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 borrowing How to write flexible, efficient code with traits and generics How to write fast, multithreaded code without data races Rust's key power tools: closures, iterators, and asynchronous programming Collections, strings and text, input and output, macros, unsafe code, and foreign function interfaces This revised, updated edition covers the Rust 2021 Edition. Read more

Programming Massively Parallel Processors: A Hands-on Approach shows both students and professionals alike the basic concepts of parallel programming and GPU architecture. Concise, intuitive, and practical, it is based on years of road-testing in the authors' own parallel computing courses. Various techniques for constructing and optimizing parallel programs are explored in detail, while case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. The new edition includes updated coverage of CUDA, including the newer libraries such as CuDNN. New chapters on frequently used parallel patterns have been added, and case studies have been updated to reflect current industry practices. Parallel Patterns Introduces new chapters on frequently used parallel patterns (stencil, reduction, sorting) and major improvements to previous chapters (convolution, histogram, sparse matrices, graph traversal, deep learning)Ampere Includes a new chapter focused on GPU architecture and draws examples from recent architecture generations, including Ampere Systematic Approach Incorporates major improvements to abstract discussions of problem decomposition strategies and performance considerations, with a new optimization checklist Read more

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Build GPU-accelerated high performing applications with Python 2.7, CUDA 9, and open source libraries such as PyCUDA and scikit-cuda. We recommend the use of Python 2.7 as this version has stable support across all libraries used in this book.Key FeaturesGet to grips with GPU programming tools such as PyCUDA, scikit-cuda, and NsightExplore CUDA libraries such as cuBLAS, cuFFT, and cuSolverApply GPU programming to modern data science applicationsBook DescriptionGPU programming is the technique of offloading intensive tasks running on the CPU for faster computing. Hands-On GPU Programming with Python and CUDA will help you discover ways to develop high performing Python apps combining the power of Python and CUDA.This book will help you hit the ground running-you'll start by learning how to apply Amdahl's law, use a code profiler to identify bottlenecks in your Python code, and set up a GPU programming environment. You'll then see how to query a GPU's features and copy arrays of data to and from its memory. As you make your way through the book, you'll run your code directly on the GPU and write full blown GPU kernels and device functions in CUDA C. You'll even get to grips with profiling GPU code and fully test and debug your code using Nsight IDE. Furthermore, the book covers some well-known NVIDIA libraries such as cuFFT and cuBLAS.With a solid background in place, you'll be able to develop your very own GPU-based deep neural network from scratch, and explore advanced topics such as warp shuffling, dynamic parallelism, and PTX assembly. Finally, you'll touch up on topics and applications like AI, graphics, and blockchain.By the end of this book, you'll be confident in solving problems related to data science and high-performance computing with GPU programming.What you will learnWrite effective and efficient GPU kernels and device functionsWork with libraries such as cuFFT, cuBLAS, and cuSolverDebug and profile your code with Nsight and Visual ProfilerApply GPU programming to data science problemsBuild a GPU-based deep neural network from scratchExplore advanced GPU hardware features such as warp shufflingWho this book is forThis book is for developers and data scientists who want to learn the basics of effective GPU programming to improve performance using Python code. Familiarity with mathematics and physics concepts along with some experience with Python and any C-based programming language will be helpful.Table of ContentsWhy GPU Programming?Setting Up Your GPU Programming EnvironmentGetting Started with PyCUDAKernels, Threads, Blocks, and GridsStreams, Events, Contexts, and ConcurrencyDebugging and Profiling Your CUDA CodeUsing the CUDA Libraries with Scikit-CUDA Draft completeThe CUDA Device Function Libraries and ThrustImplementing a Deep Neural Network Working with Compiled GPU Code Performance Optimization in CUDA Where to Go from Here Read more

