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

*****

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.

*

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

*

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:

*

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

*

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!

*

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

*******

Medical Spectroscopy : RS

Medical Spectroscopy, as used on POP & Pope for Pulmonary issues last month)The Synergy for upscaling between SiMD, Matrix & Maths reaches a new hight with { Super temporal Resolution Imaging : RS

For checking Processors, RAM, Components & LED & Technology for production errors & validity of course RS

07:48 21/07/2023

The Synergy for upscaling between SiMD, Matrix & Maths reaches a new hight with
{
Super temporal