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Concurrent computing is the concurrent (simultaneous) execution of multiple interacting computational tasks. In Computer science, concurrency is a properties of system in which several Computational processes are executing at the same time and potentially interacting These tasks may be implemented as separate programs, or as a set of processes or threads created by a single program. Computer programs (also software programs, or just programs) are instructions for a Computer. In computing a process is an instance of a Computer program that is being sequentially executed by a computer system that has the ability to run several computer A thread in Computer science is short for a thread of execution. The tasks may also be executing on a single processor, several processors in close proximity, or distributed across a network. Multiprocessing is the use of two or more central processing units (CPUs within a single computer system Distributed computing deals with Hardware and Software Systems containing more than one processing element or Storage element concurrent Concurrent computing is related to parallel computing, but focuses more on the interactions between tasks. Parallel computing is a form of computation in which many instructions are carried out simultaneously operating on the principle that large problems can often Correct sequencing of the interactions or communications between different tasks, and the coordination of access to resources that are shared between tasks, are key concerns during the design of concurrent computing systems. Pioneers in the field of concurrent computing include Edsger Dijkstra, Per Brinch Hansen, and C. A. R. Hoare. Edsger Wybe Dijkstra ( May 11, 1930 &ndash August 6, 2002; ˈɛtsxər ˈwibə ˈdɛɪkstra was a Dutch computer scientist Per Brinch Hansen (November 13 1938 - July 31 2007 was a Danish-American Computer scientist known for Concurrent programming theory Sir Charles Antony Richard Hoare ( Tony Hoare or CAR Hoare, born January 11, 1934) is a British computer scientist, probably

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Concurrent interaction and communication

In some concurrent computing systems communication between the concurrent components is hidden from the programmer (e. g. , by using futures), while in others it must be handled explicitly. In Computer science, futures and promises are closely related constructs used for synchronization in some concurrent programming languages Explicit communication can be divided into two classes:

Shared memory communication 
Concurrent components communicate by altering the contents of shared memory locations (exemplified by Java and C#). In Computing, shared memory is a memory that may be simultaneously accessed by multiple programs with an intent to provide communication among them or avoid redundant copies C# (pronounced C Sharp is a Multi-paradigm This style of concurrent programming usually requires the application of some form of locking (e. g. , mutexes (means mutual exclusion), semaphores, or monitors) to coordinate between threads. Mutual exclusion (often abbreviated to mutex) Algorithms are used in Concurrent programming to avoid the simultaneous use of a common resource such as a For other uses see Semaphore. A semaphore, in computer science is a protected Variable (an entity storing a value or Abstract A monitor is an approach to synchronize two or more computer tasks that use a shared resource usually a hardware device or a set of Variables With monitor-based
Message passing communication 
Concurrent components communicate by exchanging messages (exemplified by Erlang and occam). In Computer science, message passing is a form of communication used in Parallel computing, Object-oriented programming, and Interprocess communication Erlang is a general-purpose concurrent Programming language and Runtime system occam is a concurrent Programming language that builds on the Communicating Sequential Processes (CSP process algebra and shares many of its features The exchange of messages may be carried out asynchronously (sometimes referred to as "send and pray", although it is standard practice to resend messages that are not acknowledged as received), or may use a rendezvous style in which the sender blocks until the message is received. Message-passing concurrency tends to be far easier to reason about than shared-memory concurrency, and is typically considered a more robust, although slower, form of concurrent programming. A wide variety of mathematical theories for understanding and analyzing message-passing systems are available, including the Actor model, and various process calculi. In Computer science, the Actor model is a mathematical model of Concurrent computation that treats "actors" as the universal primitives of concurrent In Computer science, the process calculi (or process algebras) are a diverse family of related approaches to formally modelling Concurrent systems Process Message passing can be efficiently implemented on symmetric multiprocessors using shared coherent memory. In Computing, symmetric multiprocessing or SMP involves a Multiprocessor computer-architecture where two or more identical processors can connect to a single In computing Cache coherency (also cache coherence) refers to the integrity of data stored in local caches of a shared resource

Coordinating access to resources

One of the major issues in concurrent computing is preventing concurrent processes from interfering with each other. For example, consider the following algorithm for making withdrawals from a checking account represented by the shared resource balance:

