With parallel processing the situation is entirely different. A parallel computer is one that con... more With parallel processing the situation is entirely different. A parallel computer is one that consists of a collection of processing units, or processors, that cooperate to solve a problem by working simultaneously on different parts of that problem. The number of processors used can range from a few tens to several millions. As a result, the time required to solve the problem by a traditional uniprocessor computer is significantly reduced. This approach is attractive for a number of reasons. First, for many computational problems, the natural solution is a parallel one. Second, the cost and size of computer components have declined so sharply in recent years that parallel computers with a large number of processors have become feasible. And, third, it is possible in parallel processing to select the parallel architecture that is best suited to solve the problem or class of problems under consideration. Indeed, architects of parallel computers have the freedom to decide how many processors are to be used, how powerful these should be, what interconnection network links them to one another, whether they share a common memory, to what extent their operations are to be carried out synchronously, and a host of other issues. This wide range of choices has been reflected by the many theoretical models of parallel computation proposed as well as by the several parallel computers that were actually built.
With parallel processing the situation is entirely different. A parallel computer is one that con... more With parallel processing the situation is entirely different. A parallel computer is one that consists of a collection of processing units, or processors, that cooperate to solve a problem by working simultaneously on different parts of that problem. The number of processors used can range from a few tens to several millions. As a result, the time required to solve the problem by a traditional uniprocessor computer is significantly reduced. This approach is attractive for a number of reasons. First, for many computational problems, the natural solution is a parallel one. Second, the cost and size of computer components have declined so sharply in recent years that parallel computers with a large number of processors have become feasible. And, third, it is possible in parallel processing to select the parallel architecture that is best suited to solve the problem or class of problems under consideration. Indeed, architects of parallel computers have the freedom to decide how many processors are to be used, how powerful these should be, what interconnection network links them to one another, whether they share a common memory, to what extent their operations are to be carried out synchronously, and a host of other issues. This wide range of choices has been reflected by the many theoretical models of parallel computation proposed as well as by the several parallel computers that were actually built.
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