What is Concurrency?

In Real Life:

Concurrency in real life refers to the ability to handle multiple activities simultaneously within a given timeframe. This can be seen in various scenarios where multiple tasks are being managed simultaneously.

Examples:

• Chef in a Kitchen: A chef might prepare several dishes simultaneously. While one dish is baking in the oven, the chef can chop vegetables for another dish. This is the concurrent execution of tasks.
• Office Work: An employee might be handling emails, answering phone calls, and attending daily meetings. These tasks overlap in time, demonstrating concurrency.
• Traffic Management: Traffic lights at an intersection manage the flow of cars from different directions. While cars move in one direction, others wait, and pedestrians might cross the street, all managed concurrently.

In Programming:

In programming, concurrency refers to the execution of multiple tasks or processes simultaneously, potentially overlapping in execution time. It is a way to structure a program to do multiple things at once, improving efficiency and performance.

Examples:

• Multithreading: Running multiple threads within a single application. Each thread can perform a different task, such as fetching data from the network, processing user input, and updating the user interface.
• Asynchronous Programming: Using constructs like async/await to perform non-blocking operations. For instance, fetching data from a server while allowing the user interface to remain responsive.
• Parallel Processing: Executing multiple processes or computations simultaneously, often on different CPU cores. This is common in scientific computing, image processing, and machine learning tasks.

What is Parallelism?

In Real Life:

Parallelism in real life refers to the simultaneous execution of multiple tasks by multiple resources. It involves doing multiple things at the same time.

Examples:

• Construction Site: Workers on a construction site performing different tasks simultaneously, such as one worker laying bricks while another installs windows.
• Orchestra: Different musicians play their instruments at the same time to create a symphony.
• Restaurant: Multiple chefs in a restaurant kitchen cooking different dishes at the same time, each using different equipment

Programming:

In programming, parallelism refers to the simultaneous execution of multiple computations or processes. It typically involves dividing a task into subtasks that can be processed concurrently on multiple processors or cores.

Examples:

• Parallel Processing: Running multiple computations simultaneously on different CPU cores to speed up processing time.
• Parallel Algorithms: Algorithms that divide a problem into subproblems that can be solved concurrently, like matrix multiplication or sorting algorithms.
• Distributed Systems: Multiple servers processing different parts of a task at the same time to handle large-scale computations, such as in data centres or cloud computing

Concurrency vs Parallelism?

Concurrency: Two queues share one vending machine, serving one person at a time by alternating between queues.
Parallelism: Each queue has its vending machine, allowing both queues to be served simultaneously.

Parallelism Will give more speed but it involves more CPU resources.

Because Parallelism involves more resources we need to find a way that Concurrency can be achieved.

How Can We Achieve Concurrency in iOS?

1. Achieving multi-threading by creating threads manually
2. GCD (Grand Central Dispatch)
3. Operation Queues
4. Modern Concurrency By Swift. (async and await)