Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Scalable software architecture for high performance video codec's on parallel processing engines

Authors: Krishnakanth Rapaka; Mihir Mody; Keshava Prasad;

Scalable software architecture for high performance video codec's on parallel processing engines

Abstract

Video algorithm (e.g. H.264, MPEG2/4 etc) requires tremendous amount of computation power and data bandwidth. This complexity depends on encoding vs. decoding mode, video standard, resolution, frame-rate and visual quality constraints. Many video architecture solutions typically use multiple processing elements (e.g. multiple DSPs or MCU, DSP/MCU with dedicated accelerators or FPGA etc) to achieve the high computation requirements for video algorithms. These architectures provide new challenges to video software's that are typically designed to run on a single processor. This paper presents software design for a video architecture using parallel processing elements. This paper explains following aspects in detail a) Software partitioning b) Algorithm specific optimizations c) Processor specific optimizations d) Efficient DMA/Cache usage e) Concurrent scheduling of all parallel processing elements. The given approach is explained with example of MPEG4 encoder on TMS320DM6446, which is Davincitrade family device from Texas Instruments Ltd. The given software architecture is scalable for various video standards (e.g. H.264, MPEG2/4 etc) as well as various parallel processing hardware solutions. The software achieves performance Dl@30 fsp on given device at less than 50% of DSP load.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    3
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!