What are the two types of concurrency?

The two main types of concurrency are:

1. Concurrent Execution (Concurrency)

Concurrency refers to the concept of managing multiple tasks at the same time but not necessarily executing them simultaneously. In concurrent execution, multiple tasks or threads make progress independently, but they may share the same CPU core. Concurrency involves time-slicing, where the operating system switches between tasks so quickly that it appears as if they are running at the same time. However, in reality, only one task is running at a given instant on a single core.

In systems with multiple cores, concurrent tasks can run in parallel, but on a single-core system, the CPU is simply switching between tasks in a way that makes them appear to run concurrently.

Characteristics:

• Tasks run independently and make progress at their own pace.
• Tasks can share the same CPU core, with the OS switching between them using time-sharing.
• It can be implemented on both single-core and multi-core systems.
• The focus is on managing multiple tasks and their coordination rather than executing them at the same time.

Example:

Running a web server where it handles multiple client requests. Each request is processed concurrently, but not necessarily simultaneously. The server switches between tasks so quickly that the user experiences them as running at the same time.

2. Parallel Execution (Parallelism)

Parallelism refers to the actual simultaneous execution of multiple tasks. This happens when multiple threads or processes are executed at the same time on multiple CPU cores. Unlike concurrency, parallelism ensures that tasks are performed in parallel on separate cores, leading to true simultaneous execution.

Parallelism is particularly useful for CPU-bound tasks, where the workload can be split into independent subtasks that can be processed simultaneously. A multi-core processor allows each thread or task to run on a separate core, achieving true parallelism and improving performance.

Characteristics:

• Tasks run simultaneously on different CPU cores.
• It requires a multi-core system for true parallel execution.
• Tasks are typically independent and can be executed in parallel without waiting on each other.
• It is used primarily for CPU-bound tasks that can be divided into independent chunks.

Example:

In image processing, if a program is splitting an image into segments to apply filters, each segment can be processed in parallel on different cores, significantly speeding up the computation.

Key Differences Between Concurrency and Parallelism:

Conclusion:

• Concurrency is about dealing with many tasks at once, managing how they are scheduled, while parallelism is about executing multiple tasks simultaneously across multiple cores.
• While both concurrency and parallelism improve efficiency, parallelism requires multiple CPU cores for true simultaneous execution, while concurrency can be achieved with time-sharing even on a single core.

Recommended Courses:

To dive deeper into concurrency and parallelism in Java, consider the following courses from DesignGurus.io:

• Grokking Multithreading and Concurrency for Coding Interviews
• Grokking Data Structures & Algorithms for Coding Interviews
• Grokking the System Design Interview

These courses will help you understand both concurrency and parallelism, and how to effectively implement them in your Java programs.