Data-Oriented C++ in Scientific Programming

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Data-Oriented C++ in Scientific Programming

Coursera · Intermediate ·🛠️ AI Tools & Apps ·3mo ago

Key Takeaways

Applies modern C++ programming techniques for efficient data-intensive applications in scientific simulation software, statistical data processing, and computer graphics

Original Description

Learn how to write efficient, maintainable C++ code for data-intensive applications in this hands-on course. Key application areas include scientific simulation software, statistical data processing, and computer graphics. You’ll begin by exploring how modern C++ supports high-efficiency programming and review the principles of a central piece of hardware in data-intensive applications: computer memory. Next, the course shifts to software design. You’ll examine performance shortcomings of traditional object-oriented programming and dive into data-oriented perspective, which improves performance by structuring code around the data itself. You’ll learn how this paradigm overcomes bottlenecks and leads to more scalable, high-performance solutions. Finally, you’ll apply these principles to modern multi-threaded systems. Through hands-on experience you will learn to use C++'s built-in parallel features to target both multi-core CPUs and GPUs.
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