Rust in Action is a hands-on guide to systems programming with Rust. Written for inquisitive programmers, it presents real-world use cases that go far beyond syntax and structure.Summary Rust in Action introduces the Rust programming language by exploring numerous systems programming concepts and techniques. You'll be learning Rust by delving into how computers work under the hood. You'll find yourself playing with persistent storage, memory, networking and even tinkering with CPU instructions. The book takes you through using Rust to extend other applications and teaches you tricks to write blindingly fast code. You'll also discover parallel and concurrent programming. Filled to the brim with real-life use cases and scenarios, you'll go beyond the Rust syntax and see what Rust has to offer in real-world use cases. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Rust is the perfect language for systems programming. It delivers the low-level power of C along with rock-solid safety features that let you code fearlessly. Ideal for applications requiring concurrency, Rust programs are compact, readable, and blazingly fast. Best of all, Rust’s famously smart compiler helps you avoid even subtle coding errors. About the book Rust in Action is a hands-on guide to systems programming with Rust. Written for inquisitive programmers, it presents real-world use cases that go far beyond syntax and structure. You’ll explore Rust implementations for file manipulation, networking, and kernel-level programming and discover awesome techniques for parallelism and concurrency. Along the way, you’ll master Rust’s unique borrow checker model for memory management without a garbage collector. What's inside Elementary to advanced Rust programming Practical examples from systems programming Command-line, graphical and networked applications About the reader For intermediate programmers. No previous experience with Rust required. About the author Tim McNamara uses Rust to build data processing pipelines and generative art. He is an expert in natural language processing and data engineering. Table of Contents 1 Introducing Rust PART 1 RUST LANGUAGE DISTINCTIVES 2 Language foundations 3 Compound data types 4 Lifetimes, ownership, and borrowing PART 2 DEMYSTIFYING SYSTEMS PROGRAMMING 5 Data in depth 6 Memory 7 Files and storage 8 Networking 9 Time and timekeeping 10 Processes, threads, and containers 11 Kernel 12 Signals, interrupts, and exceptions 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

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Get ready to unlock the power of your data. With the fourth edition of this comprehensive guide, youâ??ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. Using Hadoop 2 exclusively, author Tom White presents new chapters on YARN and several Hadoop-related projects such as Parquet, Flume, Crunch, and Spark. Youâ??ll learn about recent changes to Hadoop, and explore new case studies on Hadoopâ??s role in healthcare systems and genomics data processing. Learn fundamental components such as MapReduce, HDFS, and YARN Explore MapReduce in depth, including steps for developing applications with it Set up and maintain a Hadoop cluster running HDFS and MapReduce on YARN Learn two data formats: Avro for data serialization and Parquet for nested data Use data ingestion tools such as Flume (for streaming data) and Sqoop (for bulk data transfer) Understand how high-level data processing tools like Pig, Hive, Crunch, and Spark work with Hadoop Learn the HBase distributed database and the ZooKeeper distributed configuration service Read more

"This book should be on every C++ programmer’s desk. It’s clear, concise, and valuable." - Rob Green, Bowling Green State University This bestseller has been updated and revised to cover all the latest changes to C++ 14 and 17! C++ Concurrency in Action, Second Edition teaches you everything you need to write robust and elegant multithreaded applications in C++17. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology You choose C++ when your applications need to run fast. Well-designed concurrency makes them go even faster. C++ 17 delivers strong support for the multithreaded, multiprocessor programming required for fast graphic processing, machine learning, and other performance-sensitive tasks. This exceptional book unpacks the features, patterns, and best practices of production-grade C++ concurrency. About the Book C++ Concurrency in Action, Second Edition is the definitive guide to writing elegant multithreaded applications in C++. Updated for C++ 17, it carefully addresses every aspect of concurrent development, from starting new threads to designing fully functional multithreaded algorithms and data structures. Concurrency master Anthony Williams presents examples and practical tasks in every chapter, including insights that will delight even the most experienced developer. What's inside     Full coverage of new C++ 17 featuresStarting and managing threadsSynchronizing concurrent operationsDesigning concurrent codeDebugging multithreaded applications About the Reader Written for intermediate C and C++ developers. No prior experience with concurrency required. About the Author Anthony Williams has been an active member of the BSI C++ Panel since 2001 and is the developer of the just::thread Pro extensions to the C++ 11 thread library. Table of Contents         Hello, world of concurrency in C++!Managing threadsSharing data between threadsSynchronizing concurrent operationsThe C++ memory model and operations on atomic typesDesigning lock-based concurrent data structuresDesigning lock-free concurrent data structuresDesigning concurrent codeAdvanced thread managementParallel algorithmsTesting and debugging multithreaded applications     Read more

