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MultiLisp
MultiLisp is a functional programming language, a dialect of the language Lisp, and of its dialect Scheme, extended with constructs for parallel computing execution and shared memory. These extensions involve side effects, rendering MultiLisp nondeterministic. Along with its parallel-programming extensions, MultiLisp also had some unusual garbage collection and task scheduling algorithms. Like Scheme, MultiLisp was optimized for symbolic computing. Unlike some parallel programming languages, MultiLisp incorporated constructs for causing side effects and for explicitly introducing parallelism. It was designed by Robert H. Halstead Jr., in the early 1980s for use on the 32-processor Concert multiprocessor then being developed at Massachusetts Institute of Technology (MIT) and implemented in Interlisp. It influenced the development of the Scheme dialects Gambit, and Interlisp-VAX. PCALL and FUTURE MultiLisp achieves parallelism with the PCALL macro, where (PCALL Fun A B C ...) is ...
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Future (programming)
In computer science, future, promise, delay, and deferred refer to constructs used for synchronizing program execution in some concurrent programming languages. They describe an object that acts as a proxy for a result that is initially unknown, usually because the computation of its value is not yet complete. The term ''promise'' was proposed in 1976 by Daniel P. Friedman and David Wise, and Peter Hibbard called it ''eventual''. A somewhat similar concept ''future'' was introduced in 1977 in a paper by Henry Baker and Carl Hewitt. The terms ''future'', ''promise'', ''delay'', and ''deferred'' are often used interchangeably, although some differences in usage between ''future'' and ''promise'' are treated below. Specifically, when usage is distinguished, a future is a ''read-only'' placeholder view of a variable, while a promise is a writable, single assignment container which sets the value of the future. Notably, a future may be defined without specifying which specific pro ...
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Concurrent Computing
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. This is a property of a system—whether a program, computer, or a network—where there is a separate execution point or "thread of control" for each process. A ''concurrent system'' is one where a computation can advance without waiting for all other computations to complete. Concurrent computing is a form of modular programming. In its paradigm an overall computation is factored into subcomputations that may be executed concurrently. Pioneers in the field of concurrent computing include Edsger Dijkstra, Per Brinch Hansen, and C.A.R. Hoare. Introduction The concept of concurrent computing is frequently confused with the related but distinct concept of parallel computing, Pike, Rob (2012-01-11). "Concurrency is not Parallelism". ''Waza conference'', 11 January ...
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Scheme (programming Language)
Scheme is a dialect of the Lisp family of programming languages. Scheme was created during the 1970s at the MIT AI Lab and released by its developers, Guy L. Steele and Gerald Jay Sussman, via a series of memos now known as the Lambda Papers. It was the first dialect of Lisp to choose lexical scope and the first to require implementations to perform tail-call optimization, giving stronger support for functional programming and associated techniques such as recursive algorithms. It was also one of the first programming languages to support first-class continuations. It had a significant influence on the effort that led to the development of Common Lisp.Common LISP: The Language, 2nd Ed., Guy L. Steele Jr. Digital Press; 1981. . "Common Lisp is a new dialect of Lisp, a successor to MacLisp, influenced strongly by ZetaLisp and to some extent by Scheme and InterLisp." The Scheme language is standardized in the official IEEE standard1178-1990 (Reaff 2008) IEEE Standard for the S ...
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Multi-paradigm Programming Language
Programming paradigms are a way to classify programming languages based on their features. Languages can be classified into multiple paradigms. Some paradigms are concerned mainly with implications for the execution model of the language, such as allowing side effects, or whether the sequence of operations is defined by the execution model. Other paradigms are concerned mainly with the way that code is organized, such as grouping a code into units along with the state that is modified by the code. Yet others are concerned mainly with the style of syntax and grammar. Common programming paradigms include: * imperative in which the programmer instructs the machine how to change its state, ** procedural which groups instructions into procedures, ** object-oriented which groups instructions with the part of the state they operate on, * declarative in which the programmer merely declares properties of the desired result, but not how to compute it ** functional in which the de ...
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Parallel Computing
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.S.V. Adve ''et al.'' (November 2008)"Parallel Computing Research at Illinois: The UPCRC Agenda" (PDF). Parallel@Illinois, University of Illinois at Urbana-Champaign. "The main techniques for these performance benefits—increased clock frequency and smarter but increasingly complex architectures—are now hitting the so-called power wall. The computer industry has accepted that future performance increases must largely come from increasing the number of processors (or cores) on a die, rather than m ...
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Speculative Evaluation
Speculative execution is an optimization technique where a computer system performs some task that may not be needed. Work is done before it is known whether it is actually needed, so as to prevent a delay that would have to be incurred by doing the work after it is known that it is needed. If it turns out the work was not needed after all, most changes made by the work are reverted and the results are ignored. The objective is to provide more concurrency if extra resources are available. This approach is employed in a variety of areas, including branch prediction in pipelined processors, value prediction for exploiting value locality, prefetching memory and files, and optimistic concurrency control in database systems.Lazy and Speculative Execution


Cons
In computer programming, ( or ) is a fundamental function in most dialects of the Lisp programming language. ''constructs'' memory objects which hold two values or pointers to two values. These objects are referred to as (cons) cells, conses, non-atomic s-expressions ("NATSes"), or (cons) pairs. In Lisp jargon, the expression "to cons ''x'' onto ''y''" means to construct a new object with (cons ''x'' ''y''). The resulting pair has a left half, referred to as the (the first element, or ''contents of the address part of register''), and a right half, referred to as the (the second element, or ''contents of the decrement part of register''). It is loosely related to the object-oriented notion of a constructor, which creates a new object given arguments, and more closely related to the constructor function of an algebraic data type system. The word "cons" and expressions like "to cons onto" are also part of a more general functional programming jargon. Sometimes operators tha ...
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Lazy Evaluation
In programming language theory, lazy evaluation, or call-by-need, is an evaluation strategy which delays the evaluation of an expression until its value is needed (non-strict evaluation) and which also avoids repeated evaluations (sharing). The benefits of lazy evaluation include: * The ability to define control flow (structures) as abstractions instead of primitives. * The ability to define potentially infinite data structures. This allows for more straightforward implementation of some algorithms. * The ability to define partially-defined data structures where some elements are errors. This allows for rapid prototyping. Lazy evaluation is often combined with memoization, as described in Jon Bentley's ''Writing Efficient Programs''. After a function's value is computed for that parameter or set of parameters, the result is stored in a lookup table that is indexed by the values of those parameters; the next time the function is called, the table is consulted to determine whe ...
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Fork (system Call)
In computing, particularly in the context of the Unix operating system and its workalikes, fork is an operation whereby a process creates a copy of itself. It is an interface which is required for compliance with the POSIX and Single UNIX Specification standards. It is usually implemented as a C Standard Library (libc) wrapper to the fork, clone, or other system calls of the kernel. Fork is the primary method of process creation on Unix-like operating systems. Overview In multitasking operating systems, processes (running programs) need a way to create new processes, e.g. to run other programs. Fork and its variants are typically the only way of doing so in Unix-like systems. For a process to start the execution of a different program, it first forks to create a copy of itself. Then, the copy, called the "child process", calls the exec system call to overlay itself with the other program: it ceases execution of its former program in favor of the other. The fork operation crea ...
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Parameter (computer Programming)
In computer programming, a parameter or a formal argument is a special kind of variable used in a subroutine to refer to one of the pieces of data provided as input to the subroutine. These pieces of data are the values of the arguments (often called ''actual arguments'' or ''actual parameters'') with which the subroutine is going to be called/invoked. An ordered list of parameters is usually included in the definition of a subroutine, so that, each time the subroutine is called, its arguments for that call are evaluated, and the resulting values can be assigned to the corresponding parameters. Unlike ''argument'' in usual mathematical usage, the ''argument'' in computer science is the actual input expression passed/supplied to a function, procedure, or routine in the invocation/call statement, whereas the ''parameter'' is the variable inside the implementation of the subroutine. For example, if one defines the add subroutine as def add(x, y): return x + y, then x, y are paramet ...
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Macro (computer Science)
In computer programming, a macro (short for "macro instruction"; ) is a rule or pattern that specifies how a certain input should be mapped to a replacement output. Applying a macro to an input is known as macro expansion. The input and output may be a sequence of lexical tokens or characters, or a syntax tree. Character macros are supported in software applications to make it easy to invoke common command sequences. Token and tree macros are supported in some programming languages to enable code reuse or to extend the language, sometimes for domain-specific languages. Macros are used to make a sequence of computing instructions available to the programmer as a single program statement, making the programming task less tedious and less error-prone. (Thus, they are called "macros" because a "big" block of code can be expanded from a "small" sequence of characters.) Macros often allow positional or keyword parameters that dictate what the conditional assembler program generates ...
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Computer Algebra
In mathematics and computer science, computer algebra, also called symbolic computation or algebraic computation, is a scientific area that refers to the study and development of algorithms and software for manipulating mathematical expressions and other mathematical objects. Although computer algebra could be considered a subfield of scientific computing, they are generally considered as distinct fields because scientific computing is usually based on numerical computation with approximate floating point numbers, while symbolic computation emphasizes ''exact'' computation with expressions containing variables that have no given value and are manipulated as symbols. Software applications that perform symbolic calculations are called ''computer algebra systems'', with the term ''system'' alluding to the complexity of the main applications that include, at least, a method to represent mathematical data in a computer, a user programming language (usually different from the languag ...
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