Intel Archives – The Broadcast Knowledge

With two years of development and deployments under its belt, AV1 is still emerging on to the codec scene. That’s not to say that it’s no in use billions of times a year, but compared to the incumbents, there’s still some distance to go. Known as very slow to encode and computationally impractical, today’s panel is here to say that’s old news and AV1 is now a real-time codec.

Brought together by Jill Boyce with Intel, we hear from Amazon, Facebook, Googles, Amazon, Twitch, Netflix and Tencent in this panel. Intel and Netflix have been collaborating on the SVT-AV1 encoder and decoder framework for two years. The SVT-AV1 encoder’s goal was to be a high-performance and scalable encoder and decoder, using parallelisation to achieve this aim.

Yueshi Shen from Amazon and Twitch is first to present, explaining that for them, AV1 is a key technology in the 5G area. They have put together a 1440p, 120fps games demo which has been enabled by AV1. They feel that this resolution and framerate will be a critical feature for Twitch in the next two years as computer games increasingly extend beyond typical broadcast boundaries. Another key feature is achieving an end-to-end latency of 1.5 seconds which, he says, will partly be achieved using AV1. His company has been working with SOC vendors to accelerate the adoption of AV1 decoders as their proliferation is key to a successful transition to AV1 across the board. Simultaneously, AWS has been adding AV1 capability to MediaConvert and is planning to continue AV1 integration in other turnkey content solutions.

David Ronca from Facebook says that AV1 gives them the opportunity to reduce video egress bandwidth whilst also helping increase quality. For them, SVT-AV1 has brought using AV1 into the practical domain and they are able to run AV1 payloads in production as well as launch a large-scale decoder test across a large set of mobile devices.

Matt Frost represent’s Google Chrome and Android’s point of view on AV1. Early adopters, having been streaming partly using AV1 since 2018 in resolution small and large, they have recently added support in Duo, their Android video-conferencing application. As with all such services, the pandemic has shown how important they can be and how important it is that they can scale. Their move to AV1 streaming has had favourable results which is the start of the return on their investment in the technology.

Google’s involvement with the Alliance for Open Media (AOM), along with the other founding companies, was born out of a belief that in order to achieve the scales needed for video applications, the only sensible future was with cheap-to-deploy codecs, so it made a lot of sense to invest time in the royalty-free AV1.

Andrey Norkin from Netflix explains that they believe AV1 will bring a better experience to their members. Netflix has been using AV1 in streaming since February 2020 on android devices using a software decoder. This has allowed them to get better quality at lower bitrates than VP9 Testing AV1 on other platforms. Intent on only using 10-bit encodes across all devices, Andrey explains that this mode gives the best efficiency. As well as being founding members of AoM, Netflix has also developed AVIF which is an image format based on AV1. According to Andrey, they see better performance than most other formats out there. As AVIF works better with text on pictures than other formats, Netflix are intending to use it in their UI.

Tencent’s Shan Liu explains that they are part of the AoM because video compression is key for most Tencent businesses in their vast empire. Tencent cloud has already launched an AV1 transcoding service and support AV1 in VoD.

The panel discusses low-latency use of AV1, with Dave Ronca explaining that, with the performance improvements of the encoder and decoders along-side the ability to tune the decode speed of AV1 by turning on and off certain tools, real-time AV1 are now possible. Amazon is paying attention to low-end, sub $300 handsets, according to Yueshi, as they believe this will be where the most 5G growth will occur so site recent tests showing decoding AV1 in only 3.5 cores on a mobile SOC as encouraging as it’s standard to have 8 or more. They have now moved to researching battery life.

The panel finishes with a Q&A touching on encoding speed, the VVC and LCEVC codecs, the Sisvel AV1 patent pool, the next ramp-up in deployments and the roadmap for SVT-AV1.

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Speakers

	Yueshi Shen Principle Engineer AWS & Twitch
	David Ronca Video Infrastructure Team, Facebook
	Matt Frost Product Manager, Chome Media Technologies, Google
	Andrey Norkin Emerging Technologies Team Netflix
	Dr Shan Liu Chief Scientist & General Manager, Tencent Media Lab
	Jill Boyce Intel

As technology continues to improve, immersive experiences are all the more feasible. This video looks at how the CDNs can play their part in enabling technologies which seem to rely on fast, local, compute. However, as with many internet services, low latency is very important.

