10.3 Parallel Programming Basics

Let’s go through Parallel Programming basics in C# — a way to run multiple operations concurrently to improve performance, especially on multi-core systems.

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📌 1. What is Parallel Programming?

• Parallel programming executes multiple operations simultaneously.

• Useful for CPU-bound operations (e.g., computations, data processing).

• C# provides built-in support through:

  • Parallel class

  • Task / Task<T>

  • PLINQ (Parallel LINQ)

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📌 2. Using the Parallel Class

Parallel.For

using System;
using System.Threading.Tasks;
 
Parallel.For(0, 5, i =>
{
    Console.WriteLine($"Task {i} running on thread {Task.CurrentId}");
});

• Runs iterations in parallel

• Automatically distributes work across threads

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Parallel.ForEach

string[] names = { "Alice", "Bob", "Charlie" };
 
Parallel.ForEach(names, name =>
{
    Console.WriteLine($"Processing {name} on thread {Task.CurrentId}");
});

• Iterates over a collection in parallel

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📌 3. Using Tasks for Parallel Work

Task t1 = Task.Run(() => Console.WriteLine("Task 1"));
Task t2 = Task.Run(() => Console.WriteLine("Task 2"));
 
Task.WaitAll(t1, t2); // Wait for all tasks to complete

• Tasks can be combined with Task.WhenAll or Task.WhenAny

• Offers more flexibility than Parallel for complex scenarios

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📌 4. Parallel LINQ (PLINQ)

• PLINQ allows parallel queries on collections using LINQ

• Syntax: add .AsParallel() to the collection

int[] numbers = { 1, 2, 3, 4, 5, 6 };
var evenNumbers = numbers.AsParallel()
                         .Where(n => n % 2 == 0)
                         .ToArray();
 
foreach (var n in evenNumbers)
    Console.WriteLine(n); // 2, 4, 6

• Automatically utilizes multiple cores

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📌 5. Important Considerations

1. Thread Safety: Shared data must be synchronized (locks, Concurrent collections).

2. Overhead: Small tasks may be slower in parallel due to thread management.

3. Exceptions: Use AggregateException to handle multiple exceptions.

try
{
    Parallel.For(0, 5, i =>
    {
        if (i == 3) throw new Exception("Error at 3");
    });
}
catch (AggregateException ex)
{
    foreach (var e in ex.InnerExceptions)
        Console.WriteLine(e.Message);
}

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📌 6. Summary Table

Feature	Description
Parallel.For	Run a loop in parallel
Parallel.ForEach	Parallel iteration over collections
Tasks / Task	Flexible parallel operations with results
PLINQ	Parallel LINQ queries on collections
Key Considerations	Thread safety, exception handling, overhead

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✅ Tip:

• Use Parallel.For/ForEach for CPU-bound loops

• Use Tasks for flexible parallel operations

• Use PLINQ for data processing with LINQ queries

• Avoid parallelism for tiny, fast operations, as overhead may reduce performance