Blocking (computing)

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In computing, a process is an instance of a computer program that is being executed. A process always exists in exactly one process state. A process that is blocked is one that is waiting for some event, such as a resource becoming available or the completion of an I/O operation. [1]

In a multitasking computer system, individual tasks, or threads of execution, must share the resources of the system. Shared resources include: the CPU, network and network interfaces, memory and disk.

When one task is using a resource, it is generally not possible, or desirable, for another task to access it. The techniques of mutual exclusion are used to prevent this concurrent use. When the other task is blocked, it is unable to execute until the first task has finished using the shared resource.

Programming languages and scheduling algorithms are designed to minimize the over-all effect blocking. A process that blocks may prevent local work-tasks from progressing. In this case "blocking" often is seen as not wanted. [2] However, such work-tasks may instead have been assigned to independent processes, where halting one has no or little effect on the others, since scheduling will continue. An example is "blocking on a channel" where passively waiting for the other part (no polling or spin loop) is part of the semantics of channels. [3] Correctly engineered any of these may be used to implement reactive systems.

Deadlock means that processes pathologically wait for each other in a circle. As such it is not directly associated with blocking.

Once the event occurs for which the process is waiting ("is blocked on"), the process is advanced from blocked state to an imminent one, such as runnable.

See also

Related Research Articles

Computer multitasking Concurrent execution of multiple processes

In computing, multitasking is the concurrent execution of multiple tasks 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 and loading the saved state of another program and transferring control to it. This "context switch" may be initiated at fixed time intervals, or the running program may be coded to signal to the supervisory software when it can be interrupted.

Distributed computing is a field of computer science that studies distributed systems. A distributed system is a system whose components are located on different networked computers, which communicate and coordinate their actions by passing messages to one another from any system. The components interact with one another in order to achieve a common goal. Three significant characteristics of distributed systems are: concurrency of components, lack of a global clock, and independent failure of components. Examples of distributed systems vary from SOA-based systems to massively multiplayer online games to peer-to-peer applications.

A real-time operating system (RTOS) is an operating system (OS) intended to serve real-time applications that process data as it comes in, typically without buffer delays. Processing time requirements are measured in tenths of seconds or shorter increments of time. A real-time system is a time-bound system which has well-defined, fixed time constraints. Processing must be done within the defined constraints or the system will fail. They are either event-driven or time-sharing. Event-driven systems switch between tasks based on their priorities, while time-sharing systems switch the task based on clock interrupts. Most RTOSs use a pre-emptive scheduling algorithm.

Mutual exclusion

In computer science, mutual exclusion is a property of concurrency control, which is instituted for the purpose of preventing race conditions. It is the requirement that one thread of execution never enters a critical section while a concurrent thread of execution is already accessing critical section, which refers to an interval of time during which a thread of execution accesses a shared resource, such as [Shared data objects, shared resources, shared memory].

Process (computing) Particular execution of a computer program

In computing, a process is the instance of a computer program that is being executed by one or many threads. It contains the program code and its activity. Depending on the operating system (OS), a process may be made up of multiple threads of execution that execute instructions concurrently.

Thread (computing) Smallest sequence of programmed instructions that can be managed independently by a scheduler

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. The multiple threads of a given process may be executed concurrently, 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.

Deadlock State in which members are blocking each other

In concurrent computing, a deadlock is a state in which each member of a group 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, where software and hardware locks are used to arbitrate shared resources and implement process synchronization.

Parallel computing Programming paradigm in which many processes are executed simultaneously

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 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 information technology and computer science, especially in the fields of computer programming, operating systems, multiprocessors, and databases, concurrency control ensures that correct results for concurrent operations are generated, while getting those results as quickly as possible.

In computer, 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.

In computer science, a lock or mutex is a synchronization primitive: a mechanism that enforces limits on access to a resource when there are many threads of execution. A lock is designed to enforce a mutual exclusion concurrency control policy, and with a variety of possible methods there exists multiple unique implementations for different applications.

In computer science, resource starvation is a problem encountered in concurrent computing where a process is perpetually denied necessary resources to process its work. Starvation may be caused by errors in a scheduling or mutual exclusion algorithm, but can also be caused by resource leaks, and can be intentionally caused via a denial-of-service attack such as a fork bomb.

In computer science, an algorithm is called non-blocking if failure or suspension of any thread cannot cause failure or suspension of another thread; for some operations, these algorithms provide a useful alternative to traditional blocking implementations. A non-blocking algorithm is lock-free if there is guaranteed system-wide progress, and wait-free if there is also guaranteed per-thread progress. "Non-blocking" was used as a synonym for "lock-free" in the literature until the introduction of obstruction-freedom in 2003.

In concurrent programming, concurrent accesses to shared resources can lead to unexpected or erroneous behavior, so parts of the program where the shared resource is accessed need to be protected in ways that avoid the concurrent access. This protected section is the critical section or critical region. It cannot be executed by more than one process at a time. Typically, the critical section accesses a shared resource, such as a data structure, a peripheral device, or a network connection, that would not operate correctly in the context of multiple concurrent accesses.

Thread pool

In computer programming, a thread pool is a software design pattern for achieving concurrency of execution in a computer program. Often also called a replicated workers or worker-crew model, a thread pool maintains multiple threads waiting for tasks to be allocated for concurrent execution by the supervising program. By maintaining a pool of threads, the model increases performance and avoids latency in execution due to frequent creation and destruction of threads for short-lived tasks. The number of available threads is tuned to the computing resources available to the program, such as a parallel task queue after completion of execution.

Concurrency (computer science) Ability of different parts or units of a program, algorithm, or problem to be executed out-of-order or in partial order, without affecting the final outcome

In computer science, concurrency is the ability of different parts or units of a program, algorithm, or problem to be executed out-of-order or at the same time simultaneously partial order, without affecting the final outcome. This allows for parallel execution of the concurrent units, which can significantly improve overall speed of the execution in multi-processor and multi-core systems. In more technical terms, concurrency refers to the decomposability of a program, algorithm, or problem into order-independent or partially-ordered components or units of computation.

In computing, preemption is the act of temporarily interrupting an executing task, with the intention of resuming it at a later time. This interrupt is done by an external scheduler with no assistance or cooperation from the task. This preemptive scheduler usually runs in the most privileged protection ring, meaning that interruption and resuming are considered highly secure actions. Such a change in the currently executing task of a processor is known as context switching.

Concurrent computing is a form of computing in which several computations are executed concurrently—during overlapping time periods—instead of sequentially—with one completing before the next starts.

In computer science, synchronization refers to one of two distinct but related concepts: synchronization of processes, and synchronization of data. Process synchronization refers to the idea that multiple processes are to join up or handshake at a certain point, in order to reach an agreement or commit to a certain sequence of action. Data synchronization refers to the idea of keeping multiple copies of a dataset in coherence with one another, or to maintain data integrity. Process synchronization primitives are commonly used to implement data synchronization.

In computing, a hang or freeze occurs when either a process or system ceases to respond to inputs. A typical example is when computer's graphical user interface no longer responds to the user typing on the keyboard or moving the mouse. The term covers a wide range of behaviors in both clients and servers, and is not limited to graphical user interface issues.

References

  1. ↑ Stallings, William (2004). Operating Systems: Internals and Design Principles (5th ed.). Prentice Hall.
  2. ↑ C++ and Beyond 2012: Herb Sutter - C++ Concurrency
  3. ↑ Go concurrency patterns by Rob Pike


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