Supercharge your applications with the ultimate guide to asynchronous and multithreaded programming in C#!C# Concurrency teaches you how to write effective multithreaded and asynchronous software in C#. Practical techniques, real-world examples, and useful code samples cut through the confusion around async/await and help you write rapid, reliable, and bug-free code. In C# Concurrency: Asynchronous and Multithreaded Programming you’ll learn how to: • Take full advantage of async/await • Write bug-free multithreaded code every time • Create multithreaded code that delivers real performance improvements • Grok C# and .NET multithreading and asynchronous primitives • Know when to use concurrency techniques—and when not to use them! In C# Concurrency Nir Dobovizki, a seasoned C# veteran with over 30 years of high-performance programming experience, shares his deep knowledge and expert techniques. Say goodbye to frustrating pitfalls and impossible-to-find bugs that slow down your applications. Nir's careful approach will teach you how to navigate these challenges with ease, allowing you to achieve lightning-fast performance like never before! About the technology Asynchronous and multithreaded programs can perform multiple tasks simultaneously without losing speed or reliability. But getting concurrency right can challenge even experienced developers. This practical book teaches you to deliver concurrent C# apps that are lighting fast and free of the deadlocks and other synchronization issues that undermine performance and take forever to find. About the book C# Concurrency equips programmers with a comprehensive understanding of multithreading and asynchronous programming, focusing on the practical use of the C# async-await feature to simplify asynchronous tasks. It teaches how to avoid common pitfalls, addresses classic multithreading issues like deadlocks and race conditions, and advanced topics such as controlling thread of execution and using thread-safe collections. What's inside • .NET multithreading and asynchronous primitives • When to use concurrency techniques—and when not to! • Confidently use async/await About the reader For experienced C# programmers. No knowledge of asynchro- nous programming required. About the author Nir Dobovizki is a senior software architect and consultant who has worked on concurrent and asynchronous systems since the late 90s. Table of Contents 1 Asynchronous programming and multithreading 2 The compiler rewrites your code 3 The async and await keywords 4 Multithreading basics 5 async/await and multithreading 6 When to use async/await 7 Classic multithreading pitfalls and how to avoid them Part 2 8 Processing a sequence of items in the background 9 Canceling background tasks 10 Await your own events 11 Controlling on which thread your asynchronous code runs 12 Exceptions and async/await 13 Thread-safe collections 14 Generating collections asynchronously/await foreach and IAsyncEnumerable Read more

A comprehensive guide to help aspiring and professional C++ developers elevate the performance of their apps by allowing them to run faster and consume fewer resources.Purchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesUpdated to C++20 with completely revised code and more content on error handling, benchmarking, memory allocators, and concurrent programmingExplore the latest C++20 features including concepts, ranges, and coroutinesUtilize C++ constructs and techniques to carry out effective data structure optimization and memory managementBook DescriptionC++ High Performance, Second Edition guides you through optimizing the performance of your C++ apps. This allows them to run faster and consume fewer resources on the device they're running on without compromising the readability of your codebase.The book begins by introducing the C++ language and some of its modern concepts in brief. Once you are familiar with the fundamentals, you will be ready to measure, identify, and eradicate bottlenecks in your C++ codebase. By following this process, you will gradually improve your style of writing code. The book then explores data structure optimization, memory management, and how it can be used efficiently concerning CPU caches.After laying the foundation, the book trains you to leverage algorithms, ranges, and containers from the standard library to achieve faster execution, write readable code, and use customized iterators. It provides hands-on examples of C++ metaprogramming, coroutines, reflection to reduce boilerplate code, proxy objects to perform optimizations under the hood, concurrent programming, and lock-free data structures. The book concludes with an overview of parallel algorithms.By the end of this book, you will have the ability to use every tool as needed to boost the efficiency of your C++ projects.What you will learnWrite specialized data structures for performance-critical codeUse modern metaprogramming techniques to reduce runtime calculationsAchieve efficient memory management using custom memory allocatorsReduce boilerplate code using reflection techniquesReap the benefits of lock-free concurrent programmingGain insights into subtle optimizations used by standard library algorithmsCompose algorithms using ranges libraryDevelop the ability to apply metaprogramming aspects such as constexpr, constraints, and conceptsImplement lazy generators and asynchronous tasks using C++20 coroutinesWho this book is forIf you're a C++ developer looking to improve the efficiency of your code or just keen to upgrade your skills to the next level, this book is for you.Table of ContentsA Brief Introduction to C++Essential C++ TechniquesAnalyzing and Measuring PerformanceData StructuresAlgorithmsUsing Ranges and ViewsMemory ManagementCompile-Time ProgrammingEssential UtilitiesProxy Objects and Lazy EvaluationConcurrencyCoroutines and Lazy GeneratorsAsynchronous Programming with CoroutinesParallel STL Algorithms Read more

