Owenson, A. M. B (2020) Towards the use of mini-applications in performance prediction and optimisation of production codes. PhD thesis, University of Warwick.

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Abstract

Maintaining the performance of large scientific codes is a difficult task. To aid in this task a number of mini-applications have been developed that are more tract able to analyse than large-scale production codes, while retaining the performance characteristics of them. These “mini-apps” also enable faster hardware evaluation, and for sensitive commercial codes allow evaluation of code and system changes outside of access approval processes.

Techniques for validating the representativeness of a mini-application to a target code are ultimately qualitative, requiring the researcher to decide whether the similarity is strong enough for the mini-application to be trusted to provide accurate predictions of the target performance. Little consideration is given to the sensitivity of those predictions to the few differences between the mini-application and its target, how those potentially-minor static differences may lead to each code responding very differently to a change in the computing environment.

An existing mini-application, ‘Mini-HYDRA’, of a production CFD simulation code is reviewed. Arithmetic differences lead to divergence in intra-node performance scaling, so the developers had removed some arithmetic from Mini-HYDRA, but this breaks the simulation so limits numerical research. This work restores the arithmetic, repeating validation for similar performance scaling, achieving similar intra-node scaling performance whilst neither are memory-bound. MPI strong scaling functionality is also added, achieving very similar multi-node scaling performance.

The arithmetic restoration inevitably leads to different memory-bounds, and also different and varied responses to changes in processor architecture or instruction set. A performance model is developed that predicts this difference in response, in terms of the arithmetic differences. It is supplemented by a new benchmark that measures the memory-bound of CFD loops. Together, they predict the strong scaling performance of a production ‘target’ code, with a mean error of 8.8% (s = 5.2%). Finally, the model is used to investigate limited speedup from vectorisation despite not being memory-bound. It identifies that instruction throughput is significantly reduced relative to serial counterparts, independent of data ordering in memory, indicating a bottleneck within the processor core.

Item Type:	Thesis or Dissertation (PhD)
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Library of Congress Subject Headings (LCSH):	Application software, Computer simulation, Computer programming
Official Date:	March 2020
Dates:	Date Event March 2020 UNSPECIFIED
Institution:	University of Warwick
Theses Department:	Department of Computer Science
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	Jarvis, Stephen A., 1970-
Sponsors:	Rolls-Royce plc ; Horizon 2020 (Programme) ; Engineering and Physical Sciences Research Council ; Intel Corporation
Format of File:	pdf
Extent:	xiv, 78 leaves : illustrations (some colour)
Language:	eng

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