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concurrency

Concurrency vs Parallelism

Concurrency is about dealing with multiple tasks at once by interleaving their execution, while parallelism is about executing multiple tasks simultaneously on separate CPU cores. A single-core system can be concurrent (switching between tasks) but not parallel. Concurrency is a design pattern for structuring programs; parallelism is an execution strategy. Understanding this distinction is essential for choosing the right tool: async/event loops for I/O-bound concurrency, multiprocessing for CPU-bound parallelism.

Use Cases

  • •Choosing between asyncio (concurrent) and multiprocessing (parallel) in Python
  • •Designing web servers that handle many connections (concurrency) vs compute farms (parallelism)
  • •Understanding why Node.js (concurrent, single-threaded) excels at I/O but struggles with CPU tasks
  • •Architecting data pipelines that combine concurrent I/O fetching with parallel CPU processing

Visualization

INITIALTask ATask BvsCPU CoreidleCore 1idleCore 2idle
Speed:1x
Concurrency (left): interleaving tasks on one core. Parallelism (right): truly simultaneous on multiple cores.Step 1 / 6

Implementation

Output

Click "Run Code" to see output...