Unlike other resources that target only programming communities, this book targets both programming and business communities. With programming models shifting more towards no-code and low-code, citizen programmers from the business side will welcome this book as a guide for how to design and optimize their information pipeline while lowering costs for infrastructure. Programmers, on the other hand, will welcome this book's business-centric programming view, which will get them a step closer to fulfilling real business requirements. Practical Spring Cloud Function touches on the themes of portability, scalability, high performance and high availability. Each theme is explored via a real enterprise use case and code. The use cases target industries including energy (oil pipeline sensors), automotive (event-driven connected vehicles), and retail (conversational AI). After reading this book, you'll come away with the know-how to build and deploy cloud-native Java applications effectively and efficiently. What You Will Learn Write functions and deploy to Amazon Web Services, Microsoft Azure, Google Cloud, IBM Cloud, and on-prem clouds such as VMWare Tanzu and RedHat OpenShift Set up locally with KNative on Kubernetes, as well as on AWS, Azure, GCP, Tanzu, and others Build, test, and deploy a simple example with Spring Cloud Function Develop an event-driven data pipeline with Spring Cloud Function Integrate with AI and machine learning models Apply Spring Cloud Function to the Internet of Things (IoT) Get industry-specific examples of Spring Cloud Function in action Who This Book Is For Software and cloud-native application developers with prior programming experience in the cloud and/or Spring Framework. DevOps professionals may find this book beneficial as well.

CUDA for Engineers gives you direct, hands-on engagement with personal, high-performance parallel computing, enabling you to do computations on a gaming-level PC that would have required a supercomputer just a few years ago. The authors introduce the essentials of CUDA C programming clearly and concisely, quickly guiding you from running sample programs to building your own code. Throughout, you'll learn from complete examples you can build, run, and modify, complemented by additional projects that deepen your understanding. All projects are fully developed, with detailed building instructions for all major platforms. Ideal for any scientist, engineer, or student with at least introductory programming experience, this guide assumes no specialized background in GPU-based or parallel computing. In an appendix, the authors also present a refresher on C programming for those who need it. Coverage includes Preparing your computer to run CUDA programs Understanding CUDA's parallelism model and C extensions Transferring data between CPU and GPU Managing timing, profiling, error handling, and debugging Creating 2D grids Interoperating with OpenGL to provide real-time user interactivity Performing basic simulations with differential equations Using stencils to manage related computations across threads Exploiting CUDA's shared memory capability to enhance performance Interacting with 3D data: slicing, volume rendering, and ray casting Using CUDA libraries Finding more CUDA resources and code Realistic example applications include Visualizing functions in 2D and 3D Solving differential equations while changing initial or boundary conditions Viewing/processing images or image stacks Computing inner products and centroids Solving systems of linear algebraic equations Monte-Carlo computations

Spring Framework 6 remains - by far - the leading de-facto "out of the box" practical Java meta application development framework for building complex enterprise, cloud-native applications as well as web applications and microservices. Introducing Spring Framework 6 is your hands-on tutorial guide for learning the Spring Framework 6 from top to bottom, and allows you to build an example application along the way from the ground-up. As you learn the Spring Framework over the course of this book, you'll incrementally build your first Spring application piece-by-piece as you learn each module, project or component of the Spring Framework and its extensions and ecosystem. As you learn the various fundamentals, you'll then apply them immediately to your Spring application. This Spring application, My Documents, enables you to learn by doing. After reading this book, you will have the essentials you should need to start using the Spring Framework and building your own Java-based applications or microservices with it. What you'll learn: Get started with Spring Framework 6 by VMWare Tanzu and the Spring community Build your first My Documents application using Spring Framework and its extensions Test your Spring application Add persistence to your application using Spring Data JPA and more Show your Spring application on the Web with Spring MVC and related Use REST APIs to enhance your application and add messaging with Kafka and AMQP Integrate your Spring application with external systems using Spring Integration toolkit Who is this book for: This book is for those aspiring software developers and programmers who are new to Spring. Some prior programming experience recommended, preferably in Java.

