Comment by Reason077
9 years ago
Considering Intel, AMD, ARM, Nvidia, Apple, and other hardware companies are all members of the Alliance for Open Media - which is the consortium behind AV1 - I'd expect that work to support it in hardware is already well underway.
Ah...
So we have to buy new processors.
Well, if you want hardware-accelerated decoding, you need new hardware. That seems reasonable?
Software encoder/decoder implementations will also be a thing in the interim, until the hardware is ready.
Are there no common computations among compression algorithms?
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If you don't want your macbook to burn a hole in your lap, potentially. I'm sure most recent processors will be able to do playback, just not optimized, and at high cpu load.
I wonder if AV1 could work with an OpenCL decoder since it does block prediction. Would almost certainly need too much per-frame sychronization to work though...
No different than HEVC or anything else. My CPUs are a few generations behind (i7-4790K and i5-4690K) and they can't hardware decode/encode HEVC.
Yet if you bought a Nvidia 960 about 1.5 years ago when I did (because it supported HEVC, and I upgraded my 10 year old plasma to a 4k TV), it can do it for you. My HTPC can happily play back high bitrate 4k HEVC content without as much as breaking into a sweat.
Sadly Netflix doesn't see it that way and demands that I update my perfectly functional i7-2500 system to a newer one to play back their 4k content.
(Sorry, slightly OT rant).
Unlikely, I would imagine that the vast majority of intrinsics used for VP9 decoding can be used for AV1 decoding as well.
FPGAs can't come soon enough.
FPGAs will never be able to compete on size, cost, or performance/watt compared to optimized dedicated silicon. You're not going to find an FPGA capable of being programmed to encode video on a mobile device.
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The power of FPGA's is their flexibility, not their pure performance.
Dedicated, fixed silicon will outperform FPGA's in performance and energy use practically every time.
For rare/uncommon use cases, having an FPGA you can adapt to your algorithm is fantastic, but for a use case as common and day-to-day as decoding video, a dedicated chip is far more ideal.