I have thought about the TPU & Yes coming to think of it! the Google Tensor G2 & G3 are indeed Tensor TPU / Coral!

So yes VP9 Coral edition would be quite a big leap in quality with intrinsic Upscaling

An example use of FMA Cooperative Matrix

In the example we use a formula like (U/X²)+(U/Y²)+(U/Z²)
Firstly the x²,y²,z² are MUL, So we need a * table or maybe with FMA we can use a (MUL)+0 ?
My primary observation is that we can use 2 methods:

MUL (U/X²), (U/Y²), (U/Z²) in tables, I suggest 3 * or FMA (MUL)+0
Or we can perform tables in order but complete all the MUL operations in Sync & then ADD with FMA,
Sync : (U/X²)+(U/Y²)+(U/Z²) to (Un/X²)+(Un/Y²)+(Un/Z²)

F1 = First Operation F2 = Second operation R = Result {R1:R3 = R4}

F1
R1=(U/X²) R2=(U/Y²) R3=(U/Z²)
F2
R1=+ R2=+ R3 = R4

So we have an example where MUL & then ADD is usable; But we could use Synced FMA

RS
https://gpuopen.com/learn/amd-lab-notes/amd-lab-notes-finite-difference-docs-laplacian_part1/

How you use FMA, Basic MUL+ADD examples first & then Mul & ADD

Firstly in video,
MUL a float set A * B + C
Video Upscaling basic A:Pixel * B:PixelDiffRightPixel + C:RightPixel,
Do that 16 Times per pixel pair and you have 16Interpolate, So a 16 Data set Wave!
You could obviously use a 32* Wave SiMD & do 4x8; So 4 Pixel groups per Wave.

So for example you can ADD Log Gama or other simple values, In A * B + C,
Pixel Values or whatever, You can use Point float 0.001 for example to do division on floats.

For all personal maths that you imagine:
Simple absolver table for MUL:ADD : MUL* Only = +0, +- Only = N*1 then +-
% = / 100 + ADD Table {N1 <> N...} : Result!

F16b Adaptive Float value : Texture Color Palettes Example : RS

Basic Example of F16b float in action on a colour pallet: {F16b,F32b, F64b}

F16b is short remainder F16 & it has 8 Bits of 0.01 point value rather than 16,
So what do we mean ? What is significant about this?

F16b Has 24Bit precision integer with an 8 bit remainder!
So? So 16Bit + 8Bit = 24Bit! & 8bit point value...

In colour representation point values contribute to subtle blending;
So a full 24Bit contributes to 90% of the Color Palettes

So the 24Bit colour pallet is 32Bit Colour Minus Alpha;
We can use F16b in HDMI & DisplayPort & inside the GPU & Also for textures & JPG'S..
Thereby i present F16b & F24Bit colours in F16b

This saves all data in single 32bit Spaces & therefore is both faster & higher resolution than comparable float value presentations.

Bound to make a big difference to BlueRay, but particularly DVD & AC3 & AC4;
F16b Adaptive Float value : Texture Color Palettes Example;

(you can use F16b * R,G,B,A) in HDMI a& DisplayPort, Massive colour improvements; Lower RAM Costs

Rupert S

Vectors & maths
https://science.n-helix.com/2022/08/simd.html
https://science.n-helix.com/2022/04/vecsr.html
https://science.n-helix.com/2016/04/3d-desktop-virtualization.html
https://science.n-helix.com/2022/04/vecsr.html
https://science.n-helix.com/2018/01/integer-floats-with-remainder-theory.html

Networking & Management
https://science.n-helix.com/2023/06/tops.html
https://science.n-helix.com/2023/06/ptp.html
https://science.n-helix.com/2023/06/map.html
https://science.n-helix.com/2023/02/pm-qos.html
https://science.n-helix.com/2022/08/jit-dongle.html
https://science.n-helix.com/2022/06/jit-compiler.html
https://science.n-helix.com/2022/03/ice-ssrtp.html
https://science.n-helix.com/2022/01/ntp.html

Faster Maths & ML
https://science.n-helix.com/2018/01/integer-floats-with-remainder-theory.html
https://science.n-helix.com/2021/02/multi-operation-maths.html
https://science.n-helix.com/2021/11/parallel-execution.html
https://science.n-helix.com/2022/12/math-error-solve.html
https://science.n-helix.com/2021/03/brain-bit-precision-int32-fp32-int16.html
https://science.n-helix.com/2022/10/ml.html

Focus on Quality
https://science.n-helix.com/2022/09/ovccans.html
https://science.n-helix.com/2022/11/frame-expand-gen-3.html
https://science.n-helix.com/2022/03/fsr-focal-length.html

Hallelujah RS Light-Wave SiMD https://www.allaboutcircuits.com/news/lightelligence-reports-worlds-first-optical-network-on-chip-processor/