For use as a core text supplement in any course covering common LISP such as Artificial Intelligence or Concepts of Programming Languages.

Teaching students new and more powerful ways of thinking about programs, this text contains a tutorial—full of examples—that explains all the essential concepts of Lisp programming, plus an up- to-date summary of ANSI Common Lisp, listing every operator in the language. Informative and fun, it gives students everything they need to start writing programs in Lisp both efficiently and effectively, and highlights such innovative Lisp features as automatic memory management, manifest typing, closures, and more.

A Comprehensive Study of SQL - Practice and Implementation is designed as a textbook and provides a comprehensive approach to SQL (Structured Query Language), the standard programming language for defining, organizing, and exploring data in relational databases. It demonstrates how to leverage the two most vital tools for data query and analysis - SQL and Excel - to perform comprehensive data analysis without the need for a sophisticated and expensive data mining tool or application. Features The book provides a complete collection of modeling techniques, beginning with fundamentals and gradually progressing through increasingly complex real-world case studies It explains how to build, populate, and administer high-performance databases and develop robust SQL-based applications It also gives a solid foundation in best practices and relational theory The book offers self-contained lessons on key SQL concepts or techniques at the end of each chapter using numerous illustrations and annotated examples This book is aimed primarily at advanced undergraduates and graduates with a background in computer science and information technology. Researchers and professionals will also find this book useful.

Features Suitable for undergraduates and early postgraduates who need simple and accessible guidance for solving practical interdisciplinary technical problems Can be used as an additional textbook in a variety of topics, including Calculus, Linear Algebra, Analytical Geometry, Discrete Mathematics, Computer Science, Computational Mathematics, Scientific Visualization, Computer Graphics Gives computer users access to an exciting new hobby - solving complex problems described in fiction.

Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the authors gained a unique perspective on the requirements and attitudes of users as well as manufacturers of parallel computers.

The text first introduces the architecture of modern cache-based microprocessors and discusses their inherent performance limitations, before describing general optimization strategies for serial code on cache-based architectures. It next covers shared- and distributed-memory parallel computer architectures and the most relevant network topologies. After discussing parallel computing on a theoretical level, the authors show how to avoid or ameliorate typical performance problems connected with OpenMP. They then present cache-coherent nonuniform memory access (ccNUMA) optimization techniques, examine distributed-memory parallel programming with message passing interface (MPI), and explain how to write efficient MPI code. The final chapter focuses on hybrid programming with MPI and OpenMP.

Users of high performance computers often have no idea what factors limit time to solution and whether it makes sense to think about optimization at all. This book facilitates an intuitive understanding of performance limitations without relying on heavy computer science knowledge. It also prepares readers for studying more advanced literature.

Read about the authors’ recent honor: Informatics Europe Curriculum Best Practices Award for Parallelism and Concurrency

Table of Contents

Modern Processors

Stored-program computer architecture

General-purpose cache-based microprocessor architecture

Memory hierarchies

Multicore processors

Multithreaded processors

Vector processors

Basic Optimization Techniques for Serial Code

Scalar profiling

Common sense optimizations

Simple measures, large impact

The role of compilers

C++ optimizations

Data Access Optimization

Balance analysis and lightspeed estimates

Storage order

Case study: The Jacobi algorithm

Case study: Dense matrix transpose

Algorithm classification and access optimizations

Case study: Sparse matrix-vector multiply

Parallel Computers

Taxonomy of parallel computing paradigms

Shared-memory computers

Distributed-memory computers

Hierarchical (hybrid) systems

Networks

Basics of Parallelization

Why parallelize?

