Original scientific paper
https://doi.org/10.7305/automatika.2014.12.617
Parallelizing MPEG Decoder with Scalable Streaming Computation Kernels
Josip Knezović
orcid.org/0000-0001-6975-4511
; Department of Control and Computer Engineering, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, HR-10000 Zagreb, Croatia
Igor Čavrak
; Department of Control and Computer Engineering, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, HR-10000 Zagreb, Croatia
Daniel Hofman
orcid.org/0000-0002-7154-0413
; Department of Control and Computer Engineering, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, HR-10000 Zagreb, Croatia
Abstract
In this paper, we describe a scalable and portable parallelized implementation of a MPEG decoder using a streaming computation paradigm, tailored to new generations of multi--core systems. A novel, hybrid approach towards parallelization of both new and legacy applications is described, where only data--intensive and performance--critical parts are implemented in the streaming domain. An architecture--independent 'StreamIt' language is used for design, optimization and implementation of parallelized segments, while the developed 'StreamGate' interface provides a communication mechanism between the implementation domains. The proposed hybrid approach was employed in re--factoring of a reference MPEG video decoder implementation; identifying the most performance--critical segments and re-implementing them in 'StreamIt' language, with 'StreamGate' interface as a communication mechanism between the host and streaming kernel. We evaluated the scalability of the decoder with respect to the number of cores, video frame formats, sizes and decomposition. Decoder performance was examined in the presence of different processor load configurations and with respect to the number of simultaneously processed frames.
Keywords
data streams; multicore; multimedia; parallel systems; stream computing; video decoding
Hrčak ID:
133173
URI
Publication date:
12.1.2015.
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