Mastering Concurrency in C# and .NET: Asynchronous, Multithreaded, and Parallel Programming for Scalable ApplicationsPowered by C# 14 and .NET 10Key Features Master asynchronous, multithreaded, and parallel programming with C# 14 and .NET 10Build scalable APIs, responsive UIs, and high-performance background servicesImplement advanced patterns including task orchestration, async pipelines, batching, throttling, and async-safe lockingDetect and resolve concurrency bugs using tools like Visual Studio, dotTrace, and PerfViewDesign real-world architectures using queue-based background processing and hosted servicesBook Description Mastering Concurrency in C# and .NET is the ultimate guide to building responsive, scalable, and production-ready applications using the latest concurrency features of C# 14 and .NET 10. Whether you're developing APIs, desktop applications, or distributed systems, this hands-on book will show you how to harness the full power of modern asynchronous and multithreaded programming in .NET. From the evolution of threading in .NET to writing async-first services using channels, pipelines, and background workers, this book gives you both the deep understanding and practical implementations you need.You’ll learn how to build applications that perform reliably under load, respond instantly to users, and make full use of hardware and system resources. Avoiding fluff, every chapter focuses on what matters: real-world code, proven best practices, and patterns that scale. This is the book that turns your understanding of concurrency into production-grade expertise.What You Will Learn Grasp the key differences between concurrency, parallelism, and asynchrony in .NETUse Task, ValueTask, async/await, and ConfigureAwait correctly and efficientlyCoordinate tasks and resource access with SemaphoreSlim, Channel, and BackgroundServiceBuild resilient systems using batching, throttling, and message pipelinesAvoid common pitfalls like deadlocks and race conditions with proven debugging techniquesProfile and analyze concurrent code using dotTrace, Visual Studio Diagnostics, and PerfViewArchitect microservices with async background processing and clean separation of concernsWho This Book Is For This book is for .NET developers, backend engineers, and system architects who want to master modern concurrency with clarity and confidence. Whether you're optimizing APIs, implementing background services, or scaling distributed systems, this guide provides the tools, techniques, and depth you need to succeed with C# 14 and .NET 10. Its ideal for intermediate developers moving beyond basic async/await, and experienced professionals seeking to sharpen their multithreading and performance skills in real-world systems.Table of Contents Chapter 1: The Fundamentals of Concurrency in C# and .NETChapter 2: Task-Based Asynchronous Programming with async/awaitChapter 3: Parallel Programming with Parallel.For and PLINQChapter 4: Threading and the Thread PoolChapter 5: Synchronization and Thread SafetyChapter 6: Channels, Queues, and Producer-Consumer PatternsChapter 7: Asynchronous Streams and Data PipelinesChapter 8: Concurrency in UI Applications (WinForms, WPF, MAUI)Chapter 9: Testing, Debugging, and Profiling Concurrent CodeChapter 10: Best Practices, Patterns, and Real-World ArchitecturesWith this guide, concurrency becomes your advantage not a challenge. You’ll build systems that scale beautifully, perform under pressure, and fully leverage the power of C# 14 and .NET 10. Read more

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The Art of Multiprocessor Programming promises to be the first comprehensive presentation of the principles and tools available for programming multiprocessor machines.As the computer industry changes from single-processor to multiprocessor architectures, this revolution requires a fundamental change in how programs are written. To leverage the performance and power of multiprocessor programming, also known as multicore programming, programmers need to learn the new principles, algorithms, and tools.The book will be of immediate use to programmers working with the new architectures. For example, the next generation of computer game consoles will all be multiprocessor-based, and the game industry is currently struggling to understand how to address the programming challenges presented by these machines. This change in the industry is so fundamental that it is certain to require a significant response by universities, and courses on multicore programming will become a staple of computer science curriculums.This book includes fully-developed Java examples detailing data structures, synchronization techniques, transactional memory, and more.Students in multiprocessor and multicore programming courses and engineers working with multiprocessor and multicore systems will find this book quite useful. The book on multicore programming, the new paradigm of computer scienceWritten by the world's most revered experts in multiprocessor programming and performanceIncludes examples, models, exercises, PowerPoint slides, and sample Java programs Read more

“This book is required reading for anyone working with accelerator-based computing systems.”–From the Foreword by Jack Dongarra, University of Tennessee and Oak Ridge National Laboratory CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required–just the ability to program in a modestly extended version of C.CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance.Major topics covered include Parallel programming Thread cooperation Constant memory and events Texture memory Graphics interoperability Atomics Streams CUDA C on multiple GPUs Advanced atomics Additional CUDA resourcesAll the CUDA software tools you’ll need are freely available for download from NVIDIA.http://developer.nvidia.com/object/cuda-by-example.html Read more

