Davis, James A. (2017) Analytical modelling for the performance prediction and optimisation of near-neighbour structured grid hydrodynamics. PhD thesis, University of Warwick.

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Abstract

The advent of modern High Performance Computing (HPC) has facilitated the use of powerful supercomputing machines that have become the backbone of data analysis and simulation. With such a variety of software and hardware available today, understanding how well such machines can perform is key for both efficient use and future planning. With significant costs and multi-year turn-around times, procurement of a new HPC architecture can be a significant undertaking.

In this work, we introduce one such measure to capture the performance of such machines – analytical performance models. These models provide a mathematical representation of the behaviour of an application in the context of how its various components perform for an architecture. By parameterising its workload in such a way that the time taken to compute can be described in relation to one or more benchmarkable statistics, this allows for a reusable representation of an application that can be applied to multiple architectures.

This work goes on to introduce one such benchmark of interest, Hydra. Hydra is a benchmark 3D Eulerian structured mesh hydrocode implemented in Fortran, with which the explosive compression of materials, shock waves, and the behaviour of materials at the interface between components can be investigated. We assess its scaling behaviour and use this knowledge to construct a performance model that accurately predicts the runtime to within 15% across three separate machines, each with its own distinct characteristics. Further, this work goes on to explore various optimisation techniques, some of which see a marked speedup in the overall walltime of the application. Finally, another software application of interest with similar behaviour patterns, PETSc, is examined to demonstrate how different applications can exhibit similar modellable patterns.

Item Type:	Thesis (PhD)
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Library of Congress Subject Headings (LCSH):	High performance computing, Computer systems -- Evaluation, Computer software -- Evaluation, Hydrodynamics -- Computer programs
Official Date:	May 2017
Dates:	Date Event May 2017 Submitted
Institution:	University of Warwick
Theses Department:	Department of Computer Science
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	Jarvis, Stephen A., 1970-
Sponsors:	Engineering and Physical Sciences Research Council ; Atomic Weapons Establishment (Great Britain)
Format of File:	pdf
Extent:	xxv, 291 leaves : illustrations, charts
Language:	eng

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