Authors:
Hashan Roshantha Mendis
and
Leandro Soares Indrusiak
Affiliation:
University of York, United Kingdom
Keyword(s):
HEVC, Decoding, Workload Characterisation, Synthetic Workload Generation.
Related
Ontology
Subjects/Areas/Topics:
Design and Implementation of Signal Processing Systems
;
Digital Audio and Video Broadcasting
;
Image and Video Processing, Compression and Segmentation
;
Multimedia
;
Multimedia and Communications
;
Multimedia Signal Processing
;
Multimedia Systems and Applications
;
Telecommunications
Abstract:
Performance evaluation of platform resource management protocols, require realistic workload models as input to obtain reliable, accurate results. This is particularly important for workloads with large variations, such as video streams generated by advanced encoders using complex coding tools. In the modern High Efficiency Video Coding (HEVC) standard, a frame is logically subdivided into rectangular coding units. This work presents synthetic HEVC decoding workload generation algorithms classified at the frame and coding unit levels, where a group of pictures is considered as a directed acyclic graph based taskset. Video streams are encoded using a minimum number of reference frames, compatible with low-memory decoders. Characteristic data from several HEVC video streams, is extracted to analyse inter-frame dependency patterns, reference data volume, frame/coding unit decoding times and other coding unit properties. Histograms are used to analyse their statistical characteristics an
d to fit to known theoretical probability density functions. Statistical properties of the analysed video streams are integrated into two novel algorithms, that can be used to synthetically generate HEVC decoding workloads, with realistic dependency patterns and frame-level properties.
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