Thread (computing) in the context of Light-weight process

In computing, a task is a unit of execution or a unit of work. The term is ambiguous; precise alternative terms include process, light-weight process, thread (for execution), step, request, or query (for work). In the adjacent diagram, there are queues of incoming work to do and outgoing completed work, and a thread pool of threads to perform this work. Either the work units themselves or the threads that perform the work can be referred to as "tasks", and these can be referred to respectively as requests/responses/threads, incoming tasks/completed tasks/threads (as illustrated), or requests/responses/tasks.

In computer programming, a runtime system or runtime environment is a sub-system that exists in the computer where a program is created, as well as in the computers where the program is intended to be run. The name comes from the compile time and runtime division from compiled languages, which similarly distinguishes the computer processes involved in the creation of a program (compilation) and its execution in the target machine (the runtime).

Most programming languages have some form of runtime system that provides an environment in which programs run. This environment may address a number of issues including the management of application memory, how the program accesses variables, mechanisms for passing parameters between procedures, interfacing with the operating system (OS), among others. The compiler makes assumptions depending on the specific runtime system to generate correct code. Typically the runtime system will have some responsibility for setting up and managing the stack and heap, and may include features such as garbage collection, threads or other dynamic features built into the language.

Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but has gained broader interest due to the physical constraints preventing frequency scaling. As power consumption (and consequently heat generation) by computers has become a concern in recent years, parallel computing has become the dominant paradigm in computer architecture, mainly in the form of multi-core processors.

In computer science, parallelism and concurrency are two different things: a parallel program uses multiple CPU cores, each core performing a task independently. On the other hand, concurrency enables a program to deal with multiple tasks even on a single CPU core; the core switches between tasks (i.e. threads) without necessarily completing each one. A program can have both, neither or a combination of parallelism and concurrency characteristics.

In computing, a process is the instance of a computer program that is being executed by one or many threads. There are many different process models, some of which are light weight, but almost all processes (even entire virtual machines) are rooted in an operating system (OS) process which comprises the program code, assigned system resources, physical and logical access permissions, and data structures to initiate, control and coordinate execution activity. Depending on the OS, a process may be made up of multiple threads of execution that execute instructions concurrently.

While a computer program is a passive collection of instructions typically stored in a file on disk, a process is the execution of those instructions after being loaded from the disk into memory. Several processes may be associated with the same program; for example, opening up several instances of the same program often results in more than one process being executed.

In concurrent computing, deadlock is any situation in which no member of some group of entities can proceed because each waits for another member, including itself, to take action, such as sending a message or, more commonly, releasing a lock. Deadlocks are a common problem in multiprocessing systems, parallel computing, and distributed systems, because in these contexts systems often use software or hardware locks to arbitrate shared resources and implement process synchronization.

In an operating system, a deadlock occurs when a process or thread enters a waiting state because a requested system resource is held by another waiting process, which in turn is waiting for another resource held by another waiting process. If a process remains indefinitely unable to change its state because resources requested by it are being used by another process that itself is waiting, then the system is said to be in a deadlock.

In computing, an event is a detectable occurrence or change in state that the system is designed to monitor, such as user input, hardware interrupt, system notification, or change in data or conditions. When associated with an event handler, an event triggers a response. The handler may run synchronously, where the execution thread is blocked until the event handler completes its processing, or asynchronously, where the event may be processed later. Even when synchronous handling appears to block execution, the underlying mechanism in many systems is still asynchronous, managed by the event loop.

Events can be implemented through various mechanisms such as callbacks, message objects, signals, or interrupts, and events themselves are distinct from the implementation mechanisms used. Event propagation models, such as bubbling, capturing, and pub/sub, define how events are distributed and handled within a system. Other key aspects include event loops, event queueing and prioritization, event sourcing, and complex event processing patterns. These mechanisms contribute to the flexibility and scalability of event-driven systems.

In computing, a context switch is the process of storing the state of a process or thread, so that it can be restored and resume execution at a later point, and then restoring a different, previously saved, state. This allows multiple processes to share a single central processing unit (CPU), and is an essential feature of a multiprogramming or multitasking operating system. In a traditional CPU, each process – a program in execution – uses the various CPU registers to store data and hold the current state of the running process. However, in a multitasking operating system, the operating system switches between processes or threads to allow the execution of multiple processes simultaneously. For every switch, the operating system must save the state of the currently running process, followed by loading the next process state, which will run on the CPU. This sequence of operations that stores the state of the running process and loads the following running process is called a context switch.

The precise meaning of the phrase "context switch" varies. In a multitasking context, it refers to the process of storing the system state for one task, so that task can be paused and another task resumed. A context switch can also occur as the result of an interrupt, such as when a task needs to access disk storage, freeing up CPU time for other tasks. Some operating systems also require a context switch to move between user mode and kernel mode tasks. The process of context switching can have a negative impact on system performance.

In computer programming, thread-local storage (TLS) is a memory management method that uses static or global memory local to a thread. The concept allows storage of data that appears to be global in a system with separate threads.

Many systems impose restrictions on the size of the thread-local memory block, in fact often rather tight limits. On the other hand, if a system can provide at least a memory address (pointer) sized variable thread-local, then this allows the use of arbitrarily sized memory blocks in a thread-local manner, by allocating such a memory block dynamically and storing the memory address of that block in the thread-local variable. On RISC machines, the calling convention often reserves a thread pointer register for this use.