Massively Parallel Open Source Encoding for Adaptive Streaming

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Publisher: SMPTE — White Plains, NY, USA
Doc Type: Conference Paper
Content Type: Original Research
Volume: 2018, No. 10, pp. 1–8
Abstract: Encoding of premium UltraHD content in adaptive streaming ecosystem trades the number of encode jobs for a wider network and device reach. The recent emergence of content and context adaptive technologies which often require “trial encodes” further raises the amount of computational resources needed to encode a single video. — Distributed encoding, where non-overlapping chunks of the same video are encoded in parallel on different machines, emerged as the mainstream response to these challenges. This approach reduces the overall encoding time and makes the best use of available hardware resources, and is an excellent fit to a cloud or cluster environment. — In this paper we will describe an implementation of the massively parallel approach to video encoding. We will start from defining a chunk encode, “joblet”, and what it entails. Lastly, the paper will demonstrate a dramatic increase in the computational efficiency of high-quality offline video encoding without a significant impact on video quality.
Publication Date: 2018-10-22
DOI: 10.5594/M001829
ISBN: Print: 978-1-61482-960-7
Link: https://doi.org/10.5594/M001829
Author(s): Alexander GiladiComcast
Blake OrthComcast
Douglas BayComcast
David LeachComcast
Alex BalkComcast
Keyword(s): Video Compression, Distributed Encoding, Distributed Processing, HEVC, X265
Copyright: © 2018 Society of Motion Picture and Television Engineers, Inc.

Bibliographic Reference(s)

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MulticoreWare Inc, “x265 online documentation”, [Online]. Available: http://x265.readthedocs.org/en/default/ EXTERNAL
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ITU-T REC H.265 [Active]

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Alexander Giladi, Blake Orth, Douglas Bay, David Leach, and Alex Balk; Massively Parallel Open Source Encoding for Adaptive Streaming, SMPTE Meetings and Conferences ( October 2018); SMPTE, 2018, ISBN: 978-1-61482-960-7. Available at https://doi.org/10.5594/M001829

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Alexander Giladi, Blake Orth, Douglas Bay, David Leach, and Alex Balk; Massively Parallel Open Source Encoding for Adaptive Streaming, SMPTE Meetings and Conferences ( October 2018); SMPTE, 2018, ISBN: 978-1-61482-960-7. Available at https://doi.org/10.5594/M001829

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<span class="citation">Alexander Giladi, Blake Orth, Douglas Bay, David Leach, and Alex Balk; <cite>Massively Parallel Open Source Encoding for Adaptive Streaming</cite>, SMPTE Meetings and Conferences ( October 2018); SMPTE, 2018, ISBN: 978-1-61482-960-7. Available at <a href="https://doi.org/10.5594/M001829" target="_blank" rel="noopener">https://doi.org/10.5594/M001829</a></span>

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Alexander Giladi, Blake Orth, Douglas Bay, David Leach, and Alex Balk; <cite id="bib-10-5594-m001829">Massively Parallel Open Source Encoding for Adaptive Streaming</cite>, SMPTE Meetings and Conferences ( October 2018); SMPTE, 2018, ISBN: 978-1-61482-960-7
<span class="doi">10.5594/M001829</span>
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