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Cost efficiency

Cost efficiency (or cost optimality), in the context of parallel computeralgorithms, refers to a measure of how effectively parallel computing can be used to solve a particular problem. A parallel algorithm is considered cost efficient if its asymptotic running time multiplied by the number of processing units involved in the computation is comparable to the running time of the best sequential algorithm.

Parallel computingParallel computingLarge supercomputers such as IBM's Blue Gene/P are designed to heavily exploit parallelism.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.AlgorithmAlgorithmIn mathematics and computer science, an algorithm () is any well-defined set of instructions that when followed terminates after a finite number of steps that comprise a solution to a given computational problem. Advanced algorithms may utilize loops and involve many conditionals that decide the next step based on the inputs provided, resulting in long sequences of steps before halting, but all algorithms terminate by definition.Human servicesHuman servicesHuman services is for people who need interdisciplinary field of study with the objective of meeting human needs through an applied knowledge base, focusing on prevention as well as remediation of problems, and maintaining a commitment to improving the overall quality of life of service populations The process involves the study of social technologies (practice methods, models, and theories), service technologies (programs, organizations, and systems), and scientific innovations designed to ameliorate problems and enhance the quality of life of individuals, families and communities to improve the delivery of service with better coordination, accessibility and accountability.Big O notationBig O notationDescribes approximate behavior of a functionBig O notation is a mathematical notation that describes the approximate size of a function on a domain. Big O is a member of a family of notations invented by the German mathematicians Paul Bachmann and Edmund Landau and expanded by others, collectively called Bachmann–Landau notation. The letter O stands for Ordnung, that is, the order of approximation.

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