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GPU Programming

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May 13, 2024 3 minute read

GPU Programming is a subfield of computer science that deals with the programming and application of graphics processing units (GPUs) in high-performance computing. GPUs are specialized electronic circuits that are designed to accelerate the rendering of computer graphics, but they can also be used for general-purpose computations. GPU Programming is a rapidly growing field, as GPUs are becoming increasingly powerful and versatile. This article will provide an overview of GPU Programming, including its benefits, applications, and how to get started with it.

Benefits of GPU Programming

Path to GPU Programming

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We've curated six courses to help you on your path to GPU Programming. Use these to develop your skills, build background knowledge, and put what you learn to practice.

Sorted from most relevant to least relevant:

Intro to Parallel Programming

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Introduction to Parallel Programming with CUDA

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OpenCL Programming

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Data-Oriented C++ in Scientific Programming

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Pythonによる科学技術計算入門【流体専門コース】Ⅰ

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【Pythonで学ぶ】CUDA プログラミング入門

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Reading list

We've selected five books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in GPU Programming.

GPU Pro 360 Guide to 3D Engine Design

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Comprehensive guide to GPU Programming. It covers a wide range of topics, from the basics of GPU architecture to advanced techniques for optimizing performance. This book is suitable for both beginners and experienced programmers, making it a great resource for anyone who wants to learn about GPU Programming.

GPU Pro 360 Guide to 3D Engine Design

Paperback

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GPU Pro 360 Guide to 3D Engine Design

Kindle Edition

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CUDA Programming

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Comprehensive guide to CUDA Programming. It covers all the basics of CUDA, including how to write kernels, optimize performance, and debug code. This book is suitable for beginners and experienced programmers alike. Shane Cook CUDA expert and his book is one of the best resources available on the topic.

CUDA by Example

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Practical guide to GPU Programming for games. It covers all the basics of GPU Programming, including how to write shaders, optimize performance, and debug code. This book is suitable for beginners and experienced programmers alike.

CUDA by Example: An Introduction to General-Purpose...

Paperback

CUDA by Example: An Introduction to General-Purpose...

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CUDA by Example: An Introduction to General-Purpose...

Kindle Edition

Introduction to Machine Learning with Python

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Practical guide to GPU Programming in Python. It covers all the basics of GPU Programming, including how to write kernels, optimize performance, and debug code. This book is suitable for beginners and experienced programmers alike.

Introduction to Machine Learning with Python: A...

Kindle Edition

OpenCL Programming Guide

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Comprehensive guide to GPU Programming with OpenCL. It covers all the basics of OpenCL, including how to write kernels, optimize performance, and debug code. This book is suitable for beginners and experienced programmers alike.

OpenCL Programming Guide (OpenGL)

Kindle Edition

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