Greg Jones from Nvidia and Nehal Mehta form Intel give us the lowdown in this video on what’s happening today to enable low-latency CDNs and what the future might look like. Intel, owners of FPGA makers Altera, and Nvidia are both interested in how their products can be of as much service at the edge as in the core datacentres.

Greg is involved in XR development at Nvidia. ‘XR’ is a term which refers to an outcome rather than any specific technology. Ostensibly ‘eXtended’ reality, it includes some VR, some augmented reality and anything else which helps improve the immersive experience. Greg explains that the importance of getting the ‘motion to photon’ delay to within 20ms. CDNs can play a role in this by moving compute to the edge. This tracks with current trends on wanting to reduce backhaul, edge computation is already on the rise.

Greg also touches on recent power improvements on newer GPUs. Similar to what we heard the other day from Gerard Phillips from Arista who said that switch manufacturers were still using technology that CPU’s were on several years ago meaning there’s plenty in the bank for speed increases over the coming years. According to Greg, the same is true for GPUs. Moreover, it’s important to compare compute per watt rather than doing it in absolute terms.

Nehal Mehta explains that, in the same way that GPUs can offload certain tasks from the CPU, so do FPGAs. At scale, this can be critical for tasks like deep packet inspection, encryption or even dynamic ad insertion at the edge,

The second half of video looks at what’s happening during the pandemic. Nehal explains that need for encryption has increased and Greg sees that large engineering functions are now, or many are soon likely to be, done in the cloud. Greg sees XR as going a long way to helping people collaborate around a large digital model and may help to reduce travel.

The last point made is regarding video conferencing all day long leaving people wanting “more meaningful interactions”. We are seeing attempts at richer and richer meeting experiences, both with and without XR.
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Speakers

	Greg Jones Global Business Development, XR NVIDIA
	Nehal Mehta Direcotr Visiual Cloud, CDN Segment, Intel
	Moderator: Tim Siglin Founding Executive Director, Help Me Stream

Hardware encoding is more pervasive with Intel’s Quick Sync embedding CUDA GPUs inside GPUs plus NVIDIA GPUs have MPEG NVENC encoding support so how does it compare with software encoding? For HEVC, can Xilinx’s FPGA solution be a boost in terms of quality or cost compared to software encoding?

Jan Ozer has stepped up to the plate to put this all to the test analysing how many real-time encodes are possible on various cloud computing instances, the cost implications and the quality of the output. Jan’s analytical and systematic approach brings us data rather than anecdotes giving confidence in the outcomes and the ability to test it for yourself.

Over and above these elements, Jan also looks at the bit rate stability of the encodes which can be important for systems which are sensitive to variations such services running at scale. We see that the hardware AVC solutions perform better than x264.

Jan takes us through the way he set up these tests whilst sharing the relevant ffmpeg commands. Finally he shares BD plots and example images which exemplify the differences between the codecs.

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Speaker

Jan Ozer
Principal, Streaming Learning Center
Contributing Editor, Streaming Media

In the ongoing battle to find the minimum bitrate for good looking video, automation is key to achieving this quickly and cheaply. However, metrics like PSNR don’t always give the best answers meaning that eyes are still better the job than silicon.

In this talk from the Demuxed conference, Intel’s Vasavee Vijayaraghavan shows us examples of computer analysis failing to identify lowest bitrate leaving the encoder spending many megabits encoding video so that it looks imperceptibly better. Further more it’s clear that MOS – the Mean Opinion Score – which has a well defined protocol behind it continues to produce the best results, though setting up and co-ordinating takes orders of magnitude more time and money.

Vasavee shows how she’s managed to develop a hybrid workflow which combines metrics and MOS scores to get much of the benefit of computer-generated metrics fed into the manual MOS process. This allows a much more targeted subjective perceptual quality MOS process thereby speeding up the whole process but still getting that human touch where it’s most valuable.

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Speaker