Gain insights into using Modern C++ for embedded programming. Learn about safety-critical systems, optimize performance, manage limited resources, and handle parallel execution effectively.

waleed1.tar.gz

C++11

C++ 17

Embedded Programming with Modern C++  is highly valuable for each professional programmer.

In the past, embedded and system programming have had their pitfalls, but modern C++ has been designed to be a better language for this type of development, addressing the previous pitfalls/requirements explicitly. What are these requirements? Embedded systems deal with safety-critical systems, meaning they must guarantee high performance combined with limited resources, while also working in parallel.

The scope of this course goes beyond just embedded programming. Developers who write servers, games, or trading systems may especially benefit from this course because they also have to deal with safety-critical systems, high performance, reduced resources, and parallel execution in their jobs.

To get the most out of the course, you only need a basic understanding of C++. Building off this understanding, this course goes over all the essentials of embedded programming with Modern C++.

Let's get started!

Embedded Programming with Modern C++

# Task 1
The calculation of the scalar product in the program below is quite easy to parallelize. Take a look at the explanation below to better understand the code.

**Launch four asynchronous functions to calculate the scalar product.** 

// dotProduct.cpp

#include <chrono>
#include <iostream>
#include <numeric>
#include <random>
#include <vector>

static const int NUM= 100000000;

long long getDotProduct(std::vector<int>& v, std::vector<int>& w){
  return std::inner_product(v.begin(), v.end(), 
                             w.begin(), 
                             0LL);
}

int main(){

  std::cout << std::endl;

  // get NUM random numbers from 0 .. 100
  std::random_device seed;

  // generator
  std::mt19937 engine(seed());

  // distribution
  std::uniform_int_distribution<int> dist(0, 100);

  // fill the vectors
  std::vector<int> v,  w;
  v.reserve(NUM);
  w.reserve(NUM);
  for (int i=0; i< NUM; ++i){
    v.push_back(dist(engine));
    w.push_back(dist(engine));
  }

  // measure the execution time
  std::chrono::system_clock::time_point start = std::chrono::system_clock::now();
  std::cout << "getDotProduct(v, w): " << getDotProduct(v, w) << std::endl;
  std::chrono::duration<double> dur  = std::chrono::system_clock::now() - start;
  std::cout << "Sequential Execution: "<< dur.count() << std::endl;

  std::cout << std::endl;

}

## Explanation

* The program uses the functionality of the random and time library. Both libraries are part of C++11. 

* The two vectors `v` and `w` are created and filled with random numbers in lines 31 - 37.  

*  Each of the vectors gets (lines 34 - 37) one hundred million elements. `dist(engine)` in lines 35 and 36 generated the random numbers, which are uniformly distributed in the range from 0 to 100. 

* The current calculation of the scalar product takes place in the function `getDotProduct` (lines 11 - 15). We have explicitly used the standard template library algorithm `std::inner_product` for the computation.  

* The return statement sums up the results of the futures.

In this exercise, you will design asynchronous functions and compare the performance of single and multithreaded programs.

Introduction

Safety-Critical Systems

High Performance

Reduced Resources

Several Tasks Simultaneously

Conclusion

- Exercise

Task 1