Parallelism means running multiple tasks simultaneously, with the performance goal of using available hardware—especially for bulk data processing. Concurrency often emphasizes separation of concerns or responsiveness instead, though the terms overlap. section 1.1.3
Parallel work can be organized in different ways:
- Run separate processes on distinct networked machines to increase available parallelism, accepting higher communication costs. section 1.1.2
- Express work as a standard-library algorithm call and delegate task parallelization to the library for optimal performance where supported. section 9.0





































