Machine Learning Equates Solve Table for Advanced ML

Machine Learning Equates Solve Table for Advanced ML (c)RS

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Int8:SiMD : Maths & Logic

This is about how you think about components such as INT8, INT4(Xbox) & SiMD, You have to classify by necessity & optimise the structure.

You can shape the game reality with specific control objects & statics!
Maths in SiMD & Int8 & Machine Learning in Int8 & SiMD; SiMD is hard maths, Int8 is soft edge inference...

Both are maths; But soft logic is not a PROOF Math but can be proof; Hard math is not 'Invention & Imagination 'Exactly''

But we have both to improve performance.

RS
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Solve Table of Statistically provable Machine Equates & Solves : Table of function competitors & Operators.

"I know this is depressing from my end with a FX8320E with AVX but if you multi tune the CPU Kernel for the RX / RTX that 512DL AVX would have meaning, If you are kind you will allow machine learning on the AVX FX8320E Level to work on SiMD Yes / No comparisons !"

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SiMD Performance : RS

Performance per WATT of MMX & MMX+ & SSE & AVX Machine Learning & Shader code; Is a matter of 8x8Bit & 16x16Bit Code on GPU

Our role is to reduce complex un-cache-able ML to Cache Enabled 64KB
Modelling of 1990's without Quality loss of 32Bit++ 64Bit+

8x8Bit sharpening MMX Becomes Dual Pipe (16x16bit)*2 in 32Bit Dual 16 Pipeline & Twice as sharp
Machine Learning method for MMX Is Fast & Cheap, MMX2 More Compatible,
Intrinsic improvements such as combined ops & DOT4 Further improve the performance of under 1MB Code..

Performance & Function per WATT, Is unbeaten; Let us prove it!

For example Quake has MMX Emulation & MMX Dithering code on 3D Textures,
In 8Bit 256 Colours dithering is noticeable; In 15Bit to 32Bit the small shade difference in dithering colour is subtle & flawless,
Improving light subtilty & Colour pallet WCG & HDR 10Bit to 16Bit per channel.

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Solve Table of Statistically provable Machine Equates & Solves : Table of function competitors & Operators.

Runtime Library - Multiple Solve Table

I would like a Solve Table of Statistically provable Machine Equates & Solves that make the equivalent of Maths Compilers such as RUST & Fortran's

For example basic ML code test function loops are basically compatible with X-OR Comparators on AVX! Other functions such as greater or less than; Are AVX Compatible.

Machine Learning : List of actions that are SiMD Baseline: Statistical Observance and Solve Tables

Yes or no comparator X-OR
Memory array Byte Swap
Greater or less than with swap or with X-OR Roll
Memory save & store
Edge comparisons
Compares (Colour, Math, Equate, Target, Solve if)

There are more! Statistical Observance and Solve Tables.

Examples 2:

Shape compare is a matter of inner & outer Vector : Comparison & X-OR, Larger outside & X-OR The differentiation:
By Dot,
By Mass (non literal dot difference comparator by axis),
Actual Mass
Density : Lumina, Weight, Mole, Mass / Area

Edge Solve : X-OR ~= Colour, Lumina, Shade, Vibrancy, Distance, Matrix Solve 3D>=2D Flattened Comparator
If = X-OR=N<0.0001 Then Compare &= Mutex Solve / Average

Polygon Join/Merge Tessellation : If Model = Same (T1 + T2 If (T1 + T2)/2 = Difference Less Than 0.0001 | = Merge/Converge

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We all think our own way; Potential is always there on a Runtime Library - Multiple Solve Table