Windows® 64-bit Assembly Language Programming Quick Start is a complete tutorial using the free Community Edition of Microsoft® Visual Studio 17 to introduce the novice to the Intel® X86-64 architecture and the Windows X64 Calling Convention.With Microsoft® Visual Studio 17, assembly language programs can be built using either its Integrated Development Environment (IDE) or using its ML64 assembler directly in a traditional command line approach. Both techniques are presented in this book, and each has its own merits for gaining a deeper understanding of computer software and hardware. The assistance provided by Visual Studio’s interactive debugger is immense not only for developing real programs but also learning how the CPU instructions work.Programmers learn by example and develop their skills by examining and modifying working programs. Every sample program is complete, but leaves room for enhancements and experimentation encouraged by the questions at the end of each chapter. All are available for download through GitHub.The sample programs, ranging from five to over one hundred lines of code, are extensively documented in both flowcharts and comments. Over seventy illustrations are included to explain programming techniques as well as X86, SSE, and AVX instructions. CPU instructions are introduced as needed to achieve programming goals as the projects in each chapter progress to the next.This is not a book that has been modified or migrates from a 32-bit or 16-bit perspective, but starts right in with 64-bit programming and only refers to past approaches when necessary to explain seemingly unnatural conventions and names.Topics like binary and hexadecimal are introduced through programming examples as well as appearing in appendices.The examples in this book have been “classroom tested” with students having very little, if any, previous programming experience. The information is complete, allowing it to be used as an independent study.Learning computer hardware and software architectures through hands-on assembly language programming experience helps develop well-rounded programmers and computer engineers. Read more

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! Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. 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 resourcesPurchase 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 intends to guide you through optimizing the performance of your C++ apps by allowing 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 C++ language and some of its modern concepts to you in brief. Once you are familiar with the fundamentals, it enables you to measure and identify bottlenecks in a C++ codebase and how to eradicate them using modern C++ constructs and techniques. In this process, you will gradually improve your style of writing code. You will further dive deep to explore 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 experience 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 developed the ability to use every tool as per its need to boost the efficiency of your C++ project.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. Read more

"Mastering GameMaker: A Journey from Novice to Expert" is the definitive guide for anyone aspiring to master the art of game development using the renowned GameMaker Studio. Whether you're an absolute beginner or an intermediate user looking to refine your skills, this book offers a comprehensive and engaging path to becoming an expert in one of the most user-friendly game development platforms.The journey begins with an introduction to the fundamentals of game design and programming. You'll learn about the unique features of GameMaker's integrated development environment (IDE) and how to navigate its user-friendly interface. The early chapters are crafted to ease you into the world of game development, with practical exercises and examples to help you get comfortable with GameMaker's scripting language, GML (GameMaker Language).As you progress, the book delves deeper into advanced topics. You'll explore complex game mechanics, animations, sound integration, and the nuances of creating a visually appealing and engaging game environment. The chapters are interspersed with case studies and real-world examples, offering insights into successful game projects developed with GameMaker."Mastering GameMaker" doesn't just teach you how to code; it empowers you to think like a game designer. The book covers essential game development principles, including level design, player engagement, and balancing gameplay. You'll learn how to bring your creative visions to life and understand what makes a game enjoyable and memorable.The latter sections of the book are dedicated to professional game development practices. Topics such as debugging, optimization, and cross-platform development are covered in detail, providing you with the knowledge to build games that can be published across various platforms, including PC, mobile, and consoles.In addition to technical skills, the book emphasizes the importance of creativity and innovation in game design. It encourages experimentation and offers tips on how to keep your ideas fresh and exciting. By the end of this journey, you'll not only have mastered GameMaker Studio but also gained a holistic understanding of game development as a craft and an art form."Mastering GameMaker: A Journey from Novice to Expert" is more than just a book; it's a mentor that guides you through the exhilarating world of game creation. It's an essential resource for anyone passionate about making their mark in the world of indie game development. Read more

