Topic 13824 min readStructured Tutorial

Parallel Programming in C# Asynchronous Programming

Quick Answer

Parallel programming in C# allows multiple tasks to run concurrently, improving application performance. Using asynchronous programming with constructs like Task Parallel Library (TPL) and async/await, developers can write efficient, responsive applications that leverage multi-core processors.

Learning Objectives

Explain the purpose of Parallel Programming in a practical learning context.
Identify the main ideas, terms, and decisions involved in Parallel Programming.
Apply Parallel Programming in a simple real-world scenario or practice task.

Introduction to Parallel Programming in C#

Parallel programming enables a program to perform multiple operations simultaneously, improving performance and responsiveness.

In C#, asynchronous programming combined with parallelism helps utilize system resources efficiently by running tasks concurrently.

This tutorial covers the basics of parallel programming in C#, focusing on practical usage with async and Task Parallel Library.

Parallelism is not about doing more work faster, but about doing more work simultaneously.

Understanding Parallel Programming

Parallel programming involves dividing a problem into independent tasks that can run simultaneously on multiple processors or cores.

This approach contrasts with sequential programming, where tasks run one after another.

Improves application throughput and responsiveness.
Utilizes multi-core processors effectively.
Requires careful management of shared resources to avoid conflicts.

Parallelism vs Concurrency

Concurrency is about dealing with multiple tasks at once, while parallelism is about executing multiple tasks simultaneously.

In C#, asynchronous programming often deals with concurrency, while parallel programming focuses on parallel execution.

Concurrency: Managing multiple tasks, may not run at the same time.
Parallelism: Tasks run simultaneously on different processors.

Task Parallel Library (TPL)

The Task Parallel Library (TPL) is a set of public types and APIs in .NET that simplify parallel programming.

TPL uses the Task class to represent asynchronous operations and provides methods to run tasks in parallel.

Simplifies thread management.
Supports task cancellation and continuation.
Improves scalability and performance.

Creating and Running Parallel Tasks

You can create tasks using Task.Run or Task.Factory.StartNew to execute code asynchronously.

Parallel.For and Parallel.ForEach provide easy ways to run loops in parallel.

Task.Run(() => DoWork());
Parallel.For(0, 10, i => Process(i));

Async and Await Keywords

The async and await keywords in C# simplify writing asynchronous code that is easy to read and maintain.

They allow asynchronous operations to be written in a synchronous style without blocking threads.

Mark methods with async to enable await inside them.
Use await to asynchronously wait for a Task to complete.
Helps keep UI responsive and improve scalability.

Example of Async Method

An async method returns a Task or Task<T> and uses await to asynchronously wait for operations.

Synchronization and Thread Safety

When running tasks in parallel, shared resources must be accessed safely to avoid race conditions and data corruption.

C# provides synchronization primitives like locks, mutexes, and concurrent collections.

Use lock statements to protect critical sections.
Use thread-safe collections like ConcurrentDictionary.
Avoid blocking calls inside async methods.

Practical Example

This example runs a loop in parallel, processing items concurrently on multiple threads.

This async method simulates an asynchronous operation using Task.Delay and returns a result.

Examples

Parallel.For Example

Parallel.For(0, 5, i => {
    Console.WriteLine($"Processing item {i} on thread {Thread.CurrentThread.ManagedThreadId}");
});

This example runs a loop in parallel, processing items concurrently on multiple threads.

Async and Await Example

public async Task<int> FetchDataAsync()
{
    await Task.Delay(1000); // Simulate async work
    return 42;
}

This async method simulates an asynchronous operation using Task.Delay and returns a result.

Best Practices

Use Task Parallel Library for CPU-bound parallel tasks.
Use async and await for I/O-bound asynchronous operations.
Avoid blocking calls in async methods to prevent deadlocks.
Protect shared data with synchronization primitives.
Keep parallel tasks independent to minimize synchronization overhead.

Common Mistakes

Blocking on async code using .Result or .Wait(), causing deadlocks.
Accessing shared variables without synchronization.
Creating too many parallel tasks causing thread pool exhaustion.
Ignoring exceptions thrown in parallel tasks.

Hands-on Exercise

Implement Parallel Data Processing

Write a C# program that uses Parallel.ForEach to process a list of integers by squaring each number concurrently.

Expected output: A list of squared integers processed in parallel.

Hint: Use Parallel.ForEach and a thread-safe collection to store results.

Convert Synchronous Method to Async

Convert a synchronous method that reads a file into an asynchronous method using async and await.

Expected output: An async method that reads file content without blocking.

Hint: Use asynchronous file I/O methods like ReadAsync.

Interview Questions

What is the difference between concurrency and parallelism in C#?

Interview

Concurrency is about managing multiple tasks at once, which may not run simultaneously, while parallelism is about executing multiple tasks simultaneously on multiple processors.

How does async and await improve asynchronous programming in C#?

Interview

Async and await simplify asynchronous programming by allowing developers to write asynchronous code in a synchronous style, improving readability and preventing thread blocking.

What is the Task Parallel Library (TPL)?

Interview

TPL is a .NET library that provides APIs and types to simplify parallel programming, allowing easy creation and management of parallel tasks.