Machine learning | Equate ~= Multi Layer Wavelet Abstraction
https://science.n-helix.com/2022/09/ovccans.html

https://www.youtube.com/watch?v=-9lCpfrOQQ4

(c)Rupert S 2022-10

https://is.gd/LEDSource
https://is.gd/BTSource

https://science.n-helix.com/2021/03/brain-bit-precision-int32-fp32-int16.html
https://science.n-helix.com/2022/08/jit-dongle.html
https://science.n-helix.com/2022/06/jit-compiler.html

https://is.gd/MLCodecShaping

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This one will suite Dedicated ARM Machine in body armour 'mental state' ARM Router & TV
(ARM Learning 4K ROM; Safe Larger USB ROM) https://bit.ly/3Afn1Y4

https://drive.google.com/file/d/102pycYOFpkD1Vqj_N910vennxxIzFh_f/view?usp=sharing

Android & Linux ARM Processor configurations; routers & TV's upgrade files, Update & improve
https://drive.google.com/file/d/1JV7PaTPUmikzqgMIfNRXr4UkF2X9iZoq/

Providence: https://www.virustotal.com/gui/file/0c999ccda99be1c9535ad72c38dc1947d014966e699d7a259c67f4df56ec4b92/

https://www.virustotal.com/gui/file/ff97d7da6a89d39f7c6c3711e0271f282127c75174977439a33d44a03d4d6c8e/

Python Deep Learning: configurations

AndroLinuxML : https://drive.google.com/file/d/1N92h-nHnzO5Vfq1rcJhkF952aZ1PPZGB/view?usp=sharing

Linux : https://drive.google.com/file/d/1u64mj6vqWwq3hLfgt0rHis1Bvdx_o3vL/view?usp=sharing

Windows : https://drive.google.com/file/d/1dVJHPx9kdXxCg5272fPvnpgY8UtIq57p/view?usp=sharing

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Machine learning | Equate ~= Multi Layer Wavelet Abstraction

https://science.n-helix.com/2022/09/ovccans.html

https://science.n-helix.com/2023/02/smart-compression.html

https://science.n-helix.com/2021/10/he-aacsbc-overlapping-wave-domains.html

(documents) JIT & OpenCL & Codec : https://is.gd/DisplaySourceCode

Include vector today *important* RS https://vesa.org/vesa-display-compression-codecs/

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/2022/04/vecsr.html

https://science.n-helix.com/2016/04/3d-desktop-virtualization.html

https://science.n-helix.com/2019/06/vulkan-stack.html

https://science.n-helix.com/2019/06/kernel.html

https://science.n-helix.com/2022/03/fsr-focal-length.html

https://science.n-helix.com/2018/01/integer-floats-with-remainder-theory.html

https://science.n-helix.com/2022/08/simd.html

Eclectic & for the codecs of the world! OVCCANS (install and maintain as provided HPC Pack)

https://science.n-helix.com/2018/09/hpc-pack-install-guide.html

*****
Best NPM site on world https://npm.n-helix.com/bundles/

(Simple Install) Website Cache JS Updated 2021-11 (c)RS https://bit.ly/CacheJS
(Simple Install) Science & Research Node High Performance Computing
Linux & Android https://is.gd/LinuxHPCNode

Presenting JIT for hardware interoperability & function :
https://is.gd/DisplaySourceCode

https://is.gd/BTSource

(Simple Install) Website Server Cache JS Updated 2021-11 (c)RS
https://bit.ly/CacheJSm
(Simple Install) Website Server Cache JS Work Files Zip Updated
2021-11 (c)RS https://bit.ly/AppCacheJSZip
*****

machine learning https://www.amazon.com/dp/B08V134ZFD

Vibration Array Spectrometer : (c)RS

Vibration Array Spectrometer : (c)RS

Vibrating side to side & where necessary up and down & at angles to create a complete wavelength photo & data from events such as nuclear reactions..

The devices specific vibrational frequency can range into the thousands Hz & must slow down before vibrating back to assist delicate sensor material from cracking or fracturing during work cycles..

We can use compound to bounce absorbed energy back the other way; Such as silicone & rubber,
But they will be Soft & springy to reduce energy transfer of heat or radiation..

Must also be capable of resisting high & low temperature or environmental energies for long periods.

Super conducting surface vibration is capable of shifting a side strengthened cube at higher frequency with wave motions & sound also.