Parallelism

Parallel scalability

Shared-Memory Parallel Programming with OpenMP

Short introduction to OpenMP

Case study: OpenMP-parallel Jacobi algorithm

Advanced OpenMP: Wavefront parallelization

Efficient OpenMP Programming

Profiling OpenMP programs

Performance pitfalls

Case study: Parallel sparse matrix-vector multiply

Locality Optimizations on ccNUMA Architectures

Locality of access on ccNUMA

Case study: ccNUMA optimization of sparse MVM

Placement pitfalls

ccNUMA issues with C++

Distributed-Memory Parallel Programming with MPI

Message passing

A short introduction to MPI

Example: MPI parallelization of a Jacobi solver

Efficient MPI Programming

MPI performance tools

Communication parameters

Synchronization, serialization, contention

Reducing communication overhead

Understanding intranode point-to-point communication

Hybrid Parallelization with MPI and OpenMP

Basic MPI/OpenMP programming models

MPI taxonomy of thread interoperability

Hybrid decomposition and mapping

Potential benefits and drawbacks of hybrid programming

Appendix A: Topology and Affinity in Multicore Environments

Appendix B: Solutions to the Problems

Bibliography

Index

Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow-up to the topics discussed in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. Features: Targets readers with a background in programming, who are interested in the tools used in data analytics and data science Uses Python throughout Presents tools, alongside solved examples, with steps that the reader can easily reproduce and adapt to their needs Focuses on the practical use of the tools rather than on lengthy explanations Provides the reader with the opportunity to use the book whenever needed rather than following a sequential path The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others, providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered. The book discusses the need to develop data products and addresses the subject of bringing models to their intended audiences - in this case, literally to the users' fingertips in the form of an iPhone app. About the Author Dr. Jesus Rogel-Salazar is a lead data scientist in the field, working for companies such as Tympa Health Technologies, Barclays, AKQA, IBM Data Science Studio and Dow Jones. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK.

Take a problem-solution approach for programming enterprise Java or Java EE applications and microservices for cloud-based solutions, enterprise database applications, and even small business web applications. Java EE to Jakarta EE 10 Recipes provides effective, practical, and proven code snippets that you can immediately use to accomplish just about any task that you may encounter. You can feel confident using the reliable solutions that are demonstrated in this book in your personal or corporate environment. Java EE was made open source under the Eclipse Foundation, and Jakarta EE is the new name for what used to be termed the Java Platform, Enterprise Edition. This book helps you rejuvenate your Java expertise and put the platform's latest capabilities to use for quickly developing robust applications. If you are new to Jakarta EE, this book will help you learn the features of the platform and benefit from one of the most widely used and powerful technologies available for cloud-native enterprise application development today. Examples in this book highlight Jakarta EE's capabilities, helping you to build streamlined and reliable applications using the latest in Java technologies. The book takes a problem-solution approach in which each section introduces a common programming problem, showing you how to solve that problem in the best possible way using the latest features in Jakarta EE. Solutions in the form of working code examples are presented that you can download and use immediately in your own projects. Clear descriptions are provided to help you understand and learn to build further on the solutions provided. This is the ideal book for the code-focused programmer interested in keeping up with the future of enterprise development on the Java Platform. What You Will Learn Develop enterprise java applications using the latest open-source Jakarta EE platform Create great-looking user interfaces using Jakarta Servlets, Jakarta Server Pages, Jakarta Server Faces and the Eclipse Krazo framework (an implementation of Jakarta MVC) Build database applications using Jakarta NoSQL, Jakarta Persistence, and Jakarta Enterprise Beans. Develop enterprise grade applications using Context & Dependency Injection, and Jakarta RESTFul web services Automate testing through cohesive test suites built on Arquillian for Jakarta EE applications Build loosely coupled distributed applications using Jakarta Messaging Deploy microservices applications in cloud environments using Docker Secure applications utilizing the Jakarta EE Security API Who This Book Is For Java developers interested in quickly finding effective and proven solutions without reading through a lengthy manual and scrubbing for techniques.

