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It's not obvious from this article why they need their own original chip. Video transcoding is a quite common task done by dedicated chip (or circuit, like QSV)

It's not obvious from this article why they need their own original chip. Video transcoding is a quite common task done by dedicated chip (or circuit, like QSV). Perhaps because they push new codecs VP9 and AV1, these are also general format but Google is a developer and early adapter. Also perhaps their use case (batch processing, transmitted many times) isn't very suitable for existing transcoding chips that might be optimized for realtime transcoding.

r3013 4y ago
The actual papers are very detailed. https://ieeexplore.ieee.org/document/9567040 https://ieeexplore.ieee.org/document/9567040 https://dl.acm.org/doi/abs/10.1145/3445814.3446723 https://dl.acm.org/doi/abs/10.1145/3445814.3446723 They basically have computing per energy as an efficiency spec and then they show how that spec increased by 20-33x compared to an "Intel Skylake" machine. Google also added some features, like a custom speed vs quality tuning thing, and single and multi-output transcoding. What was interesting to me is the video core was made with "Catapult, a C++ HLS flow from Siemens".
- j45 4y ago
  Compute per watt is a great way to look at it. A very trivial example of this is the concept in homelab circles to compare a cpus geekbench score to its watts to its price. Cost per point.
- IshKebab 4y ago
  That is interesting. I guess it makes the most sense if you already have a full C++ implementation, which they do.
- lerp 4y ago
  There's also a recording of the conference presentation at https://www.youtube.com/watch?v=vdXCVuY2CJs https://www.youtube.com/watch?v=vdXCVuY2CJs.
- ahartmetz 4y ago
  Siemens bought several EDA companies over the last ten years or so, in case anyone wonders why that old German company is offering advanced software.
sp332 4y ago
I think it's the batch thing. They can put in one input file and get out multiple formats and resolutions. Also, they have very specific requirements like only encoding 5 seconds at a time for DASH streaming, so they can build the chips with a specific amount of RAM and leave out features like B-frames or whatever they're not using.
brigade 4y ago
Typically one chip has the hardware for a total encode throughput of like 4k60 pixels per second, optimized for the possibility of one real-time 4k60 encode. The chip also includes an entire GPU and/or a bunch of CPU cores. Putting more fixed encode HW instead of GPU or CPU cores is more useful and efficient for YouTube, and at the same time they don’t need individual encodes to be real-time, so it becomes possible to design the hardware for higher quality if you don’t need to guarantee 16ms frame encode times (maybe? at least, "realtime" is the reason I got when asked why hardware can't use recon for intra mode decision...) Intel went partly this way by slapping three 4-core Xeons on a PCIe card (VCA2), abandoned it, then announced variants of Xe to replace it. But ultimately they’re repurposing their existing silicon and it’s not as important for Intel as it is for Youtube.
yaantc 4y ago
The article [1] is a bit old (2010) but still relevant to answer your question. It compares the efficiency of a HD.264 implemented first on a general purpose CPU, then on a SIMD+VLIW DSP, then on the same DSP with additional optimized instruction, then on this platform with macro memory based accelerators, and lastly a pure ASIC implementation. There are significant efficiency gains at each steps, the big gap is between optimized ops and macro accelerators. Flexibility do have a price. With efficiency gains due to new nodes getting lower (and pricer!), it's normal to see more dedicated hardware accelerators. [1] https://courses.cs.washington.edu/courses/cse591n/10au/Papers/Hameed2010_SourcesOfInefficiency.pdf https://courses.cs.washington.edu/courses/cse591n/10au/Paper...
walrus01 4y ago
not every hardware-encoding AVC (H264) or HEVC (H265) chip is in any way comparable once you start digging down into the various tweaks of encoder settings that are possible. it's very likely that youtube wants capabilities that they may not be able to guarantee exist in commercially available H264/H265 and similar encoding ASICs.

r3013 4y ago

The actual papers are very detailed. https://ieeexplore.ieee.org/document/9567040 https://ieeexplore.ieee.org/document/9567040 https://dl.acm.org/doi/abs/10.1145/3445814.3446723 https://dl.acm.org/doi/abs/10.1145/3445814.3446723 They basically have computing per energy as an efficiency spec and then they show how that spec increased by 20-33x compared to an "Intel Skylake" machine. Google also added some features, like a custom speed vs quality tuning thing, and single and multi-output transcoding. What was interesting to me is the video core was made with "Catapult, a C++ HLS flow from Siemens".

j45 4y ago
Compute per watt is a great way to look at it. A very trivial example of this is the concept in homelab circles to compare a cpus geekbench score to its watts to its price. Cost per point.
IshKebab 4y ago
That is interesting. I guess it makes the most sense if you already have a full C++ implementation, which they do.
lerp 4y ago
There's also a recording of the conference presentation at https://www.youtube.com/watch?v=vdXCVuY2CJs https://www.youtube.com/watch?v=vdXCVuY2CJs.
ahartmetz 4y ago
Siemens bought several EDA companies over the last ten years or so, in case anyone wonders why that old German company is offering advanced software.

sp332 4y ago

I think it's the batch thing. They can put in one input file and get out multiple formats and resolutions. Also, they have very specific requirements like only encoding 5 seconds at a time for DASH streaming, so they can build the chips with a specific amount of RAM and leave out features like B-frames or whatever they're not using.

brigade 4y ago

Typically one chip has the hardware for a total encode throughput of like 4k60 pixels per second, optimized for the possibility of one real-time 4k60 encode. The chip also includes an entire GPU and/or a bunch of CPU cores. Putting more fixed encode HW instead of GPU or CPU cores is more useful and efficient for YouTube, and at the same time they don’t need individual encodes to be real-time, so it becomes possible to design the hardware for higher quality if you don’t need to guarantee 16ms frame encode times (maybe? at least, "realtime" is the reason I got when asked why hardware can't use recon for intra mode decision...) Intel went partly this way by slapping three 4-core Xeons on a PCIe card (VCA2), abandoned it, then announced variants of Xe to replace it. But ultimately they’re repurposing their existing silicon and it’s not as important for Intel as it is for Youtube.

yaantc 4y ago

The article [1] is a bit old (2010) but still relevant to answer your question. It compares the efficiency of a HD.264 implemented first on a general purpose CPU, then on a SIMD+VLIW DSP, then on the same DSP with additional optimized instruction, then on this platform with macro memory based accelerators, and lastly a pure ASIC implementation. There are significant efficiency gains at each steps, the big gap is between optimized ops and macro accelerators. Flexibility do have a price. With efficiency gains due to new nodes getting lower (and pricer!), it's normal to see more dedicated hardware accelerators. [1] https://courses.cs.washington.edu/courses/cse591n/10au/Papers/Hameed2010_SourcesOfInefficiency.pdf https://courses.cs.washington.edu/courses/cse591n/10au/Paper...

walrus01 4y ago

not every hardware-encoding AVC (H264) or HEVC (H265) chip is in any way comparable once you start digging down into the various tweaks of encoder settings that are possible. it's very likely that youtube wants capabilities that they may not be able to guarantee exist in commercially available H264/H265 and similar encoding ASICs.