Mastering GPU Programming with Python: From Basics to Advanced TechniquesAbout the Technology:Unlock the hidden superpower within your computer - the Graphics Processing Unit (GPU). Once reserved for stunning visuals in games, GPUs have evolved into computational powerhouses, capable of performing thousands of calculations simultaneously. This translates into lightning-fast execution of complex tasks, from scientific simulations to cutting-edge AI models.Written by an experienced Python programmer and GPU enthusiast, this book isn't just a dry recitation of facts. It's a guided journey, sharing insights and lessons learned from countless hours spent optimizing code and pushing the boundaries of GPU capabilities. You'll benefit from practical tips and real-world examples that bridge the gap between theory and practice.Summary of the Book:Starting from the fundamentals of GPU architecture and parallel programming, this book takes you step-by-step through the essential concepts and techniques. You'll learn how to write efficient GPU kernels, manage memory effectively, and optimize data transfers between CPU and GPU. As you progress, you'll delve into advanced CUDA features, leverage specialized libraries for tasks like linear algebra and deep learning, and even integrate CUDA with other languages like C++.Why This Book:Don't let computationally intensive tasks slow you down. This book empowers you to:Break free from CPU limitations: Experience the thrill of speed as you witness your code execute orders of magnitude faster on GPUs.Tackle complex problems with ease: Solve computationally demanding tasks that were once out of reach, opening doors to new possibilities and breakthroughs.Become a sought-after expert: Gain a valuable skill set that's in high demand across various industries, from tech giants to research labs.Future-proof your career: Stay ahead of the curve as GPU computing continues to revolutionize the world of technology.About the Reader:This book is ideal for Python programmers with a thirst for high-performance computing. Whether you're a student, researcher, data scientist, or software engineer, if you're ready to take your Python skills to the next level and unleash the true potential of your GPU, this book is for you.Don't waste another minute watching progress bars inch forward. Invest in this book and transform your computational experience. Imagine the possibilities that await as you harness the power of parallel processing and accelerate your Python code to new heights.Ready to unlock the hidden superpower within your computer? Grab your copy of "Mastering GPU Programming with Python" today and embark on an exhilarating journey into the world of high-performance computing! Read more

"CUDA Programming in C: From Basics to Expert Proficiency" is a comprehensive guide designed to equip both novice and experienced developers with the knowledge and skills needed to harness the power of CUDA and parallel computing. Through a systematic and detailed approach, this book delves into the core concepts of CUDA programming, beginning with an introduction to parallel computing and the CUDA platform, and progressing to advanced features and performance optimization techniques. Each chapter provides in-depth explanations, practical examples, and invaluable insights into real-world applications, making complex subjects accessible and engaging.This book covers essential topics such as memory management, thread hierarchy, kernel functions, debugging, and profiling, ensuring a strong foundation in CUDA programming. Additionally, it explores advanced CUDA features and their applications in various domains, from high-performance computing to machine learning and scientific simulations. With clear instructions, structured learning paths, and practical case studies, "CUDA Programming in C: From Basics to Expert Proficiency" is an indispensable resource for developers seeking to unlock the full potential of their GPU hardware and create high-performance, efficient software solutions. Read more

