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C++ High Performance

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Getting Started

About This Course Course Coverage and Prerequisite Google Test and Google Benchmark Libraries

A Brief Introduction to C++

Introduction Why C++?Important Features of C++C++ Compared With Other Languages Non-performance-Related C++ Language Features Non-performance-Related C++ Language Features, Continued Summary: A Brief Introduction to C++Quiz: Introduction to C++

Essential C++ Techniques

Introduction Automatic Type Deduction with the auto Keyword Using auto for Variables Const Propagation for Pointers Move Semantics Explained Resource Acquisition and the Rule of Five Named Variables and rvalues Default Move Semantics and the Rule of Zero Applying the && Modifier to Class Member Functions Pass by Value When Applicable Quiz: Essential Techniques I Designing Interfaces with Error Handling Class Invariants Error Handling Recoverable Runtime Errors Function Objects and Lambda Expressions Initializing Variables in Capture Mutating Lambda Member Variables Assigning C Function Pointers to Lambdas Implementing a Simple Button Class with std::function Generic Lambdas Summary: Essential C++ Techniques Quiz: Essential Techniques II

Analyzing and Measuring Performance

Asymptotic Complexity and Big O Notation

Time Complexity of Insertion Sort

Amortized Time Complexity

What to Measure and How?

Performance Properties

Performance Counters

Knowing Your Code and Hot Spots

Microbenchmarking

A Microbenchmark Example

Summary: Analyzing and Measuring Performance

Quiz: Analyzing and Measuring Performance

Data Structures

Introduction The Properties of Computer Memory The Standard Library Containers Deque, List, forward_list, and basic_string Associative Containers Hash and Equals Container Adaptors Using Views Some Performance Considerations Parallel Arrays Shrinking the Data to Iterate Through by Using Parallel Arrays Summary: Data Structures Quiz: Data Structures

Algorithms

Introduction Introducing the Standard Library Algorithms Solving Everyday Problems More Everyday Problems Iterators and Ranges Iterator Categories Features of the Standard Algorithms Advantages of Using Algorithms in C++Writing and Using Generic Algorithms Best Practices Use of Standard Algorithms Over Raw for-loops Summary: Algorithms Quiz: Algorithms

Ranges and Views

Introduction The Motivation for the Ranges Library Understanding Views from the Ranges Library Ranges Views: Lazy, Non-Mutating Iterations with Materialization Views in the Standard Library Summary: Ranges and Views Quiz: Ranges and Views

Memory Management

Introduction Computer Memory Process Memory Objects in Memory Memory Alignment Padding Memory Ownership Pointers Small Object Optimization Custom Memory Management Custom Memory Allocator Using Polymorphic Memory Allocators Summary: Memory Management Quiz: Memory Management

Course Assessment

C++ Essentials Exam

Compile-Time Programming

Introduction Introduction to Template Metaprogramming Template Creation Type Traits Programming with Constant Expressions The if constexpr Statement Comparison with Runtime Polymorphism Checking Programming Errors at Compile Time Constraints and Concepts Syntactic Overview of Constraints and Concepts Real-World Examples of Metaprogramming I Real-World Examples of Metaprogramming II Summary: Compile-Time Programming Quiz: Compile-Time Programming

Essential Utilities

Introduction Representing Optional Values with std::optional Fixed-Size Heterogenous Collections Tuple Unrolling The Variadic Template Parameter Pack Dynamically Sized Heterogenous Collections Heterogenous Collections Using Variant Real-World Example 1 Real-World Example 2 Summary: Essential Utilities Quiz: Essential Utilities

Proxy Objects and Lazy Evaluation

Introduction Introducing Lazy Evaluation and Proxy Objects Avoiding Constructing Objects Using Proxy Objects Postponing sqrt Computations Implementing the LengthProxy Object Creative Operator Overloading and Proxy Objects Summary : Proxy Objects and Lazy Evaluation Quiz: Proxy Objects and Lazy Evaluation

Concurrency

Introduction Understanding the Basics of Concurrency Data Races Concurrent Programming in C++Advanced Concepts in Concurrent Programming Best Practices for Error Handling in Concurrent Programming Additional Synchronization Primitives in C++20 Signalling and Resource Counting Using Semaphores Atomic Support in C++Multithreaded Programming with shared_ptr and Atomic References The C++ Memory Model Lock-free Programming Performance Guidelines Summary: Concurrency Quiz: Concurrency

Coroutines and Lazy Generators

Introduction An Introduction to C++ Coroutines Executing Subroutines and Coroutines on the CPU Stackless vs. Stackful Coroutines Coroutines in C++A Minimal but Complete Example Avoiding Dangling References Generators Solving Generator Problems A Real-World Example Using Generators Summary: Coroutines and Lazy Generators Quiz: Coroutines and Lazy Generators

Asynchronous Programming with Coroutines

Introduction Awaitable Types Revisited Implementing a Rudimentary Task Type (Part 1)Implementing a Rudimentary Task Type (Part 2)Synchronously Waiting for a Task to Complete Wrapping a Callback-Based API A Concurrent Server Using Boost.Asio Summary: Asynchronous Programming with Coroutines

Parallel Algorithms

Introduction The Importance of Parallelism Implementing Parallel std::transform()Divide and Conquer Implementing Parallel std::count_if() and std::copy_if()Approach 1: Use a Synchronized Write Position Approach 2: Split the Algorithm Into Two Parts Parallel Standard Library Algorithms Unsequenced Policy Additions and Changes to Parallel Algorithms Parallelizing an Index-Based for-Loop Summary: Parallel Algorithms Quiz: Parallel Algorithms

Course Assessment

C++ Advanced Concepts Exam

Summary: Analyzing and Measuring Performance

A summary of what we discussed in the “Analyzing and Measuring Performance” chapter.

In this chapter, you learned how to compare the efficiency of algorithms by using big O notation. You now know that the C++ standard library provides complexity guarantees for algorithms and data structures. All standard library algorithms specify their worst-case or average-case performance guarantees, whereas containers and iterators specify amortized or exact complexity.

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