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R 763.00
Architectures for the Intelligent AI-Ready Enterprise
Create AI-ready enterprise solutions with MongoDB and discover how to design intelligent architectures that transform data into innovation, efficiency, and real business valueKey FeaturesComplete guide covering GenAI to agentic AI, semantic protection to multi-agent systems25+ proven AI use cases delivering measurable impact across 6+ industries15+ real enterprise case studies from Novo Nordisk, Base 39, and morePurchase of the print or Kindle book includes a free PDF eBookBook DescriptionAI is reshaping industries, yet most organizations struggle to scale beyond pilots. Architectures for the Intelligent AI-Ready Enterprise bridges this gap with practical frameworks for building AI-ready architectures that deliver lasting business value.The book helps you explore System of Action databases and see why they're revolutionizing real-time decision-making. Through real-world applications across industries, from manufacturing and healthcare to financial services and retail, you'll discover how leading organizations transform their operations. You'll learn semantic data protection techniques that enable AI in regulated industries, as well as master advanced patterns including agentic AI and multi-agent orchestration.Written by MongoDB and industry practitioners, this book combines strategy with technical depth and proven business value. You’ll modernize by enabling AI innovation while preserving existing investments, implement trustworthy AI with governance frameworks, and build scalable solutions using a unified data platform like MongoDB that delivers measurable ROI and transformation.Whether you're architecting next-generation systems or modernizing legacy infrastructure, this book provides the patterns, case studies, and expert guidance to build enterprises that’ll thrive in an intelligent future.What you will learnDesign AI-ready data architectures that scale in productionDefine systems of action and explain why they matter for enterprisesModernize legacy systems for AI-ready, unified architecturesImplement governance, privacy, and compliance frameworks for AIExplore real-world AI implementations for over six industriesDeploy production RAG and agentic systems with MongoDBApply semantic data protection in regulated industriesBuild domain-specific AI agents and intelligent copilotsApply MCP, causal AI, and multi-agent systems for future-ready architecturesWho this book is forThis book is for IT leaders, enterprise architects, solution designers, and innovators ready to transform AI potential into production reality. Whether you're modernizing legacy systems, implementing scalable AI solutions, or translating AI concepts into measurable business outcomes, this book provides practical frameworks and industry-proven patterns. Basic familiarity with enterprise systems and data architecture is helpful, but deep AI expertise isn't required.
R 2,442.00
Contemporary Architecture and the Digital Design Process
Contemporary Architecture and the Digital Design Process introduces the reader to new developments in the computer modelling of design form in contemporary architectural practice through a series of detailed case studies. The book illustrates how evolving design practices use and exploit the potential of new computing technologies in a wide range of areas and application.A central thesis of this book is that technology follows design demand, rather than design adjusting to available new technology. Designers are not merely passive recipients of prescribed computing tools and techniques. Instead, they are increasingly able to express their intuitive design ideas through the rational medium of computing.The book features several contemporary building projects, each of which introduces a range of CAD and computing issues based upon the work of creative architectural and engineering design practices. These include the offices of Frank O. Gehry, Peter Cook and Colin Fournier, Anthony Hunt Associates, Peter Hubner, Szyskowitz-Kowalski, and Faulkner Brown. All these examples show what architects need to know and the skills they need to acquire to use advanced CAD technology.
R 2,711.00
R 763.00
Advanced Computer Architecture
This book constitutes the refereed proceedings of the 12th Annual Conference on Advanced Computer Architecture, ACA 2018, held in Yingkou, China, in August 2018. The 17 revised full papers presented were carefully reviewed and selected from 80 submissions. The papers of this volume are organized in topical sections on: accelerators; new design explorations; towards efficient ML/AI; parallel computing system.
R 1,547.26
Raspberry Pi OS System Administration with systemd and Python
The second in a new series exploring the basics of Raspberry Pi Operating System administration, this installment builds on the insights provided in Volume 1 to provide a compendium of easy- to- use and essential Raspberry Pi OS system administration for the novice user, with specific focus on Python and Python3.The overriding idea behind system administration of a modern, 21st-century Linux system such as the Raspberry Pi OS is the use of systemd to ensure that the Linux kernel works efficiently and effectively to provide these three foundation stones of computer operation and management: computer system concurrency, virtualization, and secure persistence. Exercises are included throughout to reinforce the readers’ learning goals with solutions and example code provided on the accompanying GitHub site.This book is aimed at students and practitioners looking to maximize their use of the Raspberry Pi OS. With plenty of practical examples, projects, and exercises, this volume can also be adopted in a more formal learning environment to supplement and extend the basic knowledge of a Linux operating system.
