Data-Oriented C++ in Scientific Programming
By External Provider
About this course
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.
What you will learn
- Software architecture using an object-oriented and a data-oriented approach
- Efficient programming using language-specific features in C++
- GPU and multi-core CPU software development in C++