GPU Parallel Computing Second Edition: From Basics to Breakthroughs in GPU Programming (GPU Expert Engineering: Mastering Design, Programming, and Optimization)

Second Edition updated for 2026. This book is a complete rewrite with entirely new code samples while covering the same core topics as the original edition.All code and infographics from the book are available at the GitHub repository BurstBooksPublishing.GPU Parallel Computing: From Basics to Breakthroughs — A Technical Guide to GPU ProgrammingIf you want to understand how modern GPUs work and how to use them effectively for high-performance workloads, this book provides the technical foundation required.This book assumes no prior exposure to GPU internals; however, a working knowledge of electronics and general computer architecture is recommended.It is written for students, engineers, researchers, and data scientists who are new to GPU architecture and parallel programming and want a rigorous introduction before progressing into optimization and large-scale GPU systems.If you are already an experienced CUDA performance engineer or low-level GPU architect seeking a specialized microarchitectural reference manual, this book is not positioned for that purpose.What You Will LearnGPU Architecture FundamentalsStreaming multiprocessors and SIMT executionWarp scheduling and instruction flowGPU memory hierarchy and bandwidth considerationsGPU Programming ModelsCUDA programming principlesOpenCL fundamentalsKernel structure and execution behaviorPerformance OptimizationMemory access patterns and coalescingWarp divergence and latency hidingOccupancy principles and kernel configurationReal-World ApplicationsScientific simulationsMachine learning workloadsGraphics and visualization pipelinesAdvanced TopicsMulti-GPU communicationTensor cores and mixed precisionProfiling, debugging, and performance analysisThe early chapters establish architectural clarity and programming fundamentals.Later chapters address optimization strategies, scalability, and applied GPU workloads.Who This Book Is ForStudents entering GPU computingEngineers transitioning into parallel architectureResearchers and data scientists adopting GPU accelerationThis is a technical book. It builds understanding from architectural principles upward and focuses on performance-oriented reasoning rather than superficial overview.Why This BookMany GPU resources either assume too much prior knowledge or remain overly abstract.This book emphasizes structured technical understanding:How GPUs execute threadsWhy performance bottlenecks occurHow architectural constraints shape resultsHow programming decisions map to hardware behaviorClear explanations.Practical code examples.Architectural context. Read more