module-6.6-parallel-and-concurrent-programming.md

6.6. Parallel and Concurrent Programming

Parallel and concurrent programming techniques are essential for optimizing performance when dealing with CPU-bound tasks and improving the responsiveness of web applications. In this submodule, we'll dive into parallel and concurrent programming concepts and demonstrate how to apply them.

Parallel Computing

Parallel computing involves breaking down a large task into smaller subtasks and executing them simultaneously, making efficient use of available CPU cores. Node.js provides the cluster module to create multiple child processes and distribute work across CPU cores.

Example:

const cluster = require('cluster');
const http = require('http');
const numCPUs = require('os').cpus().length;

if (cluster.isMaster) {
  // Fork workers for each CPU core
  for (let i = 0; i < numCPUs; i++) {
    cluster.fork();
  }

  cluster.on('exit', (worker, code, signal) => {
    console.log(`Worker ${worker.process.pid} died`);
  });
} else {
  // Create an HTTP server for each worker
  http.createServer((req, res) => {
    res.writeHead(200);
    res.end('Hello, World!\n');
  }).listen(8000);

  console.log(`Worker ${process.pid} started`);
}

In this example, the cluster module is used to create multiple child processes, each running its HTTP server.

Concurrency Models

Concurrency models define how multiple tasks run concurrently without conflicting. There are different models, including worker threads, shared memory, and message-passing.

Example (Worker Threads in Node.js):

const { Worker, isMainThread, parentPort } = require('worker_threads');

if (isMainThread) {
  // This code runs in the main thread
  const worker = new Worker(__filename);
  worker.postMessage('Hello from the main thread');
} else {
  // This code runs in the worker thread
  parentPort.on('message', (message) => {
    console.log(`Received from main thread: ${message}`);
  });
}

In this example, we use worker threads in Node.js to run JavaScript code concurrently.

Benefits

• Parallel and concurrent programming allows for efficient utilization of multiple CPU cores.
• Different concurrency models provide flexibility in handling asynchronous and CPU-bound tasks.

Understanding parallel and concurrent programming is crucial for optimizing the performance of web applications, especially when dealing with computationally intensive tasks or building real-time, responsive systems.