R 7,586.44
Architecture for Fast and General Data Processing on Large Clusters
The past few years have seen a major change in computing systems, as growing data volumes and stalling processor speeds require more and more applications to scale out to clusters. Today, a myriad data sources, from the Internet to business operations to scientific instruments, produce large and valuable data streams. However, the processing capabilities of single machines have not kept up with the size of data. As a result, organizations increasingly need to scale out their computations over clusters. At the same time, the speed and sophistication required of data processing have grown. In addition to simple queries, complex algorithms like machine learning and graph analysis are becoming common. And in addition to batch processing, streaming analysis of real-time data is required to let organizations take timely action. Future computing platforms will need to not only scale out traditional workloads, but support these new applications too.This book, a revised version of the 2014 ACM Dissertation Award winning dissertation, proposes an architecture for cluster computing systems that can tackle emerging data processing workloads at scale. Whereas early cluster computing systems, like MapReduce, handled batch processing, our architecture also enables streaming and interactive queries, while keeping MapReduce's scalability and fault tolerance. And whereas most deployed systems only support simple one-pass computations (e.g., SQL queries), ours also extends to the multi-pass algorithms required for complex analytics like machine learning. Finally, unlike the specialized systems proposed for some of these workloads, our architecture allows these computations to be combined, enabling rich new applications that intermix, for example, streaming and batch processing.We achieve these results through a simple extension to MapReduce that adds primitives for data sharing, called Resilient Distributed Datasets (RDDs). We show that this is enough to capture a wide range of workloads. We implement RDDs in the open source Spark system, which we evaluate using synthetic and real workloads. Spark matches or exceeds the performance of specialized systems in many domains, while offering stronger fault tolerance properties and allowing these workloads to be combined. Finally, we examine the generality of RDDs from both a theoretical modeling perspective and a systems perspective.This version of the dissertation makes corrections throughout the text and adds a new section on the evolution of Apache Spark in industry since 2014. In addition, editing, formatting, and links for the references have been added.
R 3,210.61
Computer Systems: Architectures, Modeling, and Simulation
The SAMOS workshop is an international gathering of highly quali?ed rese- chers from academia and industry, sharing in a 3-day lively discussion on the quietandinspiringnorthernmountainsideofthe MediterraneanislandofSamos. As a tradition, the workshop features plenary presentations in the morning, while after lunch all kinds of informal discussions and nut cracking gatherings take place. The workshop is unique in the sense that not only solved research problems are presented and discussed, but also (partly) unsolved problems and in-depth topical reviews can be unleashed in the scienti?c arena. Consequently, the workshopprovidesthe participantswithanenvironmentwherecollaboration rather than competition is fostered. This fourth edition of the SAMOS workshop developed into a highly int- esting event with a program that consisted of 36 paper presentations as well as a keynote speech by Kees Vissers from Xilinx Research. The paper authors r- resented 12 di?erent countries, the USA, UK, Canada, Brazil, Germany, France, Spain, Finland, Belgium, Portugal, Greece and The Netherlands. The presen- tions were divided into three tracks: recon?gurable computing, architecture and implementation, and system modeling and simulation.We believe that all three tracks showed high-quality, state-of-the-art research in their respective ?elds. Besides the papers from SAMOS IV, this proceedings also features num- ous papers from the SAMOS III workshop. As the SAMOS III edition did not have a well-established proceedings mechanism, we decided to give the authors from last year's edition the opportunity to formally publish their papers in this proceedings.
R 2,015.00
Supercomputer Architecture
Supercomputers are the largest and fastest computers available at any point in time. The term was used for the first time in the New York World, March 1920, to describe "new statistical machines with the mental power of 100 skilled mathematicians in solving even highly complex algebraic problems. " Invented by Mendenhall and Warren, these machines were used at Columbia University'S Statistical Bureau. Recently, supercomputers have been used primarily to solve large-scale prob lems in science and engineering. Solutions of systems of partial differential equa tions, such as those found in nuclear physics, meteorology, and computational fluid dynamics, account for the majority of supercomputer use today. The early computers, such as EDVAC, SSEC, 701, and UNIVAC, demonstrated the feasibility of building fast electronic computing machines which could become commercial products. The next generation of computers focused on attaining the highest possible computational speeds. This book discusses the architectural approaches used to yield significantly higher computing speeds while preserving the conventional, von Neumann, machine organization (Chapters 2-4). Subsequent improvements depended on developing a new generation of computers employing a new model of computation: single-instruction multiple data (SIMD) processors (Chapters 5-7). Later machines refmed SIMD architec ture and technology (Chapters 8-9). SUPERCOMPUTER ARCHITECI'URE CHAPTER! INTRODUCTION THREE ERAS OF SUPERCOMPUTERS Supercomputers -- the largest and fastest computers available at any point in time -- have been the products of complex interplay among technological, architectural, and algorithmic developments.