Learning YAML for pipeline development is crucial for professionals in the software development and DevOps fields. YAML, or "YAML Ain't Markup Language," is a human-readable data serialization format that has gained significant popularity due to its simplicity and versatility. It is widely used in various tools, including continuous integration and delivery (CI/CD) pipelines, as it allows for the automation of complex workflows. Understanding YAML enables professionals to define build sequences, automate deployments, and configure diverse stages within a pipeline. Moreover, its syntax promotes code reusability and maintainability by offering modularity through reusable templates. By mastering YAML, professionals can effectively streamline their development processes and ensure consistent and error-free deployments. As pipeline development becomes increasingly essential for efficient software delivery, acquiring skills in YAML offers professionals a competitive edge, enabling them to create robust CI/CD pipelines that are responsive to changing business needs. Read more

Systems programming provides the foundation for the world's computation. Writing performance-sensitive code requires a programming language that puts programmers in control of how memory, processor time, and other system resources are used. The Rust systems programming language combines that control with a modern type system that catches broad classes of common mistakes, from memory management errors to data races between threads.With this practical guide, experienced systems programmers will learn how to successfully bridge the gap between performance and safety using Rust. Jim Blandy, Jason Orendorff, and Leonora Tindall demonstrate how Rust's features put programmers in control over memory consumption and processor use by combining predictable performance with memory safety and trustworthy concurrency.You'll learn:Rust's fundamental data types and the core concepts of ownership and borrowingHow to write flexible, efficient code with traits and genericsHow to write fast, multithreaded code without data racesRust's key power tools: closures, iterators, and asynchronous programmingCollections, strings and text, input and output, macros, unsafe code, and foreign function interfacesThis revised, updated edition covers the Rust 2021 Edition. Read more

Trade more profitably by exploiting Microsoft Excel’s powerful statistical and data mining tools:  ·    Uncover subtle anomalies and distortions that signal profit opportunities·    Create powerful new custom indicators, alerts, and trading models·    Visualize and analyze huge amounts of trading data with just a few clicks ·    Powerful techniques for every active investor who can use Excel Now that high-speed traders dominate the market, yesterday’s slower-paced analysis strategies are virtually worthless. To outperform, individual traders must discover fleeting market trends and inefficiencies and act on them before they disappear. Five years ago, this required multimillion-dollar data mining and analytical infrastructures. Today, traders can use Excel with the help of world-class trader Jeff Augen’s Microsoft Excel for Stock and Option Traders: Build your Own Analytical Tools for Higher Returns.  Augen shows how to use Excel 2007 or 2010 to uncover hidden correlations and reliable trade triggers based on subtle anomalies and price distortions, create and test new hypotheses others haven’t considered, and visualize data to reveal insights others can’t see! "Jeff Augen turns things inside out in his remarkable and challenging book Microsoft Excel for Stock and Option Traders."  - John A. Sarkett, SFO Magazine, October 2011 Read more

Multicore and GPU Programming: An Integrated Approach, Second Edition offers broad coverage of key parallel computing tools, essential for multi-core CPU programming and many-core "massively parallel" computing. Using threads, OpenMP, MPI, CUDA and other state-of-the-art tools, the book teaches the design and development of software capable of taking advantage of modern computing platforms that incorporate CPUs, GPUs and other accelerators.Presenting material refined over more than two decades of teaching parallel computing, author Gerassimos Barlas minimizes the challenge of transitioning from sequential programming to mastering parallel platforms with multiple examples, extensive case studies, and full source code. By using this book, readers will better understand how to develop programs that run over distributed memory machines using MPI, create multi-threaded applications with either libraries or directives, write optimized applications that balance the workload between available computing resources, and profile and debug programs targeting parallel machines.- Includes comprehensive coverage of all major multi-core and many-core programming tools and platforms, including threads, OpenMP, MPI, CUDA, OpenCL and Thrust- Covers the most recent versions of the above at the time of publication- Demonstrates parallel programming design patterns and examples of how different tools and paradigms can be integrated for superior performance- Updates in the second edition include the use of the C++17 standard for all sample code, a new chapter on concurrent data structures, a new chapter on OpenCL, and the latest research on load balancing- Includes downloadable source code, examples and instructor support materials on the book's companion website Read more

