Abstract
As parallel computers and parallel programming environments are used widely, people try to seek a synthetical metric to evaluate how problem sizes and system sizes influence the performance of parallel computers and parallel algorithms. Scalability is a try at this aspect. Scalability has been widely used in practice to describe how system sizes and problem sizes influence the performance of parallel computers and algorithms. It is so very important that manufacturers of parallel computers all claim that their parallel computers are scalable, and give their appropriate scaling ranges. For example, Intel Paragon XP/S was designed to scale between 16 and 1024 processors. IBM SP2 scaled over a range of 256 processors. The Cray Y-MP series scaled over a range of 16 processors, and Cray T3D was designed to scale between 16 and 1024 processors. The CM-2 scaling range is 8K to 64K processing elements, and the CM-5 scaling range is 1024 to 16K computers [12].
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Wu, X. (1999). Scalability. In: Performance Evaluation, Prediction and Visualization of Parallel Systems. The Kluwer International Series on Asian Studies in Computer and Information Science, vol 4. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5147-8_3
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