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Multithreading for Visual Effects
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Book Details

Format Hardback or Cased Book
ISBN-10 1482243563
ISBN-13 9781482243567
Publisher Apple Academic Press Inc.
Imprint Apple Academic Press Inc.
Country of Manufacture US
Country of Publication GB
Publication Date Jul 29th, 2014
Print length 256 Pages
Weight 654 grams
Dimensions 26.30 x 17.80 x 2.10 cms
Product Classification: Digital animation
Ksh 13,850.00
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In this book, developers from DreamWorks Animation, Pixar, Side Effects, Intel, and AMD share their successes and failures in the messy real-world application area of production software. They provide practical advice on multithreading techniques and visual effects used in popular visual effects libraries, one of the industry’s leading visual effects packages, and proprietary animation systems. This information is valuable not just to those in the visual effects arena, but also to developers of high performance software looking to increase performance of their code.

Tackle the Challenges of Parallel Programming in the Visual Effects Industry

In Multithreading for Visual Effects, developers from DreamWorks Animation, Pixar, Side Effects, Intel, and AMD share their successes and failures in the messy real-world application area of production software. They provide practical advice on multithreading techniques and visual effects used in popular visual effects libraries (such as Bullet, OpenVDB, and OpenSubdiv), one of the industry’s leading visual effects packages (Houdini), and proprietary animation systems. This information is valuable not just to those in the visual effects arena, but also to developers of high performance software looking to increase performance of their code.

Diverse Solutions to Solve Performance Problems

After an introductory chapter, each subsequent chapter presents a case study that illustrates how the authors used multithreading techniques to achieve better performance. The authors discuss the problems that occurred and explain how they solved them. The case studies encompass solutions for shaving milliseconds, solutions for optimizing longer running tasks, multithreading techniques for modern CPU architectures, and massive parallelism using GPUs. Some of the case studies include open source projects so you can try out these techniques for yourself and see how well they work.


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