Design and develop high-performance software solutions by using concurrent and asynchronous techniques provided by the most modern features in C++20 and C++23Key FeaturesLearn how to use modern C++ features, including futures, promises, async, and coroutines to build asynchronous solutionsDevelop cross-platform network and low-level I/O projects with Boost.AsioMaster optimization techniques by understanding how software adapts to machine hardwarePurchase of the print or Kindle book includes a free PDF eBookBook DescriptionAs hardware advancements continue to accelerate, bringing greater memory capacity and more CPU cores, software must evolve to adapt to efficiently use all available resources and reduce idle CPU cycles. In this book, two seasoned software engineers with about five decades of combined experience will teach you how to implement concurrent and asynchronous solutions in C++.You’ll gain a comprehensive understanding of parallel programming paradigms—covering concurrent, asynchronous, parallel, multithreading, reactive, and event-driven programming, as well as dataflows—and see how threads, processes, and services are related. Moving into the heart of concurrency, the authors will guide you in creating and managing threads and exploring C++’s thread-safety mechanisms, including mutual exclusion, atomic operations, semaphores, condition variables, latches, and barriers. With this solid foundation, you’ll focus on pure asynchronous programming, discovering futures, promises, the async function, and coroutines. The book takes you step by step through using Boost.Asio and Boost.Cobalt to develop network and low-level I/O solutions, proven performance and optimization techniques, and testing and debugging asynchronous software.By the end of this C++ book, you’ll be able to implement high-performance software using modern asynchronous C++ techniques.What you will learnExplore the different parallel paradigms and know when to apply themAcquire deep knowledge of thread management and safety mechanismsUnderstand asynchronous programming in C++, including coroutinesLeverage network asynchronous programming by using Boost.Asio and Boost.CobaltAdd proven performance and optimization techniques to your toolboxFind out how to test and debug asynchronous softwareWho this book is forThis book is for developers who have some experience using C++, regardless of their professional field. If you want to improve your C++ skills and learn how to develop high-performance software using the latest modern C++ features, this book is for you.Table of ContentsParallel Programming ParadigmsProcesses, Threads, and ServicesHow to Create and Manage Threads in C++Thread Synchronization with LocksAtomic OperationsPromises and FuturesThe Async FunctionAsynchronous Programming Using CoroutinesAsynchronous Programming Using Boost.AsioCoroutines with Boost.CobaltLogging and Debugging Asynchronous SoftwareSanitizing and Testing Asynchronous SoftwareImproving Asynchronous Software Performance Read more

The Rust programming language is extremely well suited for concurrency, and its ecosystem has many libraries that include lots of concurrent data structures, locks, and more. But implementing those structures correctly can be very difficult. Even in the most well-used libraries, memory ordering bugs are not uncommon.In this practical book, Mara Bos, leader of the Rust library team, helps Rust programmers of all levels gain a clear understanding of low-level concurrency. You'll learn everything about atomics and memory ordering and how they're combined with basic operating system APIs to build common primitives like mutexes and condition variables. Once you're done, you'll have a firm grasp of how Rust's memory model, the processor, and the role of the operating system all fit together.With this guide, you'll learn:How Rust's type system works exceptionally well for programming concurrency correctlyAll about mutexes, condition variables, atomics, and memory orderingWhat happens in practice with atomic operations on Intel and ARM processorsHow locks are implemented with support from the operating systemHow to write correct code that includes concurrency, atomics, and locksHow to build your own locking and synchronization primitives correctly Read more

