Abstract
This paper studies the behavior of scientific applications running on distributed memory parallel computers. Our goal is to quantify the floating point, memory, I/O, and communication requirements of highly parallel scientific applications that perform explicit communication. In addition to quantifying these requirements for fixed problem sizes and numbers of processors, we develop analytical models for the effects of changing the problem size and the degree of parallelism for several of the applications.
The contribution of our paper is that it provides quantitative data about real parallel scientific applications in a manner that is largely independent of the specific machine on which the application was run. Such data, which are clearly very valuable to an architect who is designing a new parallel computer, were not previously available. For example, the majority of research papers in interconnection networks have used simulated communication loads consisting of fixed-size messages. Our data, which show that using such simulated loads is unrealistic, can be used to generate more realistic communication loads.
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Cypher, R., Ho, A., Konstantinidou, S. et al. A quantitative study of parallel scientific applications with explicit communication. J Supercomput 10, 5–24 (1996). https://doi.org/10.1007/BF00128097
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DOI: https://doi.org/10.1007/BF00128097