Discover the cutting-edge techniques that will elevate your CUDA C++ programming skills to new heights. This comprehensive guide is an indispensable resource for expert programmers seeking to optimize their applications for maximum performance on NVIDIA GPUs.Delve deep into advanced concepts such as:In-depth memory optimization strategies: Master the art of coalesced memory accesses and learn how to avoid bank conflicts to fully exploit the memory bandwidth of modern GPUs.Advanced kernel optimization techniques: Explore methods to enhance computational efficiency, including loop unrolling, warp shuffle operations, and minimizing thread divergence.Stream and asynchronous programming with CUDA: Learn to overlap data transfer and computation using CUDA streams, enabling you to maximize resource utilization and reduce execution time.Utilizing CUDA libraries and APIs for enhanced functionality: Integrate powerful libraries like cuBLAS, cuFFT, cuRAND, and cuDNN into your applications to accelerate complex operations with ease.Dynamic parallelism and recursive algorithms: Implement recursive algorithms directly on the GPU using dynamic parallelism, allowing for efficient processing of hierarchical data structures.Utilizing unified memory in CUDA applications: Simplify memory management and handle datasets larger than GPU memory by leveraging unified memory, enabling seamless data access across CPU and GPU.Multi-GPU programming and scalability considerations: Scale your applications across multiple GPUs, focusing on data distribution, communication optimization, and load balancing to achieve unparalleled performance.Specific highlights include:Optimized Matrix Multiplication with Coalesced Memory Accesses: Enhance matrix multiplication performance by reorganizing data structures to ensure memory accesses are fully coalesced.Implementing Quicksort with Dynamic Parallelism: Design and implement a GPU-accelerated quicksort algorithm that efficiently handles recursive partitioning using dynamic parallelism.Accelerating Neural Networks with cuDNN: Integrate the cuDNN library to develop custom neural network layers, achieving significant speedups in deep learning applications.Scaling FFT Computations over Multiple GPUs: Distribute FFT computations across multiple GPUs, optimizing data partitioning and communication to handle large-scale signal processing tasks.Unified Memory for Complex Data Structures: Simplify the handling of complex and irregular data structures in applications like molecular modeling by utilizing unified memory for seamless data access.Each chapter delves into practical code examples to solidify your understanding and facilitate implementation in your own projects.Elevate your CUDA C++ applications to achieve maximum performance and unlock the full potential of GPU computing with this essential guide. Read more

Advanced CUDA Programming: High-Performance Computing with GPUs is the ultimate guide to unlocking the full power of modern GPU computing. Whether you're developing AI models, optimizing scientific simulations, or pushing real-time applications to their limits, this book delivers the advanced techniques and expert insights you need to achieve peak CUDA performance.GPU programming is no longer optional—it's a necessity in today's world of deep learning, AI acceleration, and high-performance computing. But simply writing CUDA kernels isn’t enough. To truly optimize GPU applications, you need a deep understanding of GPU architecture, memory hierarchies, execution models, and performance tuning strategies. This book takes you beyond the fundamentals and into the world of advanced CUDA programming, where efficiency, scalability, and raw computational power define success.What You’ll Learn:Deep GPU Architecture Insights – Explore the Ampere and Hopper architectures, including streaming multiprocessors, warp scheduling, and memory controller design.Memory Optimization Techniques – Implement coalesced memory access, shared memory tuning, cache optimizations, and unified memory strategies for peak performance.Asynchronous Execution & CUDA Streams – Master multi-stream processing, event-based synchronization, and pinned memory usage to maximize parallelism.High-Performance Kernel Development – Learn thread block optimization, warp-level programming, and dynamic parallelism for efficient kernel execution.AI & Deep Learning Acceleration – Optimize GEMM, convolution operations, mixed precision training, and inference using tensor cores.Multi-GPU & Distributed Computing – Scale workloads across GPUs with P2P communication, NVLink, workload distribution, and MPI integration.Real-Time Processing & Low-Latency Optimization – Develop real-time applications with deterministic execution, deadline scheduling, and pipeline optimizations.Debugging & Profiling Mastery – Use Nsight Compute, CUDA-GDB, memory checking tools, and roofline analysis to fine-tune CUDA applications.Why This Book?This isn’t just another CUDA guide—it’s a masterclass in performance optimization. Packed with real-world case studies, hands-on techniques, and cutting-edge strategies, it delivers everything you need to develop fast, scalable, and production-ready GPU applications.If you're ready to take your CUDA skills to the next level and maximize GPU performance like never before, this book is your roadmap. Don't leave performance on the table—start optimizing today. Read more

Structured Parallel Programming offers the simplest way for developers to learn patterns for high-performance parallel programming. Written by parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders, this book explains how to design and implement maintainable and efficient parallel algorithms using a composable, structured, scalable, and machine-independent approach to parallel computing. It presents both theory and practice, and provides detailed concrete examples using multiple programming models.The examples in this book are presented using two of the most popular and cutting edge programming models for parallel programming: Threading Building Blocks, and Cilk Plus. These architecture-independent models enable easy integration into existing applications, preserve investments in existing code, and speed the development of parallel applications. Examples from realistic contexts illustrate patterns and themes in parallel algorithm design that are widely applicable regardless of implementation technology.Software developers, computer programmers, and software architects will find this book extremely helpful.The patterns-based approach offers structure and insight that developers can apply to a variety of parallel programming modelsDevelops a composable, structured, scalable, and machine-independent approach to parallel computingIncludes detailed examples in both Cilk Plus and the latest Threading Building Blocks, which support a wide variety of computers Read more