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PhD Thesis


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« Methods and Tools for Rapid and Efficient Parallel Implementation of Computer Vision Algorithms on Embedded Multiprocessors ».

Author: V. Schwambach
Advisor: S. Mancini
President of jury: D. Borrione
thesis reviewer(s): S. Derrien, F. Berry,
thesis examinator(s): D. Fey, S. Cleyet-Merle,
These de Doctorat Université Grenoble Alpes
Speciality: Informatique
Defense: March 30 2016
ISBN: 978-2-11-129211-6

Abstract

Embedded computer vision applications demand high system computational power and constitute one of the key drivers for application-specific multi- and many-core systems. A number of early system design choices can impact the system’s parallel performance – among which the parallel granularity, the number of processors and the balance between computation and communication. Their impact in the final system performance is difficult to assess in early design stages and there is a lack for tools that support designers in this task. The contributions of this thesis consist in two methods and associated tools that facilitate the selection of embedded multiprocessor’s architectural parameters and computer vision application parallelization strategies. The first consists of a Design Space Exploration (DSE) methodology that relies on Parana, a fast and accurate parallel performance estimation tool. Parana enables the evaluation of what-if parallelization scenarios and can determine their maximum achievable performance limits. The second contribution consists of a method for optimal 2D image tile sizing using constraint programming within the Tilana tool. The proposed method integrates non-linear DMA data transfer times and parallel scheduling overheads for increased accuracy.

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