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How can I create a parallel stack and run a coroutine on it?

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  • Last Updated : 21 Mar, 2023
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What is Parallel Stack?

A parallel stack is a type of data structure that allows multiple threads to access and manipulate the stack concurrently

In a parallel stack, each thread has its own stack, and all of the stacks are connected in such a way that they can be accessed and manipulated simultaneously. This allows for the efficient use of multi-core processors and can improve the performance of parallel algorithms.

What is Coroutine?

A coroutine is a subroutine that can pause its execution and return control to its caller, allowing the caller to resume the subroutine’s execution at a later time. 

This allows for more efficient use of resources, as the subroutine can pause its execution and release its resources while it is waiting to be resumed, rather than consuming resources continuously while it is waiting.

What is the Relation between Parallel stack and Coroutine ?

There is no inherent relation between parallel stacks and coroutines. However, both parallel stacks and coroutines are used in parallel programming, and they can be used together to improve the performance and efficiency of parallel algorithms

For example, a parallel stack could be used to store the state of each thread in a parallel algorithm that uses coroutines to coordinate the execution of the threads.

What are the advantages of using Parallel Stack?

Some of the advantages of using parallel stacks are mentioned below:

  • Improved performance
  • Efficient use of resources
  • Simplified programming
  • Increased scalability.

How to create a Parallel Stack and run a coroutine in it?

The asyncio module in Python provides an easy way to write concurrent code using coroutines and the async/await syntax. This makes it possible to write code that can run concurrently on multiple parallel stacks, allowing you to take advantage of multiple cores on your CPU and improve the performance of your code.

In summary, the asyncio module provides a convenient way to write concurrent code in Python and take advantage of multiple cores on your CPU. By defining coroutines and running them on asyncio event loops, you can easily create parallel stacks and run multiple tasks concurrently.

Below is the code to implement:


import asyncio
async def my_coroutine():
    # Do some work here
    return result
# Create an asyncio event loop
loop = asyncio.get_event_loop()
# Schedule the coroutine to run on the event
# loop
task = loop.create_task(my_coroutine())
# Run the event loop until the coroutine is
# done
# Get the result of the coroutine
result = task.result()


const myCoroutine = async () => {
    // Do some work here
    return result;
// Create an async event loop
const loop = async () => {
    // Schedule the coroutine to run on the event loop
    let task = myCoroutine();
    let result = await task;
    // Get the result of the coroutine
    return result;


#include <iostream>
#include <chrono>
#include <future>
using namespace std::chrono;
// Declare the coroutine
std::future<int> my_coroutine() {
    // Do some work here
    return std::async(std::launch::async, []() {
        int result = 0;
        // Do some work here
        return result;
int main() {
    // Schedule the coroutine to run
    auto task = my_coroutine();
    // Wait for the coroutine to finish and get the result
    int result = task.get();
    // Print the result
    std::cout << "Result: " << result << std::endl;
    return 0;

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