Lazy evaluation

A powerful mechanism used in functional programming is the notion of higher-order functions. Functions are higher-order when they can take other functions as arguments, and/or return functions as results. (The differential operator in calculus is a common example of a function that maps a function to a function.) Higher-order functions are closely related to first-class functions, in that higher-order functions and first-class functions both allow functions as arguments and results of other functions. The distinction between the two i ...

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Functional programming, Functional programming - History, Functional programming - Higher-order functions, Functional programming - Comparison with imperative programming, Functional programming - Pure functions, Functional programming - Monads, Functional programming - Expansion of functional programming, Functional programming - Speed and space considerations, Functional programming - Functional languages

Read more here: » Functional programming: Encyclopedia II - Functional programming - Higher-order functions

Functional programming can be contrasted with imperative programming. Functional programming appears to be missing several constructs often (though incorrectly) considered essential to an imperative language such as C or Pascal. For example, in strict functional programming, there is no explicit memory allocation and no explicit variable assignment. However, these operations occur automatically when a function is invoked: memory allocation occurs to create space for the parameters and the return value, and assignment occurs to copy the param ...

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Functional programming, Functional programming - Introduction, Functional programming - History, Functional programming - Comparison with imperative programming, Functional programming - Functional programming languages, Functional programming - Higher-order functions, Functional programming - Speed and space considerations, Functional programming - Functional languages

Read more here: » Functional programming: Encyclopedia II - Functional programming - Comparison with imperative programming

The oldest example of a functional language is Lisp, though neither the original LISP nor modern Lisps such as Common Lisp are pure-functional. Lisp variants include Logo, Scheme, Dylan. The modern canonical examples are Haskell and members of the ML family including SML and OCaml. Others include Erlang, Clean, and Miranda. A third type of a commonly used functional language is Xslt. Another subset is the mathematics languages Maple and Mathematica. Some computer languages, for example Tcl, Perl, Python & Ruby, can also be used in a functional style, ...

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Functional programming, Functional programming - Introduction, Functional programming - History, Functional programming - Comparison with imperative programming, Functional programming - Functional programming languages, Functional programming - Higher-order functions, Functional programming - Speed and space considerations, Functional programming - Functional languages

Read more here: » Functional programming: Encyclopedia II - Functional programming - Functional languages

Coroutines are more generic than subroutines. The start of a subroutine is the only point of entry; the start of a coroutine is the first point of entry, and places within a coroutine following returns (yields) are subsequent points of entry. Subroutines can return only once; in contrast, coroutines can return (yield) several times. The lifespan of subroutines is dictated by last in, first out (the last subroutine called is the first to return); in contrast, the lifespan ...

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Coroutine, Coroutine - Brief comparison and example, Coroutine - Detailed comparison, Coroutine - Common uses of coroutines, Coroutine - Programming languages supporting coroutines, Coroutine - Coroutine alternatives and implementations, Coroutine - Implementations for C, Coroutine - Implementations for Python, Coroutine - Implementations for Ruby

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A dataflow network is a network of concurrently executing processes or automata that can communicate by sending data over channels (see message passing.) Kahn process networks, named after one of the pioneers of dataflow networks, are a particularly important class of such networks. In a Kahn process network the processes are determinate. This implies that they satisfy the so-called Kahn's principle, which roughly speaking states that, each determinate process computes a continuous function from input streams to o ...

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Dataflow, Dataflow - Software architecture, Dataflow - Diagrams, Dataflow - Concurrency, Dataflow - Hardware architecture

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Lambda calculus, invented by Alonzo Church in the 1930s, provides a theoretical framework for describing functions and their evaluation. Though it is a mathematical abstraction rather than a programming language, lambda calculus forms the basis of almost all functional programming languages today. The first computer-based functional programming language was Information Processing Language (IPL), developed by Newell, Shaw, and Simon at RAND Corporation for the JOHNNIAC computer in the mid-1950s. A much-improved functional programming l ...

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Functional programming, Functional programming - History, Functional programming - Higher-order functions, Functional programming - Comparison with imperative programming, Functional programming - Pure functions, Functional programming - Monads, Functional programming - Expansion of functional programming, Functional programming - Speed and space considerations, Functional programming - Functional languages

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Dataflow is a software architecture based on the idea that changing the value of a variable should automatically force recalculation of the values of other variables. Dataflow programming languages embody these principles, with Spreadsheets perhaps the most widespread embodiment of dataflow. For example, in a spreadsheet you can specify a cell formula which depends on other cells; then when any of those cells is updated the first cell's value is automatically recalculated. It's possible for one change to initiate a whole sequence of changes, if one cell depends on another ...

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Dataflow, Dataflow - Software architecture, Dataflow - Diagrams, Dataflow - Concurrency, Dataflow - Hardware architecture

Read more here: » Dataflow: Encyclopedia II - Dataflow - Software architecture

When viewed in a set-theoretic light, currying becomes the theorem that the set of functions from to A, and the set (AB)C of functions from C to the set of functions from B to A, are isomorphic. In other words, currying is the statement that product and Hom are adjoint functors; this is the key ...

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Currying, Currying - Examples, Currying - Mathematical view

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Since coroutines can have more points of entry and exit than subroutines, it is possible to implement any subroutine as a coroutine. Indeed, as Knuth describes it, "subroutines are special cases of ... coroutines." Each time a subroutine is called (invoked), execution starts at the beginning of the invoked subroutine. Likewise, the first time a coroutine is invoked, execution starts at the beginning of the coroutine; however, each subsequent time a coroutine is invoked, execution resumes following the p ...

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Coroutine, Coroutine - Brief comparison and example, Coroutine - Detailed comparison, Coroutine - Common uses of coroutines, Coroutine - Programming languages supporting coroutines, Coroutine - Coroutine alternatives and implementations, Coroutine - Implementations for C, Coroutine - Implementations for Python, Coroutine - Implementations for Ruby

Read more here: » Coroutine: Encyclopedia II - Coroutine - Detailed comparison

The term parallel processor is sometimes used for a computer with more than one processor, available for parallel processing. Systems with thousands of such processors are known as massively parallel. The recent multicore processors are also ideal for to build up parallel computing systems. There are many different kinds of parallel computers (or "parallel processors"). They are distinguished by the kind of interconnection between processors (known as "processing elements" or PEs) and between processors and memories. Fly ...

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Parallel computing, Parallel computing - Parallel computing systems, Parallel computing - Performance vs. cost, Parallel computing - Algorithms, Parallel computing - Inter-thread communication, Parallel computing - Parallel programming, Parallel computing - Parallel programming models, Parallel computing - Topics in parallel computing

Read more here: » Parallel computing: Encyclopedia II - Parallel computing - Parallel computing systems

The term parallel processor is sometimes used for a computer with more than one processor, available for parallel processing. Systems with thousands of such processors are known as massively parallel. The recent multicore processors are also ideal for to build up parallel computing systems. There are many different kinds of parallel computers (or "parallel processors"). They are distinguished by the kind of interconnection between processors (known as "processing elements" or PEs) and between processors and memories. Fly ...

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Parallel computing, Parallel computing - Parallel computing systems, Parallel computing - Performance vs. cost, Parallel computing - Algorithms, Parallel computing - Inter-thread communication, Parallel computing - Parallel software, Parallel computing - Parallel programming models, Parallel computing - Topics in parallel computing

Read more here: » Parallel computing: Encyclopedia II - Parallel computing - Parallel computing systems

A huge number of software systems have been designed for programming parallel computers, both at the operating system and programming language level. These systems must provide mechanisms for partitioning the overall problem into separate tasks and allocating tasks to processors. Such mechanisms may provide either implicit parallelism -- the system (the compiler or some other program) partitions the problem and allocates tasks to processors automatically (also called automatic parallelizing compilers) -- or explicit parallelism where the pro ...

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Parallel computing, Parallel computing - Parallel computing systems, Parallel computing - Performance vs. cost, Parallel computing - Algorithms, Parallel computing - Inter-thread communication, Parallel computing - Parallel programming, Parallel computing - Parallel programming models, Parallel computing - Topics in parallel computing

Read more here: » Parallel computing: Encyclopedia II - Parallel computing - Parallel programming

Main article: Parallel programming model A parallel programming model is a set of software technologies to express parallel algorithms and match applications with the underlying parallel systems. It encloses the areas of applications, languages, compilers, libraries, communication systems, and parallel I/O. People have to choose a proper parallel programming model or a form of mixture of the ...

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Parallel computing, Parallel computing - Parallel computing systems, Parallel computing - Performance vs. cost, Parallel computing - Algorithms, Parallel computing - Inter-thread communication, Parallel computing - Parallel programming, Parallel computing - Parallel programming models, Parallel computing - Topics in parallel computing

Read more here: » Parallel computing: Encyclopedia II - Parallel computing - Parallel programming models

Generic: Automatic parallelization Parallel algorithm Finding parallelism in problems and algorithms Cellular automaton Computer science topics: Lazy evaluation vs strict evaluation Complexity class NC Communicating sequential processes Dataflow architecture Parallel graph reduction Practical problems: Parallel computer interconnects Parallel computer I/O Reliability problems in large systems Programming languages/models: OpenMPSee also:

Parallel computing, Parallel computing - Parallel computing systems, Parallel computing - Performance vs. cost, Parallel computing - Algorithms, Parallel computing - Inter-thread communication, Parallel computing - Parallel programming, Parallel computing - Parallel programming models, Parallel computing - Topics in parallel computing

Read more here: » Parallel computing: Encyclopedia II - Parallel computing - Topics in parallel computing

It should not be imagined that successful parallel computing is a matter of obtaining the required hardware and connecting it suitably. The difficulty of cooperative problem solving is aptly demonstrated by the following dubious reasoning: If it takes one man one minute to dig a post-hole then sixty men can dig it in one second. In practice, linear speedup (i.e., speedup proportional to the number of processors) is very difficult to achieve. This is because many algorithms are essentially sequential in ...

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Parallel computing, Parallel computing - Parallel computing systems, Parallel computing - Performance vs. cost, Parallel computing - Algorithms, Parallel computing - Inter-thread communication, Parallel computing - Parallel software, Parallel computing - Parallel programming models, Parallel computing - Topics in parallel computing

Read more here: » Parallel computing: Encyclopedia II - Parallel computing - Algorithms

Parallel computers are theoretically modeled as Parallel Random Access Machines (PRAMs). The PRAM model ignores the cost of interconnection between the constituent computing units, but is nevertheless very useful in providing upper bounds on the parallel solvability of many problems. In reality the interconnection plays a significant role. The processors may either communicate in order to be able to cooperate in solving a problem or they may run completely independently, possibly under the control of another processor which distributes work t ...

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Parallel computing, Parallel computing - Parallel computing systems, Parallel computing - Performance vs. cost, Parallel computing - Algorithms, Parallel computing - Inter-thread communication, Parallel computing - Parallel programming, Parallel computing - Parallel programming models, Parallel computing - Topics in parallel computing

Read more here: » Parallel computing: Encyclopedia II - Parallel computing - Inter-thread communication

It should not be imagined that successful parallel computing is a matter of obtaining the required hardware and connecting it suitably. The difficulty of cooperative problem solving is aptly demonstrated by the following dubious reasoning: If it takes one man one minute to dig a post-hole then sixty men can dig it in one second. In practice, linear speedup (i.e., speedup proportional to the number of processors) is very difficult to achieve. This is because many algorithms are essentially sequential in ...

See also:

Parallel computing, Parallel computing - Parallel computing systems, Parallel computing - Performance vs. cost, Parallel computing - Algorithms, Parallel computing - Inter-thread communication, Parallel computing - Parallel programming, Parallel computing - Parallel programming models, Parallel computing - Topics in parallel computing

Read more here: » Parallel computing: Encyclopedia II - Parallel computing - Algorithms

Main article: Parallel programming model A parallel programming model is a set of software technologies to express parallel algorithms and match applications with the underlying parallel systems. It encloses the areas of applications, languages, compilers, libraries, communication systems, and parallel I/O. People have to choose a proper parallel programming model or a form of mixture of the ...

See also:

Parallel computing, Parallel computing - Parallel computing systems, Parallel computing - Performance vs. cost, Parallel computing - Algorithms, Parallel computing - Inter-thread communication, Parallel computing - Parallel software, Parallel computing - Parallel programming models, Parallel computing - Topics in parallel computing

Read more here: » Parallel computing: Encyclopedia II - Parallel computing - Parallel programming models

Generic: Automatic parallelization Parallel programming Parallel algorithm Finding parallelism in problems and algorithms Cellular automaton Computer science topics: Lazy evaluation vs strict evaluation Complexity class NC Communicating sequential processes Dataflow architecture Parallel graph reduction Practical problems: Parallel computer interconnects Parallel ...

See also:

Parallel computing, Parallel computing - Parallel computing systems, Parallel computing - Performance vs. cost, Parallel computing - Algorithms, Parallel computing - Inter-thread communication, Parallel computing - Parallel software, Parallel computing - Parallel programming models, Parallel computing - Topics in parallel computing

Read more here: » Parallel computing: Encyclopedia II - Parallel computing - Topics in parallel computing

Parallel computers are theoretically modeled as Parallel Random Access Machines (PRAMs). The PRAM model ignores the cost of interconnection between the constituent computing units, but is nevertheless very useful in providing upper bounds on the parallel solvability of many problems. In reality the interconnection plays a significant role. The processors may either communicate in order to be able to cooperate in solving a problem or they may run completely independently, possibly under the control of another processor which distributes work t ...

See also:

Parallel computing, Parallel computing - Parallel computing systems, Parallel computing - Performance vs. cost, Parallel computing - Algorithms, Parallel computing - Inter-thread communication, Parallel computing - Parallel software, Parallel computing - Parallel programming models, Parallel computing - Topics in parallel computing

Read more here: » Parallel computing: Encyclopedia II - Parallel computing - Inter-thread communication

A huge number of software systems have been designed for programming parallel computers, both at the operating system and programming language level. These systems must provide mechanisms for partitioning the overall problem into separate tasks and allocating tasks to processors. Such mechanisms may provide either implicit parallelism -- the system (the compiler or some other program) partitions the problem and allocates tasks to processors automatically (also called automatic parallelizing compilers) -- or explicit parallelism where the pro ...

See also:

Parallel computing, Parallel computing - Parallel computing systems, Parallel computing - Performance vs. cost, Parallel computing - Algorithms, Parallel computing - Inter-thread communication, Parallel computing - Parallel software, Parallel computing - Parallel programming models, Parallel computing - Topics in parallel computing

Read more here: » Parallel computing: Encyclopedia II - Parallel computing - Parallel software