R 1,541.67
Computational Frameworks for Political and Social Research with Python
This book is intended to serve as the basis for a first course in Python programming for graduate students in political science and related fields. The book introduces core concepts of software development and computer science such as basic data structures (e.g. arrays, lists, dictionaries, trees, graphs), algorithms (e.g. sorting), and analysis of computational efficiency. It then demonstrates how to apply these concepts to the field of political science by working with structured and unstructured data, querying databases, and interacting with application programming interfaces (APIs). Students will learn how to collect, manipulate, and exploit large volumes of available data and apply them to political and social research questions. They will also learn best practices from the field of software development such as version control and object-oriented programming. Instructors will be supplied with in-class example code, suggested homework assignments (with solutions), and material for practical lab sessions.
R 4,260.30
R 1,541.80
Computing with Parallel Architecture: T.Node
Based on the Lectures given during the Eurocourse on `Computing with Parallel Architectures' held at the Joint Research Centre Ispra, Italy, September 10-14, 1990
R 4,645.48
R 763.00
Computational Frameworks for Political and Social Research with Python
This book is intended to serve as the basis for a first course in Python programming for graduate students in political science and related fields. The book introduces core concepts of software development and computer science such as basic data structures (e.g. arrays, lists, dictionaries, trees, graphs), algorithms (e.g. sorting), and analysis of computational efficiency. It then demonstrates how to apply these concepts to the field of political science by working with structured and unstructured data, querying databases, and interacting with application programming interfaces (APIs). Students will learn how to collect, manipulate, and exploit large volumes of available data and apply them to political and social research questions. They will also learn best practices from the field of software development such as version control and object-oriented programming. Instructors will be supplied with in-class example code, suggested homework assignments (with solutions), and material for practical lab sessions.
R 2,734.60
Designing Embedded Systems and the Internet of Things (IoT) with the ARM mbed
A comprehensive and accessible introduction to the development of embedded systems and Internet of Things devices using ARM mbed Designing Embedded Systems and the Internet of Things (IoT) with the ARM mbed offers an accessible guide to the development of ARM mbed and includes a range of topics on the subject from the basic to the advanced. ARM mbed is a platform and operating system based on 32-bit ARM Cortex-M microcontrollers. This important resource puts the focus on ARM mbed NXP LPC1768 and FRDM-K64F evaluation boards. NXP LPC1768 has powerful features such as a fast microcontroller, various digital and analog I/Os, various serial communication interfaces and a very easy to use Web based compiler. It is one of the most popular kits that are used to study and create projects. FRDM-K64F is relatively new and largely compatible with NXP LPC1768 but with even more powerful features. This approachable text is an ideal guide that is divided into four sections; Getting Started with the ARM mbed, Covering the Basics, Advanced Topics and Case Studies. This getting started guide: Offers a clear introduction to the topicContains a wealth of original and illustrative case studiesIncludes a practical guide to the development of projects with the ARM mbed platformPresents timely coverage of how to develop IoT applications Designing Embedded Systems and the Internet of Things (IoT) with the ARM mbed offers students and R&D engineers a resource for understanding the ARM mbed NXP LPC1768 evaluation board.
R 3,971.00
Embedded Computer Systems: Architectures, Modeling, and Simulation
This book constitutes the refereed proceedings of the 8th International Workshop on Systems, Architectures, Modeling, and Simulation, SAMOS 2008, held in Samos, Greece, in July 2008. The 24 revised full papers presented together with a contamplative keynote and additional papers of two special workshop sessions were carefully reviewed and selected from 62 submissions. The papers are organized in topical sections on architecture, new frontiers, SoC, application specific contributions, system level design for heterogeneous systems, programming multicores, sensors and sensor networks; and systems modeling and design.
R 2,015.00
Architecture Exploration for Embedded Processors with LISA
Today more than 90% of all programmable processors are employed in embedded systems. The LISA processor design platform presented in this book addresses recent design challenges and results in highly satisfactory solutions, covering all major high-level phases of embedded processor design.
R 4,644.44
Network Analysis and Architecture
This book covers network analysis and architecture for large-scale computer network planning. Networks and the Internet are essential for modern industries and societies. Building a new network, upgrading an existing network, or planning to use a public network requires integrating various network mechanisms and technologies in a cohesive fashion. This demands a deep understanding of the concepts, principles, processes, approaches, and good practices of advanced network planning. More specifically, emphasizing service-based networking, the book introduces structured processes for network planning, provides systematic approaches for network analysis and architecture, develops network planning specifications, and discusses high-level network architectural models from various perspectives. It also offers detailed discussions on component-based architecture about addressing, routing, performance, management, and security and privacy. Recent developments in data centers, virtualization, and cloud are also embedded into the network architecture. Moreover, the book includes a comprehensive introduction to building practical TCP/IP network communications via sockets with practical examples. The book is suitable for use as a textbook for senior undergraduate and postgraduate students or as a reference book for network practitioners looking to develop or enhance their skills in network planning.