Already popular among programmers for its memory safety and speed, the Rust programming language is also valuable for asynchrony. This practical book shows you how asynchronous Rust can help you solve problems that require multitasking. You'll learn how to apply async programming to solve problems with an async approach. You will also dive deeper into async runtimes, implementing your own ways in which async runtimes handle incoming tasks.Authors Maxwell Flitton and Caroline Morton also show you how to implement the Tokio software library to help you with incoming traffic, communicate between threads with shared memory and channels, and design a range of complex solutions using actors. You'll also learn to perform unit and end-to-end tests on a Rust async system.With this book, you'll learn:How Rust approaches async programmingHow coroutines relate to async RustReactive programming and how to implement pub sub in async rustHow to solve problems using actorsHow to customize Tokio to gain control over how tasks are processedAsync Rust design patternsHow to build an async TCP server just using the standard libraryHow to unit test async RustBy the end of the book, you'll be able to implement your own async TCP server completely from the standard library with zero external dependencies, and unit test your async code. Read more

Welcometo High Performance .NET: Recipes and Thoughts for .NET 8, 9, and C# 12, 13.In today’s world, where software is expected to run faster, scale efficiently, and handle more complexity than ever before, writing high-performance code is no longer a luxury—it's a necessity.This book is designed to help you harness the full power of .NET and C#, delving into the features and optimizations introduced in the latest versions of the platform. Whether you’re building high-traffic web applications, computationally intensive tasks, or real-time systems, this guide is your toolkit for achieving peak performance.NEThas grown into a powerhouse platform with a broad range of capabilities—from low-level memory management to cutting-edge parallel programming techniques and GPU acceleration. In this book, we’ll explore both the science and the art of performance tuning in .NET. Through practical examples, hands-on recipes, and detailed technical breakdowns, you'll learn how to squeeze every ounce of speed and efficiency out of your code. Read more

A practical guide for C++ and C# programmers to learn Threading Building Blocks and Task Parallel Library. Their higher level of abstraction makes parallel coding simpler and clearer. This book shows how to structure serial algorithms for easy transition to parallel for multicore processors. All code is provided in two github repositories as open-source with examples for Windows and Linux.This book is born from a 5-year column in Dr. Dobb’s Journal and a blog on high-performance parallel algorithms, with over a decade of development. It examines several parallelization patterns, such as divide-and-conquer, parallel_for, and explicit task creation. The focus is on sorting algorithms, as an example for how to parallelize well known algorithms in a scalable way to harness multicore compute power of a processor.What You'll LearnSee working single-core algorithms transformed into high-performance parallel versionsAlgorithms such as merge, sum, histogram, merge sort, radix sort, linear-time in-place sortExplore multiple ways to parallelize, such as “parallel algorithms” and “algorithms in parallel”See how adaptive algorithms improve performance orderDevelop hybrid algorithm combinations to gain performanceImplement linear-time parallel sort hybridsSee how linear-time radix sort can be made usefulHow to create parallel algorithms that scale and “perform no worse”Unique parallel-only issuesEfficient parallel computing or just fastestOrder of parallel sorting algorithms and their constantsHow better sharing of resources increases parallel performanceAn issue with standard C++ adaptive algorithms and how to improve adaptivitySafer arithmeticWho This Book Is ForC++ and C# developers looking to raise performance and efficiency of applications to the next level by utilizing all cores within multicore CPUs of laptops, desktops, and cloud nodes. Undergraduate and graduate computer science and computer engineering classes looking to expose students to parallel programming on processors. Algorithm developers and researchers interested in parallelization techniques and performance optimization. Read more

If you’re one of many developers still uncertain about concurrent and multithreaded development, this practical cookbook will change your mind. With more than 85 code-rich recipes in this updated second edition, author Stephen Cleary demonstrates parallel processing and asynchronous programming techniques using libraries and language features in .NET and C# 8.0.Concurrency is now more common in responsive and scalable application development, but it’s still extremely difficult to code. The detailed solutions in this cookbook show you how modern tools raise the level of abstraction, making concurrency much easier than before. Complete with ready-to-use code and discussions about how and why solutions work, these recipes help you:Get up to speed on concurrency and async and parallel programmingUse async and await for asynchronous operationsEnhance your code with asynchronous streamsExplore parallel programming with .NET’s Task Parallel LibraryCreate dataflow pipelines with .NET’s TPL Dataflow libraryUnderstand the capabilities that System.Reactive builds on top of LINQUtilize threadsafe and immutable collectionsLearn how to conduct unit testing with concurrent codeMake the thread pool work for youEnable clean, cooperative cancellationExamine scenarios for combining concurrent approachesDive into asynchronous-friendly object-oriented programmingRecognize and write adapters for code using older asynchronous styles Read more

