Thread (computing)

In computer science, a thread of execution is the smallest sequence of programmed instructions that can be managed independently by a scheduler, which is typically a part of the operating system. The implementation of threads and processes differs between operating systems, but in most cases a thread is a component of a process. Multiple threads can exist within one process, executing concurrently and sharing resources such as memory, while different processes do not share these resources. In particular, the threads of a process share its executable code and the values of its dynamically allocated variables and non-thread-local global variables at any given time.Although threads seem to be a small step from sequential computation, in fact, they represent a huge step. They discard the most essential and appealing properties of sequential computation: understandability, predictability, and determinism. Threads, as a model of computation, are wildly non-deterministic, and the job of the programmer becomes one of pruning that nondeterminism. In computer science, a thread of execution is the smallest sequence of programmed instructions that can be managed independently by a scheduler, which is typically a part of the operating system. The implementation of threads and processes differs between operating systems, but in most cases a thread is a component of a process. Multiple threads can exist within one process, executing concurrently and sharing resources such as memory, while different processes do not share these resources. In particular, the threads of a process share its executable code and the values of its dynamically allocated variables and non-thread-local global variables at any given time. Systems with a single processor generally implement multithreading by time slicing: the central processing unit (CPU) switches between different software threads. This context switching generally happens very often and rapidly enough that users perceive the threads or tasks as running in parallel. On a multiprocessor or multi-core system, multiple threads can execute in parallel, with every processor or core executing a separate thread simultaneously; on a processor or core with hardware threads, separate software threads can also be executed concurrently by separate hardware threads. Threads made an early appearance under the name of 'tasks' in OS/360 Multiprogramming with a Variable Number of Tasks (MVT) in 1967. Saltzer (1966) credits Victor A. Vyssotsky with the term 'thread'. The process schedulers of many modern operating systems directly support both time-sliced and multiprocessor threading, and the operating system kernel allows programmers to manipulate threads by exposing required functionality through the system-call interface. Some threading implementations are called kernel threads, whereas light-weight processes (LWP) are a specific type of kernel thread that share the same state and information. Furthermore, programs can have user-space threads when threading with timers, signals, or other methods to interrupt their own execution, performing a sort of ad hoc time-slicing. Threads differ from traditional multitasking operating system processes in several ways described below: Systems such as Windows NT and OS/2 are said to have cheap threads and expensive processes; in other operating systems there is not so great a difference except the cost of an address space switch which on some architectures (notably x86) results in a translation lookaside buffer (TLB) flush. In computer programming, single-threading is the processing of one command at a time. The opposite of single-threading is multithreading. In the formal analysis of the variables' semantics and process state, the term single threading can be used differently to mean 'backtracking within a single thread', which is common in the functional programming community. Multithreading is mainly found in multitasking operating systems. Multithreading is a widespread programming and execution model that allows multiple threads to exist within the context of one process. These threads share the process's resources, but are able to execute independently. The threaded programming model provides developers with a useful abstraction of concurrent execution. Multithreading can also be applied to one process to enable parallel execution on a multiprocessing system.