Process (computing) in the context of Interprocess communication

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 computing, time-sharing is the concurrent sharing of a computing resource among many tasks or users by giving each task or user a small slice of processing time. This quick switch between tasks or users gives the illusion of simultaneous execution. It enables multi-tasking by a single user or enables multiple-user sessions.

Developed during the 1960s, its emergence as the prominent model of computing in the 1970s represented a major technological shift in the history of computing. By allowing many users to interact concurrently with a single computer, time-sharing dramatically lowered the cost of providing computing capability, made it possible for individuals and organizations to use a computer without owning one, and promoted the interactive use of computers and the development of new interactive applications.

In computing, a window is a graphical control element. It consists of a visual area containing some of the graphical user interface of the program it belongs to and is framed by a window decoration. It usually has a rectangular shape that can overlap with the area of other windows. It displays the output of and may allow input to one or more processes.

Windows are primarily associated with graphical displays, where they can be manipulated with a pointer by employing some kind of pointing device. Text-only displays can also support windowing, as a way to maintain multiple independent display areas, such as multiple buffers in Emacs. Text windows are usually controlled by keyboard, though some also respond to the mouse.

A dynamic linker is an operating system feature that loads and links dynamic libraries for an executable at runtime; before or while it is running. Although the details vary by operating system, typically, a dynamic linker copies the content of each library from persistent storage to RAM, fills jump tables and relocates pointers.

Linking is often referred to as a process that is performed when the executable is compiled, while a dynamic linker is a special part of an operating system that loads external shared libraries into a running process and then binds those shared libraries dynamically to the running process. This approach is also called dynamic linking or late linking.

In computing, scheduling is the action of assigning resources to perform tasks. The resources may be processors, network links or expansion cards. The tasks may be threads, processes or data flows.

The scheduling activity is carried out by a mechanism called a scheduler. Schedulers are often designed so as to keep all computer resources busy (as in load balancing), allow multiple users to share system resources effectively, or to achieve a target quality-of-service.

The THE multiprogramming system (THE OS) was a computer operating system designed by a team led by Edsger W. Dijkstra, described in monographs in 1965-66 and published in 1968.Dijkstra never named the system; "THE" is simply the abbreviation of "Technische Hogeschool Eindhoven", then the name (in Dutch) of the Eindhoven University of Technology of the Netherlands. The THE system was primarily a batch system that supported multitasking; it was not designed as a multi-user operating system. It was much like the SDS 940, but "the set of processes in the THE system was static".

The THE system apparently introduced the first forms of software-based paged virtual memory (the Electrologica X8 did not support hardware-based memory management), freeing programs from being forced to use physical locations on the drum memory. It did this by using a modified ALGOL compiler (the only programming language supported by Dijkstra's system) to "automatically generate calls to system routines, which made sure the requested information was in memory, swapping if necessary". Paged virtual memory was also used for buffering input/output (I/O) device data, and for a significant portion of the operating system code, and nearly all the ALGOL 60 compiler. In this system, semaphores were used as a programming construct for the first time.

Memory management (also dynamic memory management, dynamic storage allocation, or dynamic memory allocation) is a form of resource management applied to computer memory. The essential requirement of memory management is to provide ways to dynamically allocate portions of memory to programs at their request, and free it for reuse when no longer needed. This is critical to any advanced computer system where more than a single process might be underway (multitasking) at any time.

Several methods have been devised that increase the effectiveness of memory management. Virtual memory systems separate the memory addresses used by a process from actual physical addresses, allowing separation of processes and increasing the size of the virtual address space beyond the available amount of RAM using paging or swapping to secondary storage. The quality of the virtual memory manager can have an extensive effect on overall system performance. The system allows a computer to appear as if it may have more memory available than physically present, thereby allowing multiple processes to share it.

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. In many cases, a thread is a component of a process.

The multiple threads of a given process may be executed concurrently (via multithreading capabilities), 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.

Blink is a browser engine developed as part of the free and open-source Chromium project. Blink is by far the most-used browser engine, due to the market share dominance of Google Chrome and the fact that many other browsers are based on the Chromium code.

To create Chrome, Google initially chose to use Apple's WebKit engine. However, Google needed to make substantial changes to its code to support Chrome's novel multi-process browser architecture. Over the course of several years, the divergence from Apple's version increased, so Google decided to officially fork its version as Blink in 2013.

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 computer science, interprocess communication (IPC) is the sharing of data between running processes in a computer system, or between multiple such systems. Mechanisms for IPC may be provided by an operating system. Applications which use IPC are often categorized as clients and servers, where the client requests data and the server responds to client requests. Many applications are both clients and servers, as commonly seen in distributed computing.

IPC is very important to the design process for microkernels and nanokernels, which reduce the number of functionalities provided by the kernel. Those functionalities are then obtained by communicating with servers via IPC, leading to a large increase in communication when compared to a regular monolithic kernel. IPC interfaces generally encompass variable analytic framework structures. These processes ensure compatibility between the multi-vector protocols upon which IPC models rely.

In computer science, asynchronous I/O (also non-sequential I/O) is a form of input/output (I/O) processing that permits other processing to continue before the I/O operation has finished. A name used for asynchronous I/O in the Windows API is overlapped I/O.

Input and output operations on a computer can be extremely slow compared to the processing of data. An I/O device can incorporate mechanical devices that must physically move, such as a hard drive seeking a track to read or write; this is often orders of magnitude slower than the switching of electric current. For example, during a disk operation that takes ten milliseconds to perform, a processor that is clocked at one gigahertz could have performed ten million instruction-processing cycles.

In computer operating systems, a light-weight process (LWP) is a means of achieving multitasking. In the traditional meaning of the term, as used in Unix System V and Solaris, a LWP runs in user space on top of a single kernel thread and shares its address space and system resources with other LWPs within the same process. Multiple user-level threads, managed by a thread library, can be placed on top of one or many LWPs - allowing multitasking to be done at the user level, which can have some performance benefits.

In some operating systems, there is no separate LWP layer between kernel threads and user threads. This means that user threads are implemented directly on top of kernel threads. In those contexts, the term "light-weight process" typically refers to kernel threads and the term "threads" can refer to user threads. On Linux, user threads are implemented by allowing certain processes to share resources, which sometimes leads to these processes to be called "light weight processes". Similarly, in SunOS version 4 onwards (prior to Solaris) "light weight process" referred to user threads.

In computing, multitasking is the concurrent execution of multiple tasks (also known as processes) over a certain period of time. New tasks can interrupt already started ones before they finish, instead of waiting for them to end. As a result, a computer executes segments of multiple tasks in an interleaved manner, while the tasks share common processing resources such as central processing units (CPUs) and main memory. Multitasking automatically interrupts the running program, saving its state (partial results, memory contents and computer register contents) and loading the saved state of another program and transferring control to it. This "context switch" may be initiated at fixed time intervals (pre-emptive multitasking), or the running program may be coded to signal to the supervisory software when it can be interrupted (cooperative multitasking).

Multitasking does not require parallel execution of multiple tasks at exactly the same time; instead, it allows more than one task to advance over a given period of time. Even on multiprocessor computers, multitasking allows many more tasks to be run than there are CPUs.

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.