Practical parallel computing (58 Ergebnisse)

Hardcover. Zustand: Good. Pages slightly tannedCovers scuffed with slight moisture marks on inside of cover. Text is clean and tight. Good Reading Copy. NOT A FORMER LIBRARY BOOK.

Zustand: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

Softcover. Zustand: Bon. Ancien livre de bibliothèque. Traces de pliures sur la couverture. Légères traces d'usure sur la couverture. Salissures sur la tranche. Edition 1994. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Traces of creases on the cover. Slight signs of wear on the cover. Stains on the edge. Edition 1994. Ammareal gives back up to 15% of this item's net price to charity organizations. …

Zustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

pictorial hard cover. Zustand: Very Good. No Jacket. Computer engineering series. Includes bibliographical references and index. 252 pages VG. Light shelf wear to covers, overall very good condition.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: Used. pp. 424.

Zustand: Used. pp. 424.

Hardcover. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Zustand: Used. pp. 424.

Zustand: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: New. pp. x + 189 Index.

Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Zustand: New. pp. x + 189 Illus.

Taschenbuch. Zustand: Neu. Neuware - Stop Treating the GPU Like a Faster CPU. Learn to Engineer It as a Complete Computing System.Modern GPU development is no longer just about writing a CUDA kernel and hoping it runs faster. Real performance depends on the entire path from application code to driver, memory system, scheduler, hardware, and production infrastructure.GPU Operating Systems and Parallel Computing gives you a practical, systems-level framework for understanding that entire stack.Starting with the GPU operating environment, this guide explains how host operating systems, drivers, runtimes, contexts, queues, memory mappings, firmware, and hardware schedulers work together. From there, it moves into GPU architecture, parallel decomposition, CUDA programming, memory optimization, asynchronous execution, profiling, debugging, multi-GPU computing, and production deployment.Inside, you'll learn how to: - Understand the GPU software and hardware stack-and diagnose problems at the correct layer- Think in terms of warps, blocks, grids, streaming multiprocessors, memory hierarchies, and resource limits- Design parallel algorithms around independence, dependencies, locality, load balance, and scaling- Build and troubleshoot a CUDA development environment- Write correct CUDA kernels and reason about execution, synchronization, and launch configuration- Optimize memory access, data reuse, transfers, and shared-memory usage- Use streams, events, CUDA Graphs, and concurrency to build efficient pipelines- Profile workloads systematically instead of relying on optimization folklore- Debug memory errors, race conditions, synchronization failures, and numerical problems- Design multi-GPU workloads using topology awareness, collectives, MPS, and MIG- Build reliable GPU applications with observability, testing, reproducibility, security, and deployment practices- Evaluate CUDA, HIP, SYCL, and abstraction layers when portability mattersThe book is designed for developers and engineers working in GPU programming, HPC, machine learning, scientific computing, simulation, rendering, backend infrastructure, and high-performance systems. It combines conceptual explanations with diagrams, tables, code examples, exercises, and practical engineering decision processes.Most importantly, it teaches a repeatable approach to GPU performance: establish correctness, measure the complete workload, identify the real bottleneck, make a targeted change, and validate the result.Whether you're learning CUDA, optimizing an existing GPU workload, building a multi-GPU service, or designing production accelerator infrastructure, this book helps you connect parallel programming concepts to the physical realities of modern GPU systems.Build faster GPU software-but more importantly, learn why it is fast, when it will fail, and how to make it dependable.…