"Mastering Haskell: A Comprehensive Guide to Functional Programming" is your gateway to the elegant and powerful world of Haskell programming. This comprehensive guide takes you on a journey from the fundamentals of functional programming to advanced concepts, ensuring a smooth learning curve for beginners and experienced programmers alike.Key Features:Clear, step-by-step explanations of Haskell conceptsHands-on exercises and practical examplesIn-depth coverage of advanced topics like monads and type familiesBest practices for writing clean, efficient, and maintainable codeReal-world applications and case studiesWhy Choose This Book?Structured Learning Path: Carefully organized chapters build upon each other, providing a logical progression through Haskell's features and philosophies.Comprehensive Coverage: From basic syntax to advanced topics like concurrency and lazy evaluation, this book leaves no stone unturned.Practical Focus: Learn how to apply Haskell's unique features to solve real-world problems and build robust applications.Deep Understanding: Gain insights into the mathematical foundations and design principles that make Haskell a powerful tool for complex problem-solving.Future-Ready Skills: Master a language that's at the forefront of functional programming, preparing you for the evolving landscape of software development.Who Should Read This Book?Beginner programmers looking to start with a functional languageExperienced developers wanting to add Haskell to their skill setComputer science students and enthusiastsResearchers and academics interested in rigorous programming paradigmsWhat You'll Learn:Haskell syntax and core conceptsFunctional programming principles and patternsAdvanced type system features and type-level programmingMonads and their practical applicationsConcurrent and parallel programming in HaskellPerformance optimization techniquesTesting and debugging Haskell programsIntegration with other languages and systemsBy the end of this book, you'll have a deep understanding of Haskell and functional programming principles. You'll be equipped to write elegant, efficient, and maintainable code, tackle complex problems with confidence, and contribute to real-world Haskell projects.Whether you're new to programming or a seasoned developer, "Mastering Haskell" will transform the way you think about code. Embrace the beauty of functional programming and unlock new possibilities in your software development journey.Start your Haskell adventure today and join the ranks of developers who are shaping the future of programming with this powerful and expressive language! Read more

If you're looking to take full advantage of multi-core processors with concurrent programming, this practical book provides the knowledge and hands-on experience you need. The Art of Concurrency is one of the few resources to focus on implementing algorithms in the shared-memory model of multi-core processors, rather than just theoretical models or distributed-memory architectures. The book provides detailed explanations and usable samples to help you transform algorithms from serial to parallel code, along with advice and analysis for avoiding mistakes that programmers typically make when first attempting these computations.Written by an Intel engineer with over two decades of parallel and concurrent programming experience, this book will help you:Understand parallelism and concurrencyExplore differences between programming for shared-memory and distributed-memoryLearn guidelines for designing multithreaded applications, including testing and tuningDiscover how to make best use of different threading libraries, including Windows threads, POSIX threads, OpenMP, and Intel Threading Building BlocksExplore how to implement concurrent algorithms that involve sorting, searching, graphs, and other practical computationsThe Art of Concurrency shows you how to keep algorithms scalable to take advantage of new processors with even more cores. For developing parallel code algorithms for concurrent programming, this book is a must. Read more

