Mudalige, Gihan R. (2009) Predictive analysis and optimisation of pipelined wavefront applications using reusable analytic models. PhD thesis, University of Warwick.

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Abstract

Pipelined wavefront computations are an ubiquitous class of high performance parallel algorithms
used for the solution of many scientific and engineering applications. In order to aid
the design and optimisation of these applications, and to ensure that during procurement platforms
are chosen best suited to these codes, there has been considerable research in analysing
and evaluating their operational performance.
Wavefront codes exhibit complex computation, communication, synchronisation patterns,
and as a result there exist a large variety of such codes and possible optimisations. The
problem is compounded by each new generation of high performance computing system,
which has often introduced a previously unexplored architectural trait, requiring previous
performance models to be rewritten and reevaluated.
In this thesis, we address the performance modelling and optimisation of this class of
application, as a whole. This differs from previous studies in which bespoke models are applied
to specific applications. The analytic performance models are generalised and reusable,
and we demonstrate their application to the predictive analysis and optimisation of pipelined
wavefront computations running on modern high performance computing systems.
The performance model is based on the LogGP parameterisation, and uses a small
number of input parameters to specify the particular behaviour of most wavefront codes. The
new parameters and model equations capture the key structural and behavioural differences
among different wavefront application codes, providing a succinct summary of the operations
for each application and insights into alternative wavefront application design.
The models are applied to three industry-strength wavefront codes and are validated
on several systems including a Cray XT3/XT4 and an InfiniBand commodity cluster. Model
predictions show high quantitative accuracy (less than 20% error) for all high performance
configurations and excellent qualitative accuracy.
The thesis presents applications, projections and insights for optimisations using the
model, which show the utility of reusable analytic models for performance engineering of
high performance computing codes. In particular, we demonstrate the use of the model for:
(1) evaluating application configuration and resulting performance; (2) evaluating hardware
platform issues including platform sizing, configuration; (3) exploring hardware platform design
alternatives and system procurement and, (4) considering possible code and algorithmic
optimisations.

Item Type:	Thesis or Dissertation (PhD)
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Library of Congress Subject Headings (LCSH):	Holography, Parallel algorithms, Program transformation (Computer programming), Parallel processing (Electronic computers)
Official Date:	July 2009
Institution:	University of Warwick
Theses Department:	Department of Computer Science
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	Jarvis, Stephen ; Vernon, Mary ; Spooner, Daniel Peter
Extent:	xx, 157 leaves : ill., charts
Language:	eng
URI:	http://wrap.warwick.ac.uk/id/eprint/3773

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