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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If Graphics Programming keeps catching your attention, “Data Structures and Algorithms: Parallel Structures, GPU Computing, and Visual Rendering with WebGPU and WGSL” is a title to put on your radar. Its listed scope opens a worthwhile conversation about Computer Science. 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. Bring a pencil, a small example, and the willingness to ask why a relationship works. Moving between symbols and visible behaviour can turn an abstract topic into something you want to investigate further. A promising addition to a reading list with a purpose.

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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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For a mathematical relationship connected to the topic, identify the inputs, units, assumptions, and a simple case you can independently check.

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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