Thread

• See also loop

General

Threads of execution are a way for a program to split itself into two or more simultaneously (or pseudo-simultaneously) running tasks. Threads and processes differ from one operating system to another, but in general, the way that a thread is created and shares its resources is different from the way a process does.

Multiple threads can be executed in parallel on many computer systems. This multithreading generally occurs by time slicing, wherein a single processor switches between different threads, in which case the processing is not literally simultaneous, for the single processor is only really doing one thing at a time. This switching can happen so fast as to give the illusion of simultaneity to an end user. For instance, a typical PC today contains only one processor core, but you can run multiple programs at once, such as a word processor alongside an audio playback program; though the user experiences these things as simultaneous, in truth, the processor is quickly switching back and forth between these separate processes. On a multiprocessor or multi-core system, threading can be achieved via multiprocessing, wherein different threads and processes can run literally simultaneously on different processors or cores.

Many modern operating systems directly support both time-sliced and multiprocessor threading with a process scheduler. The operating system kernel allows programmers to manipulate threads via the system call interface. Some implementations are called a kernel thread, whereas a lightweight process is a specific type of kernel thread that shares the same state and information.

Nodal

In the nodal model, the multithreading time-slicing is achieved by time-division multiplexing using the nodal reduction algorithm. Loops and threads are formed from next and prev associations and a focus association allows the formation of trees of loops and threads.

A thread is just a loop which ends with a next association linking to root. This has the effect of the thread automatically unhooking from its context after completion because any node with a focus of root is considered to have no focus because every quanta sent to root is a new quanta. Alternatively a context could update its own loop content dynamically.

If a thread has static structure, then it can appear in many contexts simaltaneously, it's parent association will be dynamically maintained by the nodal reduction algorithm.

Hence, while traditional threading is intrinsically inefficient due to process scheduling delays, the nodal model's "router-type" multiplexing does not share that problem: this is a step forward in threading theory and practice.