Interpolation of Spectrometer Data RS 2022

We can examine the light shift with our spectrometers & use interpolation arrays to make photos of it,

Thus we will be able to isolate the spectrometric data more precisely on our telescopes; When we use split colour wavelength spectrometry.

How do these Interpolation arrays work ?

We align the orbital position & azimuth & time with the specific wavelength in our Sapphire Crystal Grid Sensor spectrometer,

We do this with time so that we can align multiple orbit passes or vibrations of our sensor & create a sharp full spectrum image & data array!

We then can verify the exact spectrum of each star or subject; For example when using a spectrometer in CERN that vibrates at high frequency..

(c)Rupert S

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Interpolation in the age of Virtual Screen Resolution/Scaling : The process of evolutions in sharpness for over qualified displays(proud makers) (c)Rupert S

LED Pixel By Pixel exact full screen display of all resolutions with automatic compatibility for all input VESA Resolutions & Zero incompatibility with Any Resolution in the correct dimensions : RS https://is.gd/LEDSource

With PoCL & FSR intrinsic

It makes perfect sense that scaling frames is done though PoCL & FSR, Indeed both are required for CPU function!

Streaming services frame video & scale it & so do games, the scaling of inset video is a logical vector of FSR Scaling & colour correct display... HDR, SD, Rec709, Rec2020

Pure Tone Encoding/Decoding Codec

Applies to Displays & Camera/Recording Equipment; Codec: Decode & Encode,
Colours of composing display or recording elements; Red, Green, Blue, Grayscale Channel,
Pure tone Encoding & Decoding.

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FRC is clever Dither : https://is.gd/BTSource https://is.gd/LEDSource

The main thing about Rec709 10Bit is that all 10Bit is in LED Standard spectrum, All 1.07B colours; Add FRC this is important!

Rec2020 is flexible upto 12/14Bit So 8Bit+2/4/6/8Bit FRC makes sense! & so does 10Bit + FRC

FRC Modes:

6Bit+FRC (for car & mobile tablet)

8Bit+FRC

10Bit+FRC

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https://is.gd/ColourGrading

4 primary colour composure: RS

What does decomposing a frame into 4 colour groups mean?

Red, Green, Blue, Grayscale

Each pixel on a screen has 4 colour components & they are on a different place on the screen,
So when we sharpen; We sharpen to the closest pixel LED of the right colour,

Obtaining the best colour with the most logical of LED content,
the right colour sharpened for the right LED

Fist of all "We Have to decompose the image into primaries to compose the screen in it's highest colour value composite" Sharpening our composure to maximum colour correctness & sharpness Is only a:

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Interpolation FRC Frame Compose:

CPU Estimate 300Mhz : 600Mhz : 900Mhz

2 step process,

Max 3 Processor Cycles:
Get/Fetch, Decompose, Blend & Sharpen,

Compose/FRC to pure Primaries Pixel & Interpolation
Max 5 Cycles

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The creation of the frame requires so much data bandwidth, more pictures means more RAM...
Refinement means less error repair?

So what can we do ?

This is how interpolation works in principle:

We find the edges of a blurred image, now for our purposes we will Super Sample that image before saving it!

Therefore we have maneuvering room to upscale the actual screen & we can!

Using a simple principle of dividing the Image pixel count into its defining Red, Green, Blue & contrast shadow...

We have three planes of existence? no 4! Red, Green, Blue, Backlight or light shading!

With this we interpolate the nearest Pixel of the closest matching colour..

Not perfect; We still can lose contrast,
But we can take an upscaled image enhanced Alpha blend & get more from the actual display.

We can imagine the image being too red,green,blue, too contrasted?

But no, The project is to bring real extra resolution to the screen; By dividing our Red,Green,Blue,Black & White pixels into individually sharpened & together blended master piece,

One picture; 4 parts; One Whole piece

4 primary colour composure: RS

What does decomposing a frame into 4 colour groups mean?

