

Modeling and Simulation in HPC and Cloud Systems by Florin Pop
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.
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Foundations of Machine Learning and AI
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Advances in Next-Generation Networking for Cyber-Physical System: TCP, SDN, and Emerging Technologies
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Digitalization
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Innovations in Data Science and Analytics
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Blockchain Innovations for a Sustainable Circular Economy
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AI Intervention in Digital and Social Marketing
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Intelligent Governance in the Big Data Era
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Computational and Data-Driven Approaches in Pharmaceutical Sciences: From Molecular Modelling to Evidence-Based Therapeutics
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Data Science in Finance and Accounting
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Cyber Security
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Internet of Things for Healthcare Technologies
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New Paradigm of Industry 4.0
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Blockchain and Deep Learning
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Cyber and Digital Forensic Investigations
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Handbook of Machine Learning Applications for Genomics
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Fog Data Analytics for IoT Applications
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The Future of Metaverse in the Virtual Era and Physical World
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Machine Learning for Adaptive Many-Core Machines - A Practical Approach
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Big Data and Blockchain for Service Operations Management
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The Geometry of Intelligence: Foundations of Transformer Networks in Deep Learning
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Concepts and Methods for a Librarian of the Web
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Blockchain and its Applications in Industry 4.0
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Deep Learning Through the Prism of Tensors
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Internet of Things and Analytics for Agriculture, Volume 3
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Environmental Modeling Using Satellite Imaging and Dataset Re-processing
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The Power of Data: Driving Climate Change with Data Science and Artificial Intelligence Innovations
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Recommender System for Improving Customer Loyalty
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Evolutionary Decision Trees in Large-Scale Data Mining
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Supply Chain Performance Evaluation
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The Autonomous Web
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Total Journalism
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Big Data in Information Society and Digital Economy
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Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach
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Text Mining
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Information Retrieval and Natural Language Processing
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| ISBN 13 | |
| ISBN 10 | |
| Title | Modeling and Simulation in HPC and Cloud Systems |
| Author | Florin Pop |
| Series | |
| Condition | Unavailable |
| Binding Type | |
| Publisher | |
| Year published | |
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| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
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