R 6,594.00
Microprocessor Architecture
This book gives a comprehensive description of the architecture of microprocessors from simple in-order short pipeline designs to out-of-order superscalars. It discusses topics such as: • The policies and mechanisms needed for out-of-order processing such as register renaming, reservation stations, and reorder buffers • Optimizations for high performance such as branch predictors, instruction scheduling, and load-store speculations • Design choices and enhancements to tolerate latency in the cache hierarchy of single and multiple processors • State-of-the-art multithreading and multiprocessing emphasizing single chip implementations Topics are presented as conceptual ideas, with metrics to assess the performance impact, if appropriate, and examples of realization. The emphasis is on how things work at a black box and algorithmic level. The author also provides sufficient detail at the register transfer level so that readers can appreciate how design features enhance performance as well as complexity.
R 4,297.50
Architecture of Computing Systems - ARCS 2009
This book constitutes the refereed proceedings of the 22nd International Conference on Architecture of Computing Systems, ARCS 2009, held in Delft, The Netherlands, in March 2009. The 21 revised full papers presented together with 3 keynote papers were carefully reviewed and selected from 57 submissions. This year's special focus is set on energy awareness. The papers are organized in topical sections on compilation technologies, reconfigurable hardware and applications, massive parallel architectures, organic computing, memory architectures, enery awareness, Java processing, and chip-level multiprocessing.
R 1,552.25
Software Architecture in Practice
The Definitive, Practical, Proven Guide to Architecting Modern Software--Fully Updated with New Content on Mobility, the Cloud, Energy Management, DevOps, Quantum Computing, and More Updated with eleven new chapters, Software Architecture in Practice, Fourth Edition, thoroughly explains what software architecture is, why it's important, and how to design, instantiate, analyze, evolve, and manage it in disciplined and effective ways. Three renowned software architects cover the entire lifecycle, presenting practical guidance, expert methods, and tested models for use in any project, no matter how complex. You'll learn how to use architecture to address accelerating growth in requirements, system size, and abstraction, and to manage emergent quality attributes as systems are dynamically combined in new ways. With insights for utilizing architecture to optimize key quality attributes--including performance, modifiability, security, availability, interoperability, testability, usability, deployability, and more--this guide explains how to manage and refine existing architectures, transform them to solve new problems, and build reusable architectures that become strategic business assets. Discover how architecture influences (and is influenced by) technical environments, project lifecycles, business profiles, and your own practicesLeverage proven patterns, interfaces, and practices for optimizing quality through architectureArchitect for mobility, the cloud, machine learning, and quantum computingDesign for increasingly crucial attributes such as energy efficiency and safetyScale systems by discovering architecturally significant influences, using DevOps and deployment pipelines, and managing architecture debtUnderstand architecture's role in the organization, so you can deliver more value Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
R 1,532.00
Functional Programming Languages and Computer Architecture
This book offers a comprehensive view of the best and thelatest work in functional programming. It is the proceedingsof a major international conference and contains 30 papersselected from 126 submitted. A number of themes emerge. Oneis a growing interest in types: powerful type systems ortype checkers supporting overloading, coercion, dynamictypes, and incremental inference; linear types to optimizestorage, and polymorphic types to optimize semanticanalysis. The hot topic of partial evaluation is wellrepresented: techniques for higher-order binding-timeanalysis, assuring termination of partial evaluation, andimproving the residual programs a partial evaluatorgenerates. The thorny problem of manipulating state infunctional languages is addressed: one paper even arguesthat parallel programs with side-effects can be "moredeclarative" than purely functional ones. Theoretical workcovers a new model of types based on projections,parametricity, a connection between strictness analysis andlogic, and a discussion of efficient implementations of thelambda-calculus. The connection with computer architectureand a variety of other topics are also addressed.
