Parallelism executes multiple computations simultaneously. A single thread runs on one processor core at a time; parallel systems run multiple threads at once when hardware provides available cores. Concurrency is broader: multiple executions may progress within one application without running simultaneously. section 8.4
The practical goal is to divide work into tasks that can use additional processors. Four threads on four cores can run in parallel, while applications with more threads than processors may run concurrently instead. Parallel execution can improve throughput, but task ordering is not guaranteed. section 8.4
Parallel Mandelbrot work
A Python application creates a ThreadPoolExecutor with four workers, submits Mandelbrot computations, and awaits eight tasks with asyncio.gather. The example distributes independent image calculations across execution threads rather than processing them serially.
