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Data Structures and Algorithms: Parallel Structures, GPU Computing, and Visual Rendering with WebGPU and WGSL — cover

Book cover from the publisher catalogue.

Computer Science

Data Structures and Algorithms: Parallel Structures, GPU Computing, and Visual Rendering with WebGPU and WGSL

By Kenwright

A modern take on classic computing principles, this book explores how data structures and algorithms evolve in the age of parallelism and GPU acceleration.

Pages
746
Publication
5 October 2025
Language
English
ISBN
9798272012067
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There is a strong reading opportunity in the space between WebGPU and Parallel Programming. “Data Structures and Algorithms: Parallel Structures, GPU Computing, and Visual Rendering with WebGPU and WGSL” brings those listed subjects onto the same shelf and gives your next question a place to start. WebGPU connects browser-based graphics and computation with highly visible possibilities. Choose a scene, data display, or small parallel task and use it to organise the concepts you want to explore. Use the topic as material for a clearer explanation. Choose a person who needs the idea, find a concrete example, and make the connection visible. The result can be a better conversation as well as a useful reading session. Worth exploring when you are ready for a fresh reading direction.

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Explore Computer Science, Algorithms, Data Structures with a reading approach that gives the ideas somewhere to go. WebGPU connects browser-based graphics and computation with highly visible possibilities. Choose a scene, data display, or small parallel task and use it to organise the concepts you want to explore.

The listed 746 pages give a sense of extent; page count alone does not establish depth or difficulty.

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Publisher’s synopsis

As computing shifts toward parallel architectures and GPU acceleration, traditional approaches to data structures and algorithms must evolve. This book dives into the challenges and opportunities of modern computing, introducing readers to WebGPU and WGSL as tools for high-performance rendering and computation. Learn how to adapt classic structures like trees, graphs, and queues for parallel execution, and explore how algorithms behave in massively concurrent environments. Ideal for developers, researchers, and students aiming to stay ahead in the computing landscape.

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