Algorithm comparison and benchmarking using a parallel spectra transform shallow water model
- Oak Ridge National Lab., TN (United States)
- Argonne National Lab., IL (United States)
In recent years, a number of computer vendors have produced supercomputers based on a massively parallel processing (MPP) architecture. These computers have been shown to be competitive in performance with conventional vector supercomputers for some applications. As spectral weather and climate models are heavy users of vector supercomputers, it is interesting to determine how these models perform on MPPS, and which MPPs are best suited to the execution of spectral models. The benchmarking of MPPs is complicated by the fact that different algorithms may be more efficient on different architectures. Hence, a comprehensive benchmarking effort must answer two related questions: which algorithm is most efficient on each computer and how do the most efficient algorithms compare on different computers. In general, these are difficult questions to answer because of the high cost associated with implementing and evaluating a range of different parallel algorithms on each MPP platform.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC05-84OR21400
- OSTI ID:
- 35370
- Report Number(s):
- CONF-9411178-2; ON: DE95009124; TRN: 95:003260
- Resource Relation:
- Conference: 6. workshop on use of parallel processors in meterology, Reading (United Kingdom), 24 Nov 1994; Other Information: PBD: [1995]
- Country of Publication:
- United States
- Language:
- English
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