Estimation and optimization of the performance of polyhedral process networks

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Estimation and optimization of the performance of polyhedral process networks

Title: Estimation and optimization of the performance of polyhedral process networks
Author: Haastregt, Sven Joseph Johannes van
Publisher: Leiden Institute of Advanced Computer Science (LIACS), Faculty of Science, Leiden University
Issue Date: 2013-12-17
Keywords: Polyhedral process networks
Performance estimation
System-level design
Multiprocessor Systems-on-Chip (MPSoCs) design
High-level synthesis
Abstract: A system-level design methodology such as Daedalus provides designers with a forward synthesis flow for automated design, programming, and implementation of multiprocessor systems-on-chip. Daedalus employs the polyhedral process network model of computation to represent applications. These networks are automatically derived from sequential C code. A forward synthesis flow greatly increases designer productivity. Still, the designer needs to perform a time-consuming forward synthesis step to learn if a network satisfies his performance constraints. Furthermore, it is not trivial to select a set of transformations and transformation parameters for a network such that performance requirements are met. A forward synthesis flow thus solves only part of a design problem, as it does not provide fast feedback on the transformations a designer should apply to meet his performance constraints. This dissertation intro duces different performance estimation techniques for polyhedral process networks. The most promising technique is the profiling-based cprof technique that works directly on the sequential application code. This makes cprof an easy-to-use, robust, and fast technique, without the need to derive a polyhedral process network. This dissertation then discusses four transformations and analyzes factors that affect the efficacy of each transformation.
Description: Promotor: E.F.A. Deprettere, Co-Promotor: A.C.J. Kienhuis
With Summary in Dutch
Faculty: Faculteit der Wiskunde en Natuurwetenschappen
Citation: Haastregt, S.J.J. van, 2013, Doctoral Thesis, Leiden University
ISBN: 9789461823830
Handle: http://hdl.handle.net/1887/22911
 

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