# Concurrent Execution

Doing work in parallel. pperl ships two distinct concurrency stories
and they answer different questions:

- **Auto-parallelization** — `pperl`’s runtime detects parallelisable
  patterns in ordinary Perl and spreads them across cores without
  any user-level threading. This is the preferred answer for
  CPU-bound loops over large data.
- **Classical ithreads (partial support)** — Perl 5’s `threads` and
  `threads::shared` model. pperl’s support here is deliberately
  limited; many programs that historically used ithreads are better
  rewritten against the auto-parallel path.

Start with the [decision chapter](alternatives.md) if you have an
existing threaded program and are deciding how to port it; start
with [parallel](parallel.md) if you are writing new code and want to
understand when pperl speeds your loop up.

* [Parallel Execution](parallel.md)
  * [How It Works](parallel.md#how-it-works)
  * [What Gets Parallelized](parallel.md#what-gets-parallelized)
  * [CLI Control](parallel.md#cli-control)
  * [Performance](parallel.md#performance)
  * [Limitations](parallel.md#limitations)
  * [How Reduction Detection Works](parallel.md#how-reduction-detection-works)
* [Threads](threads.md)
  * [pperl status — read this first](threads.md#pperl-status-read-this-first)
  * [How this chapter is organised](threads.md#how-this-chapter-is-organised)
  * [Reference cross-links](threads.md#reference-cross-links)