Unlock the full potential of GPU computing with this comprehensive guide to CUDA programming in C++. Designed for expert programmers seeking to harness the immense power of parallel processing, this book delves deep into advanced concepts and techniques that transform computational performance.Key Features:Master the CUDA Thread HierarchyDive into the intricacies of grids, blocks, and threads. Learn how to effectively map complex computations onto the GPU's architecture, optimizing parallel execution and resource utilization.Advanced Memory Management StrategiesExplore the nuanced roles of global, shared, constant, and texture memory. Discover techniques to minimize memory latency and maximize bandwidth, crucial for high-performance applications.Synchronization Techniques and Atomic OperationsUnderstand the mechanisms of thread synchronization within CUDA. Utilize atomic operations to manage concurrent data access, ensuring data integrity without compromising performance.Optimization of Memory Access PatternsLearn to achieve memory coalescing and reduce bank conflicts. Implement strategies that enhance memory throughput and overall application speed.Harnessing CUDA Streams and Asynchronous ExecutionUtilize CUDA streams to overlap computation and data transfers. Master asynchronous execution models to fully exploit GPU capabilities and accelerate processing.Implementation of Parallel AlgorithmsImplement efficient parallel reduction and scan (prefix sum) algorithms. Apply these foundational techniques to operations like sum, min, max, and complex data structures.Warp-Level Programming and Data ShufflingDelve into warp-level primitives and understand how to use shuffle operations for efficient inter-thread communication within a warp.Leveraging the Thrust LibraryExplore the Thrust library's high-level abstractions for CUDA. Utilize STL-like APIs for streamlined implementation of parallel algorithms and data structures.Template Metaprogramming in CUDAEmploy advanced C++ template metaprogramming techniques. Write flexible and efficient CUDA code that adapts to different data types and computational requirements.Multi-GPU Programming and Peer-to-Peer CommunicationScale your applications across multiple GPUs. Implement data partitioning and leverage peer-to-peer communication for direct memory access between GPUs.Optimization of Register Usage and OccupancyLearn how to balance register usage to optimize occupancy. Fine-tune your kernels for better resource utilization and enhanced performance.Integration with CUDA LibrariesHarness the power of NVIDIA's CUDA libraries like cuBLAS, cuFFT, and cuRAND. Perform efficient linear algebra operations, fast Fourier transforms, and random number generation.Whether you're developing high-performance simulations, complex data analyses, or cutting-edge machine learning models, this book equips you with the skills to:Accelerate computational tasks by orders of magnitude.Optimize applications for maximum efficiency on NVIDIA GPUs.Implement advanced parallel algorithms and data structures.Integrate modern C++ features seamlessly with CUDA programming.Embark on a transformative journey into the realm of GPU computing. Unlock new levels of performance and efficiency in your applications with the advanced techniques and expert guidance provided in this essential resource for CUDA programming in C++. Read more

Using Sidekiq for background jobs is a great way to scale and grow your app. This book will give you a solid, practical foundation for creating resilient, well-tested, self-healing code that uses background jobs. You'll be able to simulate real-world failure modes and learn how to write idempotent code that can be safely run with Sidekiq.One of the best ways to improve your Rails app's performance is to use background jobs with Sidekiq. While Sidekiq is easy to get set up, you need to do more than just move code around to reap the benefits. In this book, you'll get solutions to what sort of code should go into a Sidekiq job and how to manage those jobs.You'll create a Sidekiq configuration that will serve as a solid foundation for your app, including how to be notified when jobs inevitably fail. You'll then tame alerting fatigue by designing idempotent jobs that can be safely retried in the face of the types of transient failures that are common in networked applications, all without alerting you until action is needed. With that foundation, you'll get a conceptual framework for general monitoring and alerting around your Sidekiq installation and the Redis database it uses, as well as practical tips for organizing the code around your Sidekiq jobs. You'll also learn valuable testing strategies for code that uses Sidekiq jobs.In no time at all you'll build a Rails app using Sidekiq that is efficient, manageable, and sustainable.What You Need:You should have some experience with Ruby and Rails. You should have a basic understanding of what a background job is. You'll need to be able to run Docker in order to set up all the software. Read more

