C++17 Parallel Algorithms: Concurrency in the Standard Template Library

Modern software demands high performance, yet utilizing multi-core processors efficiently remains a major challenge for many developers. This course introduces you to the modern concurrency features introduced in C++17, enabling you to accelerate your applications with minimal code changes. You will transition from writing slow, sequential loops to leveraging the full power of your hardware using standard, portable language features. In this course, you will build a solid foundation in modern C++ concurrency, starting with essential concepts of parallel execution and thread safety. You will learn to use execution policies to run standard algorithms concurrently, safely manage shared state, and implement modern best practices like type hints and standard smart pointers to write clean, robust code. What you'll learn: - Understand the foundational concepts of concurrency, parallelism, and vectorization in modern C++ - Configure standard algorithms using execution policies such as seq, par, and par_unseq - Apply parallel versions of common algorithms like sorting, searching, and transforming data - Manage shared state safely to prevent data races and synchronization bottlenecks - Practice writing clean, modern C++ code using smart pointers and modern type safety practices - Analyze performance trade-offs to determine when parallel execution is appropriate This written course guides you systematically from core theoretical principles to practical, modern implementation techniques. You will start with basic definitions and thread safety fundamentals before exploring advanced execution policies and performance tuning. This course is designed for intermediate C++ developers who want to learn modern parallel programming, as well as ambitious beginners with a basic grasp of C++ syntax. No prior experience with multi-threaded programming is required. Start reading today to unlock the full processing power of modern hardware with C++17 parallel algorithms.