Programming Massively Parallel Processors: A Hands-on Approach
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Programming Massively Parallel Processors: A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach shows both students and professionals alike the basic concepts of parallel programming and GPU architecture.
Programming Massively Parallel Processors: A Hands-on Approach
товар №: 54878760

Programming Massively Parallel Processors: A Hands-on Approach

86% of respondents would recommend this to a friend

товар №: 54878760

KZT 45367

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Programming Massively Parallel Processors: A Hands-on Approach shows both students and professionals alike the basic concepts of parallel programming and GPU architecture.
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What Stands Out

Hands-On Learning
This edition emphasizes practical experience, enabling readers to implement real-world applications and gain hands-on skills in programming massively parallel processors effectively.
Updated Content
Incorporating the latest developments in parallel processing technologies, this edition ensures readers stay current with industry standards and practices, providing a competitive edge in the software development field.
Comprehensive Coverage
Offers extensive coverage of programming techniques and algorithms tailored for parallel processing, equipping readers with the knowledge to tackle complex computing challenges and optimize performance.

Информация о продукте

Shop for Programming Massively Parallel Processors: A Hands-on Approach 4th Edition at Ubuy Kazakhstan. Get the best deals on programming books and enhance your parallel processing skills.
Publisher Morgan Kaufmann
Publication date August 18, 2022
Edition 4th
Language English
Print length 580 pages
ISBN-10 0323912311
ISBN-13 978-0323912310
Item Weight 1.95 pounds (880 grams)
Dimensions 7.25 x 0.75 x 9 inches (18.4 x 1.9 x 22.9 cm)

Who Should Buy?

Suitable For
  • Students in Academia

    Ideal for students studying parallel computing, offering hands-on exercises with CUDA programming for practical learning.

  • Professional Developers

    Helpful for experienced developers looking to enhance skills in parallel programming for high-performance applications.

  • Researchers in HPC

    Useful for researchers focusing on high-performance computing, providing insights into programming with massively parallel processors.

Not Suitable For
  • Beginners in Programming

    Not suitable for beginners without prior programming knowledge, as the content is advanced and assumes familiarity.

ОПИСАНИЕ ТОВАРА

Programming Massively Parallel Processors: A Hands-on Approach

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Microprocessor Design Editorial Review

Programming Massively Parallel Processors: A Hands-on Approach is an essential read for anyone looking to master CUDA programming. The book is published by Morgan Kaufmann, and its fourth edition provides 580 pages rich in content, guiding readers through the basics of CUDA and offering case studies to solidify understanding. Readers have praised the clear explanations, especially in the foundational chapters, making complex concepts more accessible. While it comprehensively covers programming abstractions and hardware differences, some users noted the absence of detailed coverage on CUDA C++, tensor cores, and empirical performance analysis. Despite these minor gaps, it's considered a valuable resource for both teaching and practical application.

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Плюсы

  • Clear explanations help grasp complex CUDA concepts
  • Practical case studies for real-world kernel optimization
  • Structurally well-organized for teaching purposes
  • Deep dives into parallel programming techniques
  • Excellent foundational resource for beginners

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KZT 45367

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Особенности и преимущества

  • The book explains the basic concepts of parallel programming and GPU architecture in a concise, intuitive, and practical manner.
  • It explores various techniques for constructing and optimizing parallel programs with case studies.
  • New chapters on frequently used parallel patterns have been added and case studies updated to reflect current industry practices.
  • It includes updated coverage of CUDA, including newer libraries such as CuDNN.
  • A new chapter on GPU architecture draws examples from recent architecture generations, including Ampere.
  • It incorporates major improvements to abstract discussions of problem decomposition strategies and performance considerations with a new optimization checklist.

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