Book Details
ISBN: 9798278959335
Publication Date: December 12, 2024
Categories:
Keywords:
Quick Stats
Reads: 3458
Discussions: 26
Quotes Saved: 6
Difficulty: 4/5
Practicality: 4/5
Depth: 5/5
OpenCL Compute
About This Book
This comprehensive guide to OpenCL and GPU Computing provides readers with both theoretical foundations and practical applications. The author's approach to Programming has been praised for its clarity and depth, making complex concepts accessible to professionals and enthusiasts alike.
With a focus on real-world Parallel Programming, this book stands out from others in the field by emphasizing Heterogeneous Computing through detailed examples and case studies. Whether you're new to GPU Computing or looking to deepen your expertise, this volume offers valuable insights at every level.
"Essential reading for anyone serious about GPU Computing"
—Professor
Based on survey of 444 professionals
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Book Review • January 20, 2026
This roundup of essential reading for Parallel Programming includes praise for the book's groundbreaking work on GPU Computing.
Reader Reviews
Michael Chen
Programming Expert
As someone who's struggled with Parallel Programming, this book was a revelation. The practical exercises for Heterogeneous Computing have already improved my daily routine. I've recommended it to all my colleagues in Parallel Programming.
Sarah Johnson
Game Development Expert
Solved: I spent weeks trying to understand OpenCL until I found this book. The chapter on GPU Computing provided exactly the explanation I needed. Saved me countless hours of frustration!
Emma Williams
Web Development Expert
This book provides a comprehensive examination of OpenCL and GPU Computing and Parallel Programming and Heterogeneous Computing and Compute Kernels and High‑Performance Computing and GPGPU and Cross‑Platform Development and C Programming and C++ Programming. The author's approach to Programming is particularly insightful, offering both theoretical foundations and practical applications. The section on GPU Computing was especially valuable for my research.
James Wilson
Debugging Expert
Solved: I spent weeks trying to understand OpenCL until I found this book. The chapter on GPU Computing provided exactly the explanation I needed. Saved me countless hours of frustration!
Robert Brown
Technology Expert
Solved: I spent weeks trying to understand OpenCL until I found this book. The chapter on GPU Computing provided exactly the explanation I needed. Saved me countless hours of frustration!
Lisa Rodriguez
Analytics Expert
I never thought I'd enjoy reading about OpenCL until I picked up this book. It completely changed my perspective on Programming and how it relates to everyday GPU Computing. The author has a gift for making complex ideas accessible.
Olivia Martinez
Game Design Expert
The methodological rigor applied to Parallel Programming in this work establishes a new benchmark for future studies in GPU Computing. While some may find the statistical treatments dense, they are necessary for the Heterogeneous Computing framework the author develops.
David Kim
JavaScript Expert
Compared to similar titles in GPU Computing, this book excels in its real-world applications of GPU Computing. The case studies are current and relevant to today's challenges in High‑Performance Computing.
Michael Chen
Programming Expert
As someone who's struggled with Parallel Programming, this book was a revelation. The practical exercises for Heterogeneous Computing have already improved my daily routine. I've recommended it to all my colleagues in Parallel Programming.
Robert Brown
Technology Expert
Compared to similar titles in GPU Computing, this book excels in its real-world applications of GPU Computing. The case studies are current and relevant to today's challenges in High‑Performance Computing.
Community Discussions
SolutionEmma Williams
Web Development Expert • 4723 views
For anyone facing issues with Parallel Programming, the troubleshooting guide in chapter 7 saved me hours of frustration.
SolutionLisa Rodriguez
Analytics Expert • 4603 views
For anyone facing issues with Parallel Programming, the troubleshooting guide in chapter 4 saved me hours of frustration.
SolutionMichael Chen
Programming Expert • 860 views
Solved: I had this problem with OpenCL, but the book's explanation on page 187 clarified everything. Spent ages on Google before finding this!
SolutionSarah Johnson
Game Development Expert • 1779 views
After struggling with GPU Computing for weeks, the step-by-step breakdown in section 6.2 was exactly what I needed.
SolutionOlivia Martinez
Game Design Expert • 2328 views
After struggling with GPU Computing for weeks, the step-by-step breakdown in section 5.2 was exactly what I needed.
Lisa Rodriguez
Analytics Expert • 3377 views
Has anyone successfully implemented the OpenCL approach from chapter 3? I'm stuck on the part about GPU Computing.
Sarah Johnson
Game Development Expert • 1106 views
Pro tip: Before diving into chapter 6, make sure you're comfortable with Parallel Programming basics. It makes a huge difference!
Emma Williams
Web Development Expert • 2699 views
Has anyone successfully implemented the OpenCL approach from chapter 3? I'm stuck on the part about GPU Computing.
Robert Brown
Technology Expert • 2265 views
Is the Parallel Programming methodology still current with today's standards in GPU Computing?
Robert Brown
January 18, 2026This worked perfectly for me too! Saved me so much time.
Olivia Martinez
January 15, 2026I had the same question. The key is to focus on C++ Programming first.
Sarah Johnson
January 19, 2026This worked perfectly for me too! Saved me so much time.
Robert Brown
January 15, 2026I had the same question. The key is to focus on Heterogeneous Computing first.
James Wilson
Debugging Expert • 3679 views
Don't skip the exercises in section 4. They seem simple but really cement the Heterogeneous Computing concepts.
James Wilson
Debugging Expert • 346 views
The companion website has additional resources for OpenCL that aren't mentioned in the book. Worth checking out!
David Kim
JavaScript Expert • 1053 views
Pro tip: Before diving into chapter 6, make sure you're comfortable with Parallel Programming basics. It makes a huge difference!
Robert Brown
January 15, 2026This solution should be marked as the accepted answer. It's exactly what the book recommends on page 152.
Olivia Martinez
January 10, 2026I had the same question. The key is to focus on Parallel Programming first.
Olivia Martinez
January 14, 2026I had the same question. The key is to focus on Compute Kernels first.
David Kim
JavaScript Expert • 2043 views
Don't skip the exercises in section 5. They seem simple but really cement the Heterogeneous Computing concepts.
Emma Williams
January 16, 2026Can you share more details about your implementation?
Michael Chen
January 10, 2026For those coming from a GPU Computing background, there's an alternative approach that might work better.
Robert Brown
Technology Expert • 1291 views
The book's perspective on Heterogeneous Computing really challenges conventional wisdom in High‑Performance Computing. What do others think about this approach?
Michael Chen
Programming Expert • 3120 views
Pro tip: Before diving into chapter 9, make sure you're comfortable with Parallel Programming basics. It makes a huge difference!
Olivia Martinez
January 18, 2026I had the same question. The key is to focus on High‑Performance Computing first.
Highlighted Quotes
"Highlighted on page 64: 'The Parallel Programming principle transforms ordinary High‑Performance Computing into exceptional High‑Performance Computing.'"
"One powerful idea: 'Programming requires not just knowledge of OpenCL, but mastery of GPU Computing.' The book shows exactly how to achieve this."
"Highlighted on page 62: 'The Parallel Programming principle transforms ordinary High‑Performance Computing into exceptional High‑Performance Computing.'"
"As the author notes in chapter 8, 'GPU Computing is not just about Parallel Programming, but rather about Heterogeneous Computing.' This distinction makes all the difference."
"Highlighted on page 65: 'The Parallel Programming principle transforms ordinary High‑Performance Computing into exceptional High‑Performance Computing.'"
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