Book Image

C++ High Performance - Second Edition

By : Björn Andrist, Viktor Sehr
5 (2)
Book Image

C++ High Performance - Second Edition

5 (2)
By: Björn Andrist, Viktor Sehr

Overview of this book

C++ High Performance, Second Edition guides you through optimizing the performance of your C++ apps. This allows them to run faster and consume fewer resources on the device they're running on without compromising the readability of your codebase. The book begins by introducing the C++ language and some of its modern concepts in brief. Once you are familiar with the fundamentals, you will be ready to measure, identify, and eradicate bottlenecks in your C++ codebase. By following this process, you will gradually improve your style of writing code. The book then explores data structure optimization, memory management, and how it can be used efficiently concerning CPU caches. After laying the foundation, the book trains you to leverage algorithms, ranges, and containers from the standard library to achieve faster execution, write readable code, and use customized iterators. It provides hands-on examples of C++ metaprogramming, coroutines, reflection to reduce boilerplate code, proxy objects to perform optimizations under the hood, concurrent programming, and lock-free data structures. The book concludes with an overview of parallel algorithms. By the end of this book, you will have the ability to use every tool as needed to boost the efficiency of your C++ projects.
Table of Contents (17 chapters)
15
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16
Index

Executing algorithms on the GPU

Graphics processing units (GPUs) were originally designed and used for processing points and pixels for computer graphics rendering. Briefly, what the GPUs did was retrieve buffers of pixel data or vertex data, perform a simple operation on each buffer individually, and store the result in a new buffer (to eventually be displayed).

Here are some examples of simple, independent operations that could be executed on the GPU at an early stage:

  • Transform a point from world coordinates to screen coordinates
  • Perform a lighting calculation at a specific point (by lighting calculation, I am referring to calculating the color of a specific pixel in an image)

As these operations could be performed in parallel, the GPUs were designed for executing small operations in parallel. Later on, these graphics operations became programmable, although the programs were written in terms of computer graphics (that is, the memory reads were done...