Perennial favorites, Charlotte Kaslas "If the Buddha Dated and If the Buddha Married" have inspired readers with their empowering blend of spiritual and psychological insights. Her latest, "If the Buddha Got Stuck," is a wise yet lighthearted book that will speak to anyone who's ever experienced being stuck in life and wanted to break free. With her signature clarity, wisdom, and warm heart, Kasl presents readers with seven steps that tap into lifeas bigger picture: Notice Where Youare Stuck; Show Up; Pay Attention; Live in Reality; Connect with Others; Move From Thought to Action; and Let Go. Full of insight from Buddhist and other teachings that emphasize the joy that comes with letting go of attachments to events and things, "If the Buddha Got Stuck" is an inspirational and practical roadmap to a more joyful, peaceful, and fulfilling life.

Written by two very experienced instructors, with more than thirty years of teaching experience between them; Presents material that is grounded in practical applications that are representative of the problems researchers encounter in real life; Teaches readers the core features of modern JavaScript; Covers programming with callbacks and promises; Describes how to build data services and data visualization;

This book brings together a number of researchers and developers from industry and academia who report on their work. It is of interest to language designers and the creators of toolkits, UIMSs, and other user interface tools.

Python for Scientific Computation and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web.

Agile Systems Engineering presents a vision of systems engineering where precise specification of requirements, structure, and behavior meet larger concerns as such as safety, security, reliability, and performance in an agile engineering context. World-renown author and speaker Dr. Bruce Powel Douglass incorporates agile methods and model-based systems engineering (MBSE) to define the properties of entire systems while avoiding errors that can occur when using traditional textual specifications. Dr. Douglass covers the lifecycle of systems development, including requirements, analysis, design, and the handoff to specific engineering disciplines. Throughout, Dr. Douglass couples agile methods with SysML and MBSE to arm system engineers with the conceptual and methodological tools they need to avoid specification defects and improve system quality while simultaneously reducing the effort and cost of systems engineering.

It is a textbook that provides a thorough introduction to the C++ programming language. Introduction to the C++ language in a substantial, non-tiring way, including hints and advices for writing clear, reliable, and efficient code. Numerous programming exercises of progressive difficulty and non-obvious short questions.

The authoritative resource to writing clear and idiomatic Go to solve real-world problems Google's Go team member Alan A. A. Donovan and Brian Kernighan, co-author of The C Programming Language, provide hundreds of interesting and practical examples of well-written Go code to help programmers learn this flexible, and fast, language. It is designed to get you started programming with Go right away and then to progress on to more advanced topics. Basic components: an opening tutorial provides information and examples to get you off the ground and doing useful things as quickly as possible. This includes: command-line arguments gifs URLs web servers Program structure: simple examples cover the basic structural elements of a Go program without getting sidetracked by complicated algorithms or data structures. Data types: Go offers a variety of ways to organize data, with a spectrum of data types that at one end match the features of the hardware and at the other end provide what programmers need to conveniently represent complicated data structures. Composite types: arrays slices maps structs JSON test and HTML templates Functions: break a big job into smaller pieces that might well be written by different people separated by both time and space. Methods: declarations with a pointer receiver struct embedding values and expressions Interfaces: write functions that are more flexible and adaptable because they are not tied to the details of one particular implementation. Concurrent programming: Goroutines, channels, and with shared variables. Packages: use existing packages and create new ones. Automated testing: write small programs that check the code. Reflection features: update variables and inspect their values at run time. Low-level programming: step outside the usual rules to achieve the highest possible performance, interoperate with libraries written in other languages, or implement a function that cannot be expressed in pure Go. Each chapter has exercises to test your understanding and explore extensions and alternatives. Source code is freely available for download and may be conveniently fetched, built, and installed using the go get command.

