How cooperative thread pool works?

The cooperative thread pool in Swift is designed to manage concurrency efficiently by allowing tasks to yield the CPU when they are waiting for asynchronous operations to complete. This helps in optimizing CPU usage and improving the performance of concurrent applications.

Here are some key points about how the cooperative thread pool works:

Tasks as Fundamental Units: In Swift, the fundamental unit of concurrency is a task, which represents an independent concurrent execution context. Tasks are lightweight, allowing the creation of many tasks without significant overhead (A Swift Tour: Explore Swift’s features and design).
Suspension and Yielding: When a task performs an asynchronous operation, such as reading from the disk or waiting for a network response, it suspends itself. This suspension allows the CPU to be yielded to other tasks, ensuring that the CPU is not idle while waiting for I/O operations to complete (A Swift Tour: Explore Swift’s features and design).
Memory Management: The cooperative thread pool uses a slab allocator for memory management. When a task needs memory, it tries to allocate it from the current slab. If the slab is full, a new slab is allocated. Deallocation marks the memory as unused, making it available for future allocations. This approach is typically faster than traditional malloc-based allocation (Explore Swift performance).
Partial Functions: To run an asynchronous function, it is split into partial functions that span the gaps between potential suspension points. This splitting allows the function to be resumed efficiently after suspension (Explore Swift performance).
Data Race Safety: Swift's concurrency model emphasizes data race safety. By using actors and the Sendable protocol, Swift ensures that shared mutable state is protected, preventing data races and ensuring safe concurrent execution (What’s new in Swift).

By leveraging these mechanisms, the cooperative thread pool in Swift provides a robust and efficient way to handle concurrency, making it easier to write performant and safe concurrent applications.