Get a fundamental understanding of asynchronous programming and Rust's futures by working through examples that show you how everything really worksKey FeaturesMaster asynchronous Rust through examples focusing on key conceptsBuild a solid understanding of concepts such as coroutines, fibers, futures, and callbacksExplore Rust's futures, craft your own runtime, and excel in handling stacks, ABIs, syscalls, and inline assemblyPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionStep into the world of asynchronous programming with confidence by conquering the challenges of unclear concepts with this hands-on guide. Using functional examples, this book simplifies the trickiest concepts, exploring goroutines, fibers, futures, and callbacks to help you navigate the vast Rust async ecosystem with ease.You’ll start by building a solid foundation in asynchronous programming and explore diverse strategies for modeling program flow. The book then guides you through concepts like epoll, coroutines, green threads, and callbacks using practical examples. The final section focuses on Rust, examining futures, generators, and the reactor-executor pattern. You’ll apply your knowledge to create your own runtime, solidifying expertise in this dynamic domain. Throughout the book, you’ll not only gain proficiency in Rust's async features but also see how Rust models asynchronous program flow.By the end of the book, you'll possess the knowledge and practical skills needed to actively contribute to the Rust async ecosystem.What you will learnExplore the essence of asynchronous program flow and its significanceUnderstand the difference between concurrency and parallelismGain insights into how computers and operating systems handle concurrent tasksUncover the mechanics of async/awaitUnderstand Rust's futures by implementing them yourselfImplement green threads from scratch to thoroughly understand themWho this book is forThis book is for programmers who want to enhance their understanding of asynchronous programming, especially those experienced in VM’ed or interpreted languages like C#, Java, Python, JavaScript, and Go. If you work with C or C++ but have had limited exposure to asynchronous programming, this book serves as a resource to broaden your knowledge in this area.Although the examples are predominantly in Rust, the intricacies of Rust’s futures are covered in detail. So, anyone with a keen interest in learning Rust or with working knowledge of Rust will be able to get the most out of this book.Table of ContentsAn Introduction to Asynchronous ProgrammingEpoll, Kqueue and IOCPEpoll exampleDifferent strategies for modelling asynchronous program flowStackfull Coroutines/Green Threads/Fibers [Example]Callbacks and promises [Example]Futures in Rust Coroutines and async/await Runtimes, Wakers, and the Reactor-Executor Pattern Coroutines, Self-Referential Structs, and PinningCreating Your Own Runtime Read more

Do you know C++ but not AI? Do you dream of writing your own Generative AI engine in C++? From beginner to advanced, this book covers the internals of GPT-style Transformer engines and Large Language Models (LLMs) in C++, with source code examples and research paper citations.Key FeaturesTransformer components in C++Faster and smarter AIOpen source LLMsAdvanced software developmentCutting-edge research optimizationsJust C++ code without all the mathResearch papers literature surveyTable of ContentsPart I: AI Projects in C++1. Introduction to AI in C++2. Transformers & LLMs3. AI Phones4. AI on Your Desktop5. Design Choices & Architectures6. Training, Fine-Tuning & RAG7. Deployment ArchitecturePart II: Basic C++ Optimizations8. Bitwise Operations9. Floating Point Arithmetic10. Arithmetic Optimizations11. Compile-Time Optimizations12. Pointer Arithmetic13. Algorithm Speedups14. Memory OptimizationsPart III: Parallel C++ Optimizations15. Loop Vectorization16. Hardware Acceleration17. AVX Intrinsics18. Parallel Data StructuresPart IV: Transformer Components in C++19. Encoders & Decoders20. Attention21. Activation Functions22. Vector Algorithms23. Tensors24. Normalization25. Softmax26. Decoding Algorithms27. Tokenizer and VocabularyPart V: Optimizing Transformers in C++28. Deslugging AI Engines29. Caching Optimizations30. Vectorization31. Kernel Fusion32. Quantization33. Pruning34. MatMul/GEMM35. Lookup Tables & Precomputation36. AI Memory OptimizationsPart VI: Enterprise AI in C++37. Tuning, Profiling & Benchmarking38. Platform Portability39. Quality40. Reliability41. Self-Testing Code42. DebuggingPart VII: Research on AI Optimization43. Overview of AI Research44. Advanced Quantization45. Knowledge Distillation46. Structured Pruning47. Early Exit and Layer Pruning48. Width Pruning49. Length Pruning50. Adaptive Inference51. Zero-Multiplication Models52. Logarithmic Models53. Arithmetic Optimization Research54. Ensemble Multi-Model Architectures55. Advanced Number Systems56. Neural Architecture SearchAppendix 1: C++ Slug Catalog Read more