Adaptive streaming applications : analysis and implementation models

Leiden Repository

Adaptive streaming applications : analysis and implementation models

Type: Doctoral Thesis
Title: Adaptive streaming applications : analysis and implementation models
Author: Zhai, Jiali Teddy
Publisher: Leiden Embedded Research Center, Faculty of Science (LERC), Leiden Institute of Advanced Computer Science (LIACS), Leiden University
Issue Date: 2015-05-13
Keywords: Adaptive streaming applications
Model-of-computation
High-throughput systems
Hard real-time systems
Abstract: This thesis presents a highly automated design framework, called DaedalusRT, and several novel techniques. As the foundation of the DaedalusRT design framework, two types of dataflow Models-of-Computation (MoC) are used, one as timing analysis model and another one as the implementation model. The timing analysis model is used to formally reason about timing behavior of an application. In the context of DaedalusRT, the Mode-Aware Data Flow (MADF) MoC has been developed as the timing analysis model for adaptive streaming applications using different static modes. A novel mode transition protocol is devised to allow efficient reasoning of timing behavior during mode transitions. Based on the transition protocol, a hard real-time scheduling approach is proposed. On the other hand, the implementation model is used for efficient code generation of parallel computation, communication, and synchronization. In this thesis, the Parameterized Polyhedral Process Network (P3N) MoC has been developed to model adaptive streaming applications with parameter reconfiguration. An approach to verify the functional property of the P3N MoC has been devised. Finally, implementation of the P3N MoC on a MPSoC platform has shown that run-time performance penalty due to parameter reconfiguration is negligible.
Description: Promotor: Ed F.A. Deprettere, Co-Promotor: Todor P. Stefanov
With summary in Dutch
Faculty: Faculteit der Wiskunde en Natuurwetenschappen
Citation: Zhai, J.T., 2015, Doctoral Thesis, Leiden University
Sponsor: Technology Foundation STW
Handle: http://hdl.handle.net/1887/32963
 

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