Taschenbuch. Zustand: Neu. Neuware - GPU's have become an important part of modern computing, enabling applications to process large amounts of data through massive parallelism. CUDA provides developers with a powerful programming model for taking advantage of NVIDIA GPUs, but getting started can be challenging when concepts such as kernels, threads, blocks, grids, memory spaces, and synchronization are introduced all at once.GPU Programming with CUDA For Beginners provides a practical introduction to CUDA programming for readers who want to understand how GPU computing works and learn how to build CUDA applications from the ground up.Starting with the fundamentals of GPU architecture and parallel computing, the book progressively introduces the CUDA programming model, kernel execution, threads, thread blocks, grids, memory management, data transfer, synchronization, and common parallel programming patterns. Practical examples help connect these concepts to the way CUDA programs actually execute on a GPU.You will explore how to: - Understand the fundamentals of GPU computing and parallel execution- Set up a CUDA development environment- Write and launch CUDA kernels- Work with threads, blocks, grids, and execution hierarchies- Manage data between the CPU and GPU- Understand CUDA's different memory spaces- Use synchronization and coordinate parallel work- Design practical parallel algorithms- Identify common CUDA programming mistakes- Structure CUDA applications more effectively- Build a solid foundation for further CUDA development and optimizationThe goal is not simply to memorize CUDA functions. Instead, you will develop a practical mental model of how CUDA programs execute and how GPU-oriented programming differs from conventional CPU programming.Whether you are a programmer new to GPU computing, a software developer expanding into parallel programming, or a technical professional looking to understand CUDA, this book provides a structured starting point for building useful GPU programming skills.Build the fundamentals first. Then use them to write better GPU programs.…

Taschenbuch. Zustand: Neu. Neuware.

Zustand: New. pp. x + 189.

Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Taschenbuch. Zustand: Neu. Neuware - This book is a comprehensive guide to engineering highly optimized, distributed C++ applications. It teaches you how to construct software that scales seamlessly from a local workstation to an enterprise supercomputing cluster without wasting a single CPU cycle.I know exactly what it feels like to watch a carefully written application collapse under its own weight. You optimize your mathematics on one machine, only to watch the software freeze or crash the moment you try to scale it up. The hard truth is that the standard rules of software development fail at massive scale. Standard file operations throttle your storage drives, and synchronous network messages force your CPUs to sit entirely idle. What happens when your dataset grows so large that a single server simply cannot process it You must change your entire execution architecture. I wrote this guide to show you exactly how to bypass the operating system, manipulate physical RAM across networks, and coordinate thousands of nodes without a single collision.What's Inside: The Architecture of ScaleThis guide is packed with rigorous, highly practical techniques to transform how you write software: - Custom Memory Mapping: Transmit complex C++ structures instantly using zero-copy communication.- Asynchronous Execution: Master Remote Memory Access to seamlessly alter remote RAM without interrupting active calculations.- Parallel Storage Pipelines: Coordinate collective I/O to write massive datasets at absolute hardware speed.- Hybrid Processing: Unify MPI and OpenMP to completely dominate modern multi-core servers.- Dynamic Load Balancing: Eliminate idle time by constructing highly efficient master-worker task queues.Who It's Meant For: Systems EngineersThis guide is written for C++ developers and software architects who refuse to accept hardware limitations. If you want to elevate your engineering skills to command massive computing clusters, this is your direct roadmap.Stop writing software that is permanently trapped inside a single computer. Your hardware is capable of infinite parallel execution, and it is time you unlock that potential. Grab your copy now, rewrite your architecture, and start engineering the scalable systems of tomorrow.…

Zustand: New. Print on Demand.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Zustand: Brand New. 420 pages. 9.25x7.75x1.00 inches. In Stock.

Hardcover. Zustand: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: New.

Hardcover. Zustand: new. Hardcover. These ten papers represent a range of applications for the practical use of parallel computing. They address large scale high performance applications, data transfer and storage cost minimisation, two-stroke engine applications, large air pollution models, parallel global aircraft configuration design, parallel execution time analysis, parallel randomised heuristics, the analysis of complex waveguide circuits, reading database copy, and business process re-engineering. These ten papers represent a range of applications for the practical use of parallel computing. They address large scale high performance applications, data transfer and storage cost minimisation, two-stroke engine applications, large air pollution models, parallel global aircraft configuration design, parallel execution time analysis, parallel randomised heuristics, the analysis of complex waveguide circuits, reading database copy, and business process re-engineering. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …