This book presents the proceedings of the 12th International Parallel Tools Workshop, held in Stuttgart, Germany, during September 17-18, 2018, and of the 13th International Parallel Tools Workshop, held in Dresden, Germany, during September 2-3, 2019. The workshops are a forum to discuss the latest advances in parallel tools for high-performance computing. High-performance computing plays an increasingly important role for numerical simulation and modeling in academic and industrial research. At the same time, using large-scale parallel systems efficiently is becoming more difficult. A number of tools addressing parallel program development and analysis has emerged from the high-performance computing community over the last decade, and what may have started as a collection of a small helper scripts has now matured into production-grade frameworks. Powerful user interfaces and an extensive body of documentation together create a user-friendly environment for parallel tools.

A comprehensive guide to understanding the standard and most recent advances in the design of reliable computer systems. It is organized into three sections, beginning with an in-depth review of existing reliability techniques and evaluation criteria for both hardware and software. also examined are the models for detecting faults and predicting failures, and the financial considerations which are inherent in the design, purchase, operation, and maintenance of a reliable system.

This book presents the latest research in the fields of reliability theory and its applications, providing a comprehensive overview of reliability engineering and discussing various tools, techniques, strategies and methods within these areas. Reliability analysis is one of the most multidimensional topics in the field of systems reliability engineering, and while its rapid development creates opportunities for industrialists and academics, it is also means that it is hard to keep up to date with the research taking place. By gathering findings from institutions around the globe, the book offers insights into the international developments in the field. As well as discussing the current areas of research, it also identifies knowledge gaps in reliability theory and its applications and highlights fruitful avenues for future research. Covering topics from life cycle sustainability to performance analysis of cloud computing, this book is ideal for upper undergraduate and postgraduate researchers studying reliability engineering.

This book systematically examines and quantifies industrial problems by assessing the complexity and safety of large systems. It includes chapters on system performance management, software reliability assessment, testing, quality management, analysis using soft computing techniques, management analytics, and business analytics, with a clear focus on exploring real-world business issues. Through contributions from researchers working in the area of performance, management, and business analytics, it explores the development of new methods and approaches to improve business by gaining knowledge from bulk data. With system performance analytics, companies are now able to drive performance and provide actionable insights for each level and for every role using key indicators, generate mobile-enabled scorecards, time series-based analysis using charts, and dashboards. In the current dynamic environment, a viable tool known as multi-criteria decision analysis (MCDA) is increasingly being adopted to deal with complex business decisions. MCDA is an important decision support tool for analyzing goals and providing optimal solutions and alternatives. It comprises several distinct techniques, which are implemented by specialized decision-making packages. This book addresses a number of important MCDA methods, such as DEMATEL, TOPSIS, AHP, MAUT, and Intuitionistic Fuzzy MCDM, which make it possible to derive maximum utility in the area of analytics. As such, it is a valuable resource for researchers and academicians, as well as practitioners and business experts.

Business analysis is about identifying business needs and formulating workable solutions to business problems. It requires the widest possible array of tools and the professional ability to use each one when and where it is needed. This new edition provides a comprehensive single source of 123 business analysis techniques, offering practical guidance on how and when to apply them within a clear BA service framework. This book complements Business Analysis, also published by BCS.

Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of blockchain based data analytic environment. Recent research of security based on big data, blockchain and machine learning has been explained through actual work by practitioners and researchers, including their technical evaluation and comparison with existing technologies. The theoretical background and experimental case studies related to real-time environment are covered as well. Aimed at Senior undergraduate students, researchers and professionals in computer science and engineering and electrical engineering, this book: Converges Blockchain, Big Data and Machine learning in one volume. Connects Blockchain technologies with the data centric applications such Big data and E-Health. Easy to understand examples on how to create your own blockchain supported by case studies of blockchain in different industries. Covers big data analytics examples using R. Includes lllustrative examples in python for blockchain creation.

This introductory textbook is designed for a one-semester course on the use of the matrix and analytical methods for the performance analysis of telecommunication systems. It provides an introduction to the modelling and analysis of telecommunication systems for a broad interdisciplinary audience of students in mathematics and applied disciplines such as computer science, electronics engineering, and operations research.

This book provides a collection of selected papers presented at the International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2019), which was held in Goa, India, on 16-17 August 2019. It covers the latest research trends and advances in the areas of data science, artificial intelligence, neural networks, cognitive science and machine learning applications, cyber-physical systems, and cybernetics.

"Do you want to learn more about software telemetry? Don't look any further, this book is the one you need." - Sander Zegveld Software telemetry is the discipline of tracing, logging, and monitoring infrastructure by observing and analyzing the events generated by the system. In Software Telemetry, you'll master the best practices for operating and updating telemetry systems. This practical guide is filled with techniques you can apply to any organization upgrading and optimizing their telemetry systems, from lean startups to well-established companies. You'll learn troubleshooting techniques to deal with every eventuality, such as building easily-auditable systems, preventing and handling accidental data leaks, and ensuring compliance with standards like GDPR. about the technology Complex systems can become black boxes. Telemetry provides feedback on what's happening inside. Telemetry systems are built for gathering, transforming, and communicating data on the performance, functionality, processing speeds, errors, and security events of production systems. There are many forms of telemetry systems, from classic centralized logging to cutting-edge distributed tracing that follows data across microservices. But despite their difference in functionality, all telemetry systems share core operational similarities-and best practices for optimizing them to support your business needs. about the book Software Telemetry is a guide to operating the telemetry systems that monitor and report on your applications. It takes a big picture view of telemetry, teaching you to manage your logging, metrics, and events as a complete end-to-end ecosystem. You'll learn the base architecture that underpins any software telemetry system, allowing you to easily integrate new systems into your existing infrastructure, and how these systems work under the hood. Throughout, you'll follow three very different companies to see how telemetry techniques impact a software-producing startup, a large legacy enterprise, and any organization that writes software for internal use. You'll even cover how software telemetry is used by court processes-ensuring that when your first telemetry discovery request arrives, there's no reason to panic! what's inside - Processes for legal compliance - Cleaning up after toxic data spills and leaks - Safely handling toxic telemetry and confidential records - Multi-tenant techniques and transformation processes - Updating metrics aggregation and sampling traces to display accurate data for longer - Revising software telemetry emissions to be easier to parse - Justifying increased spend on telemetry software about the reader For software developers and infrastructure engineers supporting and building telemetry systems. about the author Jamie Riedesel is a staff engineer at Dropbox. She has over twenty years of experience in IT, working in government, education, legacy companies, and startups. She has specialized in DevOps for the past decade, running distributed systems in public clouds, getting over workplace trauma, and designing software telemetry architectures.

Praise for the First Edition ...a well-written book on data analysis and data mining that provides an excellent foundation...CHOICE This is a must-read book for learning practical statistics and data analysis...Computing Reviews.com A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide readers from almost every field of study. In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. The tools to summarize and interpret data in order to master data analysis are integrated throughout, and the Second Edition also features: * Updated exercises for both manual and computer-aided implementation with accompanying worked examples * New appendices with coverage on the freely available Traceis software, including tutorials using data from a variety of disciplines such as the social sciences, engineering, and finance * New topical coverage on multiple linear regression and logistic regression to provide a range of widely used and transparent approaches * Additional real-world examples of data preparation to establish a practical background for making decisions from data Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition is an excellent reference for researchers and professionals who need to achieve effective decision making from data. The Second Edition is also an ideal textbook for undergraduate and graduate-level courses in data analysis and data mining and is appropriate for cross-disciplinary courses found within computer science and engineering departments.

This book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems. Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.

Codesign for Real-Time Video Applications describes a modern design approach for embedded systems. It combines the design of hardware, software, and algorithms. Traditionally, these design domains are treated separately to reduce the design complexity. Advanced design tools support a codesign of the different domains which opens an opportunity for exploiting synergetic effects. The design approach is illustrated by the design of a video compression system. It is integrated into the video card of a PC. A VLIW processor architecture is used as the basis of the compression system and popular video compression algorithms (MPEG, JPEG, H.261) are analyzed. A complete top-down design flow is presented and the design tools for each of the design steps are explained. The tools are integrated into an HTML-based design framework. The resulting design data can be directly integrated into the WWW. This is a crucial aspect for supporting distributed design groups. The design data can be directly documented an cross referencing in an almost arbitrary way is supported. This provides a platform for information sharing among the different design domains. Codesign for Real-Time Video Applications focuses on the multi-disciplinary aspects of embedded system design. It combines design automation and advanced processor design with an important application domain. A quantitative design approach is emphasized which focuses the design time on the most crucial components. Thus enabling a fast and cost efficient design methodology. This book will be of interest to researchers, designers and managers working in embedded system design.

In Software Mistakes and Tradeoffs you'll learn from costly mistakes that Tomasz Lelek and Jon Skeet have encountered over their impressive careers. You'll explore real-world scenarios where poor understanding of tradeoffs lead to major problems down the road, to help you make better design decisions. Plus, with a little practice, you'll be able to avoid the pitfalls that trip up even the most experienced developers. Software Mistakes and Tradeoffs teaches you how to make better decisions about designing, planning, and implementing applications. You'll analyse real-world scenarios where the wrong tradeoff decisions were made, and discover what could have been done differently. The book lays out the pros and cons of different approaches and explores evergreen patterns that will always be relevant to software design. Code performance versus simplicity. Delivery speed versus duplication. Flexibility versus maintain ability-everydecision you make in software engineering involves balancing tradeoffs. Often, decisions that look good at the design stage can prove problematic in practice.This book reveals the questions you need to be asking to make the right decisions for your own software tradeoffs.

This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and the Computing Sciences. The prerequisite is one year of calculus. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with only a calculus background. They explore the practical implications of the formal results to problem-solving so students gain an understanding of the logic behind the techniques as well as practice in using them. The examples, exercises, and applications were chosen specifically for students in engineering and computer science and include opportunities for real data analysis.

This two-wolume set (CCIS 1395-1396) constitutes the refereed proceedings of the Third International Conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2020, held in Taganrog, Russia, in October 2020.The 80 revised full papers presented were carefully reviewed and selected from 291 submissions. The prime aim of the conference is to invite researchers from different domains of network and communication technologies to a single platform to showcase their research ideas. The selected papers are organized in topical sections on communication technologies; security and privacy; futuristic computing technologies; network and computing technologies; wireless networks and Internet of Things (IoT).

This book constitutes the refereed proceedings of the 13th IFIP WG 5.11 International Symposium on Environmental Software Systems, ISESS 2020, held in Wageningen, The Netherlands, in February 2020. The 22 full papers and 3 short papers were carefully reviewed and selected from 29 submissions. The papers cover a wide range of topics on environmental informatics, including data mining, artificial intelligence, high performance and cloud computing, visualization and smart sensing for environmental, earth, agricultural and food applications.

Research into grid computing has been driven by the need to solve large-scale, increasingly complex problems for scientific applications. Yet the applications of grid computing for business and casual users did not begin to emerge until the development of the concept of cloud computing, fueled by advances in virtualization techniques, coupled with the increased availability of ever-greater Internet bandwidth. The appeal of this new paradigm is mainly based on its simplicity, and the affordable price for seamless access to both computational and storage resources.

This timely text/reference introduces the fundamental principles and techniques underlying grids, clouds and virtualization technologies, as well as reviewing the latest research and expected future developments in the field. Readers are guided through the key topics by internationally recognized experts, enabling them to develop their understanding of an area likely to play an ever more significant role in coming years.

Topics and features: presents contributions from an international selection of experts in the field; provides a thorough introduction and overview of existing technologies in grids, clouds and virtualization, including a brief history of the field; examines the basic requirements for performance isolation of virtual machines on multi-core servers, analyzing a selection of system virtualization technologies; examines both business and scientific applications of grids and clouds, including their use in the life sciences and for high-performance computing; explores cloud building technologies, architectures for enhancing grid infrastructures with cloud computing, and cloud performance; discusses energy aware grids and clouds, workflows on grids and clouds, and cloud and grid programming models.

This useful text will enable interested readers to familiarize themselves with the key topics of grids, clouds and virtualization, and to contribute to new advances in the field. Researchers, undergraduate and graduate students, system designers and programmers, and IT policy makers will all benefit from the material covered.

This book constitutes the refereed post-conference proceedings of the Third International Symposium on Benchmarking, Measuring, and Optimization, Bench 2020, held virtually in November 2020.The 12 revised full papers and 1 revised short paper presented were carefully reviewed and selected from 28 submissions. The papers are organized in topical sections named: best paper session; data management and storage; supercomputing; benchmarking on GPU; and application and dataset.

"This book is a comprehensive text for the design of safety critical, hard real-time embedded systems. It offers a splendid example for the balanced, integrated treatment of systems and software engineering, helping readers tackle the hardest problems of advanced real-time system design, such as determinism, compositionality, timing and fault management. This book is an essential reading for advanced undergraduates and graduate students in a wide range of disciplines impacted by embedded computing and software. Its conceptual clarity, the style of explanations and the examples make the abstract concepts accessible for a wide audience." Janos Sztipanovits, Director E. Bronson Ingram Distinguished Professor of Engineering Institute for Software Integrated Systems Vanderbilt University Real-Time Systems focuses on hard real-time systems, which are computing systems that must meet their temporal specification in all anticipated load and fault scenarios. The book stresses the system aspects of distributed real-time applications, treating the issues of real-time, distribution and fault-tolerance from an integral point of view. A unique cross-fertilization of ideas and concepts between the academic and industrial worlds has led to the inclusion of many insightful examples from industry to explain the fundamental scientific concepts in a real-world setting. Compared to the Second Edition, new developments in communication standards for time-sensitive networks, such as TSN and Time-Triggered Ethernet are addressed. Furthermore, this edition includes a new chapter on real-time aspects in cloud and fog computing. The book is written as a standard textbook for a high-level undergraduate or graduate course on real-time embedded systems or cyber-physical systems. Its practical approach to solving real-time problems, along with numerous summary exercises, makes it an excellent choice for researchers and practitioners alike.

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 23rd International Conference on Distributed and Computer and Communication Networks, DCCN 2020, held in Moscow, Russia, in September 2020. Due to the COVID-19 pandemic the conference was held online. The 43 papers were carefully reviewed and selected from 167 submissions.The papers are organized in the following topical sections: computer and communication networks and technologies; analytical modeling of distributed systems, and distributed systems applications.

This book constitutes the refereed proceedings of the 16th International Conference on Integrated Formal Methods, IFM 2019, held in Lugano, Switzerland, in November 2020. The 24 full papers and 2 short papers were carefully reviewed and selected from 63 submissions. The papers cover a broad spectrum of topics: Integrating Machine Learning and Formal Modelling; Modelling and Verification in B and Event-B; Program Analysis and Testing; Verification of Interactive Behaviour; Formal Verification; Static Analysis; Domain-Specific Approaches; and Algebraic Techniques.

This book describes how we can design and make efficient processors for high-performance computing, AI, and data science. Although there are many textbooks on the design of processors we do not have a widely accepted definition of the efficiency of a general-purpose computer architecture. Without a definition of the efficiency, it is difficult to make scientific approach to the processor design. In this book, a clear definition of efficiency is given and thus a scientific approach for processor design is made possible. In chapter 2, the history of the development of high-performance processor is overviewed, to discuss what quantity we can use to measure the efficiency of these processors. The proposed quantity is the ratio between the minimum possible energy consumption and the actual energy consumption for a given application using a given semiconductor technology. In chapter 3, whether or not this quantity can be used in practice is discussed, for many real-world applications. In chapter 4, general-purpose processors in the past and present are discussed from this viewpoint. In chapter 5, how we can actually design processors with near-optimal efficiencies is described, and in chapter 6 how we can program such processors. This book gives a new way to look at the field of the design of high-performance processors.

This book constitutes the refereed post-conference proceedings of the 6th Russian Supercomputing Days, RuSCDays 2020, held in Moscow, Russia, in September 2020.* The 51 revised full and 4 revised short papers presented were carefully reviewed and selected from 106 submissions. The papers are organized in the following topical sections: parallel algorithms; supercomputer simulation; HPC, BigData, AI: architectures, technologies, tools; and distributed and cloud computing. * The conference was held virtually due to the COVID-19 pandemic.

This book constitutes refereed proceedings of the 8th Conference on Information and Communication Technologies of Ecuador, TICEC 2020, held in November 2020. Due to the COVID-19 pandemic the conference was held online. The 36 full and 7 short papers were carefully reviewed and selected from 117 qualified submissions. The papers are organized according to the following topical sections: biomedical sensors and wearables systems; data science; ICTs applications; industry 4.0; smart cities; software development; technology and environment.