R 3,099.34
Event-Database Architecture for Computer Games
Event-Database Architecture for Computer Games proposes the first explicit software architecture for game development, answering the problem of building modern computer games with little or no game design. In this volume, an example of a practical production process based on the software production process is explained, including examples of the game design, technical design, data design and tools design in that process.This volume includes a brief overview on how to optimise the results. This leads on to an exploration of how staff, especially Software Engineers, typically view optimisation. It also explains how the vision of the Engineers relates to the vision of the leadership of a project or company. It describes how this leadership can also affect the efficacy of a production process, including the Event-Database Production Process.This book will be of great interest to professional game developers involved in management roles such as Technical Directors and Game Producers and technical roles, such as Tools Programmers, UI Programmers, Gameplay Programmers and Engineers, as well as students studying game development and programming.Rodney Quaye is Senior Software Development Engineer in Test at Build A Rocket Boy. He has worked in the Computer Games industry for over 16 years. He has worked at several Games Studios, including Sumo Digital, nDreams, Supermassive Games, Traveller’s Tales, Hotgen, Oysterworld, Second Impact, Flaming Pumpkin, Goldhawk Interactive, Jagex, Gusto Games, Criterion, Asylum Entertainment, Codemasters and Deibus Studios. The famous titles he has worked on include Burnout 2 and 3 for Criterion, LMA Manager for Codemasters, Runescape for Jagex, Lego Worlds for Traveller’s Tales and Everywhere for Build A Rocket Boy.
R 7,589.82
AWS for Solutions Architects
Master AWS architecture and design secure, scalable, production-ready cloud systems. This practical guide features real-world patterns, GenAI strategies, cost optimization techniques, and certification-aligned best practices.Key FeaturesStay current with hands-on coverage of MLOps, AIOps, and the latest AWS service updatesImplement migration strategies with real-world examples and enterprise case studiesAdvance your AWS career with certification-aligned insights and exam-ready strategiesBook DescriptionAWS for Solutions Architects, Third Edition is your essential guide to thriving in the fast-evolving AWS ecosystem. As a solutions architect, staying on top of the latest technologies and managing complex cloud migrations can be challenging, and this book addresses those pain points head-on. Seasoned AWS experts Saurabh Shrivastava, Neelanjali Srivastav, and Dhiraj Thakur bring deep industry insight and hands-on experience to every chapter.This third edition introduces cutting-edge topics, including Generative AI and MLOps, to keep pace with the evolving cloud landscape and guide you in building AI-driven applications. The book also reflects updates from the AWS Well-Architected Framework and aligns with the latest AWS certifications, making it a future-ready guide for cloud professionals. The chapters help you stay ahead of the competition with in-depth coverage of the latest AWS certifications, including AI Practitioner Foundation and Data Engineer Associate, helping you position yourself as a leader in cloud innovation.By the end of this book, you'll transform into a solutions architecture expert, equipped with the strategies, tools, and certifications needed to handle any cloud challenge.What you will learnGain expertise in GenAI, MLOps, AIOps, and mobile edge computingOptimize performance and handle errors in cloud-native applicationsPrepare for new AWS certifications, including those focused on AI and data engineeringApply best practices for security, compliance, and AWS Learning BadgesExplore the updated Well-Architected Framework with six pillarsGet in-depth knowledge of new storage options and security group configurationsWho this book is forThis book is for application and enterprise architects, developers, operations engineers, and certification aspirants looking to master AWS architectural patterns, best practices, and advanced techniques for building scalable, secure, highly available, fault-tolerant, and cost-effective cloud solutions. Prior coding knowledge isn’t required, but experience in software architecture design will be helpful.
R 1,791.00
Azure Cloud Native Architecture Mapbook
Build modern, secure, and scalable cloud-native solutions on Azure with expert-guided architecture patternsKey FeaturesApply proven architectural patterns to real-world Azure cloud solutionsTranslate enterprise requirements into secure and scalable reference architecturesGain practical design insights from a Microsoft cloud solution architectGet With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader FreeBook DescriptionDesigning effective cloud-native architectures on Azure often feels overwhelming—especially when trying to translate complex requirements into reliable solutions. This book solves that problem by giving you a structured, visual guide to building modern systems that are scalable, secure, and production-ready.You’ll discover how to plan, design, and communicate Azure-based architectures using practical reference diagrams mapped to real-world use cases. Organized by domain including infrastructure, applications, data, container orchestrators, AI and security—each chapter walks you through the key services, patterns, and decisions that underpin successful solutions.Throughout the book, you’ll find over 40 detailed architecture maps, created and curated by a seasoned Microsoft cloud solution architect. These maps illustrate how to align Azure services with business goals, manage hybrid and multi-cloud complexity, and incorporate best practices for governance, resilience, and cost optimization.This book gives you more than just diagrams,it offers the confidence to design cloud solutions that scale and perform. Whether you're modernizing a legacy stack or building greenfield applications, the Azure Cloud Native Architecture Mapbook is your trusted design companion from concept to delivery.What you will learnAlign architecture with business and technical requirementsChoose the right compute, storage, and networking servicesVisualize key components using architectural map diagramsApply design principles for identity, governance, and observabilityArchitect hybrid and containerized solutionsTranslate real-world needs into actionable cloud designsApply patterns from Microsoft's Cloud Adoption FrameworkWho this book is forCloud architects, Solution Architects, developers, DevOps engineers, and IT professionals designing, deploying, or modernizing solutions on Microsoft Azure. Readers should understand core Azure services and have experience working in cloud-native or hybrid environments. Additionally, readers should be familiar with some generic architecture concepts.
R 1,726.00
R 1,166.11
Raspberry Pi OS System Administration with systemd and Python
The second in a new series exploring the basics of Raspberry Pi Operating System administration, this installment builds on the insights provided in Volume 1 to provide a compendium of easy- to- use and essential Raspberry Pi OS system administration for the novice user, with specific focus on Python and Python3.The overriding idea behind system administration of a modern, 21st-century Linux system such as the Raspberry Pi OS is the use of systemd to ensure that the Linux kernel works efficiently and effectively to provide these three foundation stones of computer operation and management: computer system concurrency, virtualization, and secure persistence. Exercises are included throughout to reinforce the readers’ learning goals with solutions and example code provided on the accompanying GitHub site.This book is aimed at students and practitioners looking to maximize their use of the Raspberry Pi OS. With plenty of practical examples, projects, and exercises, this volume can also be adopted in a more formal learning environment to supplement and extend the basic knowledge of a Linux operating system.
R 2,885.45
Critical Computational Relations in Design, Architecture and the Built Environment
This book delves into the power relations between computational practices, technology infrastructures, knowledge, and their reproductions of bias in design at multiple scales. It provides critical perspectives and insights on how computation intersects with architecture, design, the built environment, and society.Computational practices, tools and methods in design, architecture, and the built environment, frequently offer technocentric solutions to design problems. Portrayed as mere tools that are "neutral" and "optimized", these technological infrastructures mask social, political, and environmental entanglements involved in their creation and expansion as well as the power of software monopolies and technology providers.The six contributions to this volume provide critical perspectives and insights on how computation intersects with architecture, design, the built environment, and society. The chapters cover diverse topics such as data practices for design simulations, machine learning (ML) and digital humanities methods for digital heritage, a computationally-aided exploration of ideologies of digital architecture, embodied and craft practice for digital fabrication, feminist hacking practices challenging heteronormative values in digital urban design, and post-disciplinary pedagogies for computational design.The book will be of interest to researchers, students and practitioners in the fields of architecture, built environment, computational design, science and technology studies, and sociology. The chapters in this book were originally published in Digital Creativity.
R 2,381.00
Architecture for Fast and General Data Processing on Large Clusters
The past few years have seen a major change in computing systems, as growing data volumes and stalling processor speeds require more and more applications to scale out to clusters. Today, a myriad data sources, from the Internet to business operations to scientific instruments, produce large and valuable data streams. However, the processing capabilities of single machines have not kept up with the size of data. As a result, organizations increasingly need to scale out their computations over clusters. At the same time, the speed and sophistication required of data processing have grown. In addition to simple queries, complex algorithms like machine learning and graph analysis are becoming common. And in addition to batch processing, streaming analysis of real-time data is required to let organizations take timely action. Future computing platforms will need to not only scale out traditional workloads, but support these new applications too.This book, a revised version of the 2014 ACM Dissertation Award winning dissertation, proposes an architecture for cluster computing systems that can tackle emerging data processing workloads at scale. Whereas early cluster computing systems, like MapReduce, handled batch processing, our architecture also enables streaming and interactive queries, while keeping MapReduce's scalability and fault tolerance. And whereas most deployed systems only support simple one-pass computations (e.g., SQL queries), ours also extends to the multi-pass algorithms required for complex analytics like machine learning. Finally, unlike the specialized systems proposed for some of these workloads, our architecture allows these computations to be combined, enabling rich new applications that intermix, for example, streaming and batch processing.We achieve these results through a simple extension to MapReduce that adds primitives for data sharing, called Resilient Distributed Datasets (RDDs). We show that this is enough to capture a wide range of workloads. We implement RDDs in the open source Spark system, which we evaluate using synthetic and real workloads. Spark matches or exceeds the performance of specialized systems in many domains, while offering stronger fault tolerance properties and allowing these workloads to be combined. Finally, we examine the generality of RDDs from both a theoretical modeling perspective and a systems perspective.This version of the dissertation makes corrections throughout the text and adds a new section on the evolution of Apache Spark in industry since 2014. In addition, editing, formatting, and links for the references have been added.
