Concurrency & Parallelism Basics
Concurrency and parallelism are foundational concepts in computing. Concurrency refers to the ability of a system to handle multiple tasks at once by managing their execution, often by interleaving them on a single processor. Parallelism, on the other hand, involves executing multiple tasks simultaneously, typically on multiple processors or cores. Both approaches aim to improve efficiency and performance, but concurrency focuses on task management, while parallelism emphasizes simultaneous execution.
Concurrency & Parallelism Basics
Concurrency and parallelism are foundational concepts in computing. Concurrency refers to the ability of a system to handle multiple tasks at once by managing their execution, often by interleaving them on a single processor. Parallelism, on the other hand, involves executing multiple tasks simultaneously, typically on multiple processors or cores. Both approaches aim to improve efficiency and performance, but concurrency focuses on task management, while parallelism emphasizes simultaneous execution.
💡 Key Takeaways
- Differentiate concurrency from parallelism and know when to use each.
- Explain how concurrency interleaves tasks on a single processor to improve responsiveness.
- Describe how parallelism executes multiple tasks simultaneously using multiple cores or hardware.
- Identify basic concurrency concepts (threads and processes) and common pitfalls (race conditions and deadlocks).
❓ Frequently Asked Questions
What is concurrency in computing?
Concurrency is the ability of a system to manage multiple tasks by coordinating their progress, often by interleaving execution on a single processor or using asynchronous operations so work can advance while sharing time.
What is parallelism in computing?
Parallelism is executing multiple tasks at the same time, typically using multiple cores or processors to perform work simultaneously.
What is the difference between concurrency and parallelism?
Concurrency focuses on managing multiple tasks over time, possibly by interleaving on one core. Parallelism focuses on doing multiple tasks at the exact same time using multiple cores or hardware units.
When should I use concurrency vs parallelism, and what are common pitfalls?
Use concurrency to improve responsiveness and overlap I/O-bound work; use parallelism to speed up CPU-bound tasks. Common pitfalls include race conditions, deadlocks, synchronization complexity, and overhead from context switching or contention.