Technology and Mechatronics Engineering (ICMTTME 2014), June 22-23, 2014, Guilin, Guangxi, China. The 1440 papers are grouped as follows: Chapter 1: Applied Mechanics, Chapter 2: Measurement and Instrumentation, Monitoring, Testing and Detection Technologies, Chapter 3: Numerical Methods, Computation Methods and Algorithms for Modeling, Simulation and Optimization, Data Mining and Data Processing, Chapter 4: Information Technologies, WEB and Networks Engineering, Information Security, Software Application and Development, Chapter 5: Electronics and Microelectronics, Embedded and Integrated Systems, Power and Energy, Electric and Magnetic Systems, Chapter 6: Communication, Signal and Image Processing, Data Acquisition, Identification and Recognation Technologies, Chapter 7: Materials Processing and Manufacturing Technology, Industry Applications, Chapter 8: Civil and Structure Engineering, Architecture Science, Chapter 9: Bio- and Medical Applications, Chemistry Engineering, Resources and Environmental Engineering, Chapter 10: Advanced Information and Innovative Technologies for Management, Logistics, Economics, Marketing, Education, Assessment

High Performance Computing

High Performance Computing
Author: Michèle Weiland,Guido Juckeland,Carsten Trinitis,Ponnuswamy Sadayappan
Publsiher: Springer
Total Pages: 352
Release: 2019-07-15
ISBN 10: 3030206564
ISBN 13: 9783030206567
Language: EN, FR, DE, ES & NL

High Performance Computing Book Review:

This book constitutes the refereed proceedings of the 34th International Conference on High Performance Computing, ISC High Performance 2019, held in Frankfurt/Main, Germany, in June 2019. The 17 revised full papers presented were carefully reviewed and selected from 70 submissions. The papers cover a broad range of topics such as next-generation high performance components; exascale systems; extreme-scale applications; HPC and advanced environmental engineering projects; parallel ray tracing - visualization at its best; blockchain technology and cryptocurrency; parallel processing in life science; quantum computers/computing; what's new with cloud computing for HPC; parallel programming models for extreme-scale computing; workflow management; machine learning and big data analytics; and deep learning and HPC.

Application of Intelligent Systems in Multi modal Information Analytics

Application of Intelligent Systems in Multi modal Information Analytics
Author: Vijayan Sugumaran
Publsiher: Springer Nature
Total Pages: 329
Release: 2021
ISBN 10: 3030748146
ISBN 13: 9783030748142
Language: EN, FR, DE, ES & NL

Application of Intelligent Systems in Multi modal Information Analytics Book Review:

Data Science and Big Data Analytics

Data Science and Big Data Analytics
Author: Durgesh Kumar Mishra,Xin-She Yang,Aynur Unal
Publsiher: Springer
Total Pages: 406
Release: 2018-08-01
ISBN 10: 9811076413
ISBN 13: 9789811076411
Language: EN, FR, DE, ES & NL

Data Science and Big Data Analytics Book Review:

This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence.