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In software engineering, "programming in the large" and "programming in the small" refer to two different aspects of writing software. "Programming in the large" means designing a larger system as a composition of smaller parts, and "programming in the small" means creating those smaller parts by writing lines of code in a programming language.
An Introduction to Software Architecture [1] describes it as such "We are still far from having a well-accepted taxonomy of such architectural paradigms, let alone a fully-developed theory of software architecture. But we can now clearly identify a number of architectural patterns, or styles, that currently form the basic repertoire of a ...
His design was funded by the US Air Force, which was the earliest SIMD parallel-computing effort, ILLIAC IV. [79] The key to its design was a fairly high parallelism, with up to 256 processors, which allowed the machine to work on large datasets in what would later be known as vector processing .
In computing, a parallel programming model is an abstraction of parallel computer architecture, with which it is convenient to express algorithms and their composition in programs. The value of a programming model can be judged on its generality : how well a range of different problems can be expressed for a variety of different architectures ...
An architectural pattern is a general, reusable resolution to a commonly occurring problem in software architecture within a given context. [1] The architectural patterns address various issues in software engineering , such as computer hardware performance limitations, high availability and minimization of a business risk .
The Practical Guide to Structured Systems Design. New York: Yourdon Press. ISBN 978-8-12031482-5. Standard Glossary of Software Engineering Terminology. New York: IEEE. 1990. ISBN 0-7381-0391-8. 610.12_1990. "Curriculum for Certified Professional for Software Architecture (CPSA) - Foundation Level" (PDF). 3.01. International Software ...
In parallel computing, granularity (or grain size) of a task is a measure of the amount of work (or computation) which is performed by that task. [1]Another definition of granularity takes into account the communication overhead between multiple processors or processing elements.
The parallel random-access machine [10] The actor model; Computational bridging models such as the bulk synchronous parallel (BSP) model; Petri nets; Process calculi. Calculus of communicating systems (CCS) Communicating sequential processes (CSP) model; π-calculus; Tuple spaces, e.g., Linda; Simple Concurrent Object-Oriented Programming (SCOOP)
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