1  bool withdraw(int withdrawal) {
2     if( balance > withdrawal ) {
3         balance = balance - withdrawal;
4         return true;
5     } 
6     return false;
7  }

Suppose balance=500, and two concurrent processes make the calls withdraw(300) and withdraw(350). If line 2 in both operations executes before line 3 both operations will find that balance > withdrawal evaluates to true, and execution will proceed to subtracting the withdrawal amount. However, since both processes perform their withdrawals, the total amount withdrawn will end up being more than the original balance. These sorts of problems with shared resources require the use of concurrency control, or non-blocking algorithms. In Computer science, especially in the fields of Computer programming (see also Concurrent programming, Parallel programming) Operating systems In Computer science, non-blocking synchronization ensures that threads competing for a shared resource do not have their execution indefinitely

Because concurrent systems rely on the use of shared resources (including communications mediums), concurrent computing in general requires the use of some form of arbiter somewhere in the implementation to mediate access to these resources. Metastability in electronics is the ability of a non-equilibrium electronic state to persist for a long (and theoretically unlimited period of time (see Asynchronous circuit

Unfortunately, while many solutions exist to the problem of a conflict over one resource, many of those "solutions" have their own concurrency problems such as deadlock when more than one resource is involved. In Computer science, concurrency is a properties of system in which several Computational processes are executing at the same time and potentially interacting A deadlock is a situation wherein two or more competing actions are waiting for the other to finish and thus neither ever does

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Concurrent programming languages

Concurrent programming languages are programming languages that use language constructs for concurrency. A programming language is an Artificial language that can be used to write programs which control the behavior of a machine particularly a Computer. In Computer science, concurrency is a properties of system in which several Computational processes are executing at the same time and potentially interacting These constructs may involve multi-threading, support for distributed computing, message passing, shared resources (including shared memory) or futures (known also as promises). A thread in Computer science is short for a thread of execution. Distributed computing deals with Hardware and Software Systems containing more than one processing element or Storage element concurrent In Computer science, message passing is a form of communication used in Parallel computing, Object-oriented programming, and Interprocess communication Sharing is the joint use of a resource or space In its narrow sense it refers to joint or alternating use of an inherently finite good such as a common pasture or a Timeshared A Parallel Random Access Machine ( PRAM) is an Abstract machine for designing the Algorithms applicable to Parallel computers It eliminates the In Computer science, futures and promises are closely related constructs used for synchronization in some concurrent programming languages

Today, the most commonly used programming languages that have specific constructs for concurrency are Java and C#. C# (pronounced C Sharp is a Multi-paradigm Both of these languages fundamentally use a shared-memory concurrency model, with locking provided by monitors (although message-passing models can and have been implemented on top of the underlying shared-memory model). A monitor is an approach to synchronize two or more computer tasks that use a shared resource usually a hardware device or a set of Variables With monitor-based Of the languages that use a message-passing concurrency model, Erlang is probably the most widely used in industry at present. Erlang is a general-purpose concurrent Programming language and Runtime system

Many concurrent programming languages have been developed more as research languages (e. g. Pict) rather than as languages for production use. Pict is a statically typed Programming language based on the Pi-calculus, one of very few languages to do this However, languages such as Erlang, Limbo, and occam have seen industrial use at various times in the last 20 years. Languages in which concurrency plays an important role include:

Many other languages provide support for concurrency in the form of libraries (on level roughly comparable with the above list). Oz is a Multiparadigm programming language, developed in the Programming Systems Lab at Saarland University. The Mozart Programming System is a Multiplatform implementation of the Oz Programming language developed by the Mozart Consortium. In computing cross-platform (also known as multi-platform) is a term used to refer to Computer software or computing methods and concepts that are implemented Pict is a statically typed Programming language based on the Pi-calculus, one of very few languages to do this In Theoretical computer science, the \pi-calculus is a Process calculus originally developed by Robin Milner, Joachim Parrow and The SALSA programming language ( S imple A ctor L anguage S ystem and A rchitecture is an actor-oriented programming language Scala ( Scalable Language) is a multi-paradigm Programming language designed to integrate features of Object-oriented programming and SR (short for Synchronizing Resources) is a Programming language designed for Concurrent programming.

Models of concurrency

There are several models of concurrent computing, which can be used to understand and analyze concurrent systems. These models include:

See also

Bibliography

External links

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