Red, Green, Blue, Grayscale

Each pixel on a screen has 4 colour components & they are on a different place on the screen,
So when we sharpen; We sharpen to the closest pixel LED of the right colour,
Obtaining the best colour with the most logical of LED content,
the right colour sharpened for the right LED

Divided we FALL, Together we stand tall, The important bit is to catch the pieces that start to fall & rebuild tall!

Rupert S

If you design and create LED Monitors & TV's & want 165Hz refresh rate you often have sRGB, OLED Monitors are over 2x the price! So you need LED,

But how do we get the best out of LED?

Two ways: to be clear we use both methods at the same time!

1: We use FRC to increase colour references within our pallet ...
2: We sharpen & smooth unique content!

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https://science.n-helix.com/2022/03/fsr-focal-length.html

https://science.n-helix.com/2021/09/temporal-aliasing-image-shaping-polygon.html

https://science.n-helix.com/2022/04/vecsr.html

https://science.n-helix.com/2022/08/simd.html

https://science.n-helix.com/2022/08/jit-dongle.html

https://science.n-helix.com/2022/06/jit-compiler.html

Reference source https://is.gd/LEDSource

Main interpolation references:

This doc https://drive.google.com/file/d/1dn0mdYIHsbMsBaqVRIfFkZXJ4xcW_MOA/view?usp=sharing

ICC & FRC https://drive.google.com/file/d/1vKZ5Vvuyaty5XiDQvc6LeSq6n1O3xsDl/view?usp=sharing

FRC Calibration >

FRC_FCPrP(tm):RS (Reference)

https://drive.google.com/file/d/1hEU6D2nv03r3O_C-ZKR_kv6NBxcg1ddR/view?usp=sharing

FRC & AA & Super Sampling (Reference)
https://drive.google.com/file/d/1AMR0-ftMQIIC2ONnPc_gTLN31zy-YX4d/view?usp=sharing

Audio 3D Calibration
https://drive.google.com/file/d/1-wz4VFZGP5Z-1lG0bEe1G2MRTXYIecNh/view?usp=sharing

2: We use a reference pallet to get the best out of our LED; Such a reference pallet is:

Rec709 Profile in effect : use today! https://is.gd/ColourGrading

Rec709 <> Rec2020 ICC 4 Million Reference Colour Profile : https://drive.google.com/file/d/1sqTm9zuY89sp14Q36sTS2hySll40DilB/view?usp=sharing

For Broadcasting, TV, Monitor & Camera https://is.gd/ICC_Rec2020_709

ICC Colour Profiles for compatibility: https://drive.google.com/file/d/1sqTm9zuY89sp14Q36sTS2hySll40DilB/view?usp=sharing

https://is.gd/BTSource

Colour Profile Professionally
https://displayhdr.org/guide/
https://www.microsoft.com/store/apps/9NN1GPN70NF3

*Files*

This one will suite Dedicated ARM Machine in body armour 'mental state' ARM Router & TV https://drive.google.com/file/d/102pycYOFpkD1Vqj_N910vennxxIzFh_f/view?usp=sharing

Android & Linux ARM Processor configurations; routers & TV's upgrade files, Update & improve
https://drive.google.com/file/d/1JV7PaTPUmikzqgMIfNRXr4UkF2X9iZoq/

Providence: https://www.virustotal.com/gui/file/0c999ccda99be1c9535ad72c38dc1947d014966e699d7a259c67f4df56ec4b92/

https://www.virustotal.com/gui/file/ff97d7da6a89d39f7c6c3711e0271f282127c75174977439a33d44a03d4d6c8e/

Python Deep Learning: configurations

AndroLinuxML : https://drive.google.com/file/d/1N92h-nHnzO5Vfq1rcJhkF952aZ1PPZGB/view?usp=sharing

Linux : https://drive.google.com/file/d/1u64mj6vqWwq3hLfgt0rHis1Bvdx_o3vL/view?usp=sharing

Windows : https://drive.google.com/file/d/1dVJHPx9kdXxCg5272fPvnpgY8UtIq57p/view?usp=sharing