R 2,013.00
Practical Cybersecurity Architecture
Plan and design robust security architectures to secure your organization’s technology landscape and the applications you developKey FeaturesUnderstand the role of the architect in successfully creating complex security structures.Learn methodologies for creating architecture documentation, engaging stakeholders, and implementation of designs.Understand how to refine and improve architecture methodologies to meet business challenges.Book DescriptionCybersecurity architecture is the discipline of systematically ensuring that an organization is resilient against cybersecurity threats. Cybersecurity architects work in tandem with stakeholders to create a “vision” for security in the organization and create designs that are implementable, goal-based, and in keeping with the organization’s governance strategy.Within this book, you'll learn the fundamentals of cybersecurity architecture as a practical discipline. These fundamentals are evergreen approaches that, once mastered, can be applied and adapted to new and emerging technologies like AI and ML. You’ll learn how to address and mitigate risks, how to design secure solutions in a purposeful and repeatable way, how to communicate with others about security designs, and how to bring designs to fruition. This book outlines strategies to help you work with execution teams to make your vision a reality, along with ways to keep designs relevant over time. As you progress, you'll also learn about recognized frameworks for building robust designs and strategies you can adopt to create your own designs.When you complete this book, you will have the foundational skills required to architect infrastructure, cloud, AI, and application solutions for today and well into the future with robust security components for your organization.What you will learnExplore ways to create your own architectures and analyze those from othersUnderstand strategies for creating architectures for environments and applicationsDiscover approaches to documentation using repeatable approaches and toolsDelve into communication techniques for designs, goals, and requirementsFocus on implementation strategies for designs that help reduce riskBecome well-versed with methods to apply architectural discipline to your organization.Who this book is forThe primary audience includes those who are new to cybersecurity architecture, as well as seasoned architects interested in honing their skills. However, anyone involved in the process of implementing, planning, operating, or maintaining cybersecurity in an organization can benefit from this book. This includes security practitioners, systems auditors, and (to a lesser extent) software developers invested in keeping their organizations secure.
R 1,693.00
Architecture and Design of Distributed Embedded Systems
Due to the decreasing production costs of IT systems, applications that had to be realised as expensive PCBs formerly, can now be realised as a system-on-chip. Furthermore, low cost broadband communication media for wide area communication as well as for the realisation of local distributed systems are available. Typically the market requires IT systems that realise a set of specific features for the end user in a given environment, so called embedded systems. Some examples for such embedded systems are control systems in cars, airplanes, houses or plants, information and communication devices like digital TV, mobile phones or autonomous systems like service- or edutainment robots. For the design of embedded systems the designer has to tackle three major aspects: The application itself including the man-machine interface, The (target) architecture of the system including all functional and non-functional constraints and, the design methodology including modelling, specification, synthesis, test and validation. The last two points are a major focus of this book. This book documents the high quality approaches and results that were presented at the International Workshop on Distributed and Parallel Embedded Systems (DIPES 2000), which was sponsored by the International Federation for Information Processing (IFIP), and organised by IFIP working groups WG10.3, WG10.4 and WG10.5. The workshop took place on October 18-19, 2000, in Schloß Eringerfeld near Paderborn, Germany. Architecture and Design of Distributed Embedded Systems is organised similar to the workshop. Chapters 1 and 4 (Methodology I and II) deal with different modelling and specification paradigms and the corresponding design methodologies. Generic system architectures for different classes of embedded systems are presented in Chapter 2. In Chapter 3 several design environments for the support of specific design methodologies are presented. Problems concerning test and validation are discussed in Chapter 5. The last two chapters include distribution and communication aspects (Chapter 6) and synthesis techniques for embedded systems (Chapter 7). This book is essential reading for computer science researchers and application developers.
R 4,646.37
Hands-On Data Structures and Algorithms with Python
Learn to implement complex data structures and algorithms using PythonKey FeaturesUnderstand the analysis and design of fundamental Python data structuresExplore advanced Python concepts such as Big O notation and dynamic programmingLearn functional and reactive implementations of traditional data structuresBook DescriptionData structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications.This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail.By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.What you will learnUnderstand object representation, attribute binding, and data encapsulationGain a solid understanding of Python data structures using algorithmsStudy algorithms using examples with pictorial representationLearn complex algorithms through easy explanation, implementing PythonBuild sophisticated and efficient data applications in PythonUnderstand common programming algorithms used in Python data scienceWrite efficient and robust code in Python 3.7Who this book is forThis book is for developers who want to learn data structures and algorithms in Python to write complex and flexible programs. Basic Python programming knowledge is expected.
R 1,498.00
Systems Architecture
Architecture and Function of Complex SystemsSystem architecture is the study of early decision making in complex systems. This text teaches how to capture experience and analysis about early system decisions, and how to choose architectures that meet stakeholder needs, integrate easily, and evolve flexibly. With case studies written by leading practitioners, from hybrid cars to communications networks to aircraft, this text showcases the science and art of system architecture.