Sharpen your coding skills by exploring established computer science problems! Classic Computer Science Problems in Java challenges you with time-tested scenarios and algorithms. You'll work through a series of exercises based in computer science fundamentals that are designed to improve your software development abilities, improve your understanding of artificial intelligence, and even prepare you to ace an interview. Classic Computer Science Problems in Java will teach you techniques to solve common-but-tricky programming issues. You'll explore foundational coding methods, fundamental algorithms, and artificial intelligence topics, all through code-centric Java tutorials and computer science exercises. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your "new" problems! Key Features * Recursion, memorization, bit manipulation * Search algorithms * Constraint-satisfaction problems * Graph algorithms * K-means clustering For intermediate Java programmers. About the technology In any computer science classroom you'll find a set of tried-and-true algorithms, techniques, and coding exercises. These techniques have stood the test of time as some of the best ways to solve problems when writing code, and expanding your Java skill set with these classic computer science methods will make you a better Java programmer. David Kopec is an assistant professor of computer science and innovation at Champlain College in Burlington, Vermont. He is the author of Dart for Absolute Beginners (Apress, 2014), Classic Computer Science Problems in Swift (Manning, 2018), and Classic Computer Science Problems in Python (Manning, 2019).

For courses in Visual Basic Programming. A Current and Comprehensive Introduction to Visual Basic Programming Schneider's Introduction to Programming Using Visual Basic has been consistently praised in the industry since 1991 and is a favorite of instructors and students. The 11th Edition is updated for Visual Basic 2017, providing an ideal tool for students learning their first programming language. The text keeps pace with modern programming methodology while incorporating current content and good programming practices. Schneider emphasizes problem solving by discussing problem-solving techniques early and using them throughout the book. He also ensures each chapter is rich yet concise by developing chapters around crucial subjects rather than covering too many topics superficially. The new edition provides a broad range of real-world examples, section-ending exercises, case studies, and programming projects that provide students with the most current and hands-on experience of any Visual Basic book on the market. The number and range of projects give instructors the flexibility to adapt the course according to the interests and abilities of students. Some programming projects in later chapters can be assigned as end-of-the-semester projects. Also available with MyLab Programming MyLab (TM) is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab personalizes the learning experience and improves results for each student.With MyLab Programming, students work through hundreds of short, auto-graded coding exercises and receive immediate and helpful feedback based on their work. Note: You are purchasing a standalone product; MyLab Programming does not come packaged with this content. Students, if interested in purchasing this title with MyLab Programming, ask your instructor for the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information. If you would like to purchase both the physical text and MyLab Programming, search for: 0135862167 / 9780135862162 Introduction to Programming Using Visual Basic Plus MyLab Programming - Access Card Package, 11e Package consists of: 0135416116 / 9780135416112 MyLab Programming Standalone Access Card 0135416035 / 9780135416037 Introduction to Programming Using Visual Basic

Many students of C will rightly admit that it's not an easy language to learn, but the professional insight, clear explanations, examples, and pictures in the Cengage Learning for the Absolute Beginner series make learning C easy and fun. Programming is not a skill you can acquire by reading; you have to write programs to learn. That's why each chapter in this book contains programming challenges, a chapter review, and a complete program that uses chapter-based concepts to construct an easily built application. With the guidance in this book, you'll learn how to create algorithms and pseudocode to think through and design programs; translate your designs and plans into working C programs; write, compile, test, and debug your code; use data types, arrays, pointers, strings, file operations and more to create robust programs.

This Element discusses how shiny, an R package, can help instructors teach quantitative methods more effectively by way of interactive web apps. The interactivity increases instructors' effectiveness by making students more active participants in the learning process, allowing them to engage with otherwise complex material in an accessible, dynamic way. The Element offers four detailed apps that cover two fundamental linear regression topics: estimation methods (least squares, maximum likelihood) and the classic linear regression assumptions. It includes a summary of what the apps can be used to demonstrate, detailed descriptions of the apps' full capabilities, vignettes from actual class use, and example activities. Two other apps pertain to a more advanced topic (LASSO), with similar supporting material. For instructors interested in modifying the apps, the Element also documents the main apps' general code structure, highlights some of the more likely modifications, and goes through what functions need to be amended.