R 5,689.00
Mobile and Wireless Communications with Practical Use-Case Scenarios
The growing popularity of advanced multimedia-rich applications along with the increasing affordability of high-end smart mobile devices has led to a massive growth in mobile data traffic that puts significant pressure on the underlying network technology. However, no single network technology will be equipped to deal with this explosion of mobile data traffic. While wireless technologies had a spectacular evolution over the past years, the present trend is to adopt a global heterogeneous network of shared standards that enables the provisioning of quality of service and quality of experience to the end-user. To this end, enabling technologies like machine learning, Internet of Things and digital twins are seen as promising solutions for next generation networks that will enable an intelligent adaptive interconnected environment with support for prediction and decision making so that the heterogeneous applications and users' requirements can be highly satisfied. The aim of this textbook is to provide the readers with a comprehensive technical foundation of the mobile communication systems and wireless network design, and operations and applications of various radio access technologies. Additionally, it also introduces the reader to the latest advancements in technologies in terms of Internet of Things ecosystems, machine learning and digital twins for IoT-enabled intelligent environments. Furthermore, this textbook also includes practical use-case scenarios using Altair WinProp Software as well as Python, TensorFlow and Jupyter as support for practice-based laboratory sessions.
R 2,650.15
JavaTech, an Introduction to Scientific and Technical Computing with Java
JavaTech is a practical introduction to the Java programming language with an emphasis on the features that benefit technical computing. After presenting the basics of object-oriented programming in Java, it examines introductory topics such as graphical interfaces and thread processes. It goes on to review network programming and develops Web client-server examples for tasks such as monitoring remote devices. The focus then shifts to distributed computing with RMI. Finally, it examines how Java programs can access the local platform and interact with hardware. Topics include combining native code with Java, communication via serial lines, and programming embedded processors. An extensive web site supports the book with additional instructional materials. JavaTech demonstrates the ease with which Java can be used to create powerful network applications and distributed computing applications. It will be used as a textbook for programming courses, and by researchers who need to learn Java for a particular task.
R 2,872.00
Architecture Design and Validation Methods
This state-of-the-art survey gives a systematic presentation of recent advances in the design and validation of computer architectures. The book covers a comprehensive range of architecture design and validation methods, from computer aided high-level design of VLSI circuits and systems to layout and testable design, including the modeling and synthesis of behavior and dataflow, cell-based logic optimization, machine assisted verification, and virtual machine design.
R 1,566.79
Practical Numerical and Scientific Computing with MATLAB® and Python
Practical Numerical and Scientific Computing with MATLAB® and Python concentrates on the practical aspects of numerical analysis and linear and non-linear programming. It discusses the methods for solving different types of mathematical problems using MATLAB and Python. Although the book focuses on the approximation problem rather than on error analysis of mathematical problems, it provides practical ways to calculate errors.The book is divided into three parts, covering topics in numerical linear algebra, methods of interpolation, numerical differentiation and integration, solutions of differential equations, linear and non-linear programming problems, and optimal control problems.This book has the following advantages:It adopts the programming languages, MATLAB and Python, which are widely used among academics, scientists, and engineers, for ease of use and contain many libraries covering many scientific and engineering fields.It contains topics that are rarely found in other numerical analysis books, such as ill-conditioned linear systems and methods of regularization to stabilize their solutions, nonstandard finite differences methods for solutions of ordinary differential equations, and the computations of the optimal controls. It provides a practical explanation of how to apply these topics using MATLAB and Python.It discusses software libraries to solve mathematical problems, such as software Gekko, pulp, and pyomo. These libraries use Python for solutions to differential equations and static and dynamic optimization problems.Most programs in the book can be applied in versions prior to MATLAB 2017b and Python 3.7.4 without the need to modify these programs.This book is aimed at newcomers and middle-level students, as well as members of the scientific community who are interested in solving math problems using MATLAB or Python.
R 5,652.87
R 428.00
Architecture of Computing Systems - ARCS 2012
This book constitutes the refereed proceedings of the 25th International Conference on Architecture of Computing Systems, ARCS 2012, held in Munich, Germany, in February/March 2012.The 20 revised full papers presented in 7 technical sessions were carefully reviewed and selected from 65 submissions. The papers are organized in topical sections on robustness and fault tolerance, power-aware processing, parallel processing, processor cores, optimization, and communication and memory.
R 1,551.22
Solution Architecture Foundations
The field of solution architecture is fast evolving, this brand new edition gives you the tools you need to stay ahead. Introducing proven techniques within a structured framework and life cycle, this essential guide supports you from problem definition through to designing holistic, evidence-based solutions.The second edition adds new topics such as AI architecture, cloud architecture, security requirements, and data science integration, thereby ensuring you have the knowledge and practical guidance to create secure, scalable, and future-ready solutions.Solution Architecture Foundations retains its place as the indispensable guide for newcomers and a trusted resource for experienced professionals looking to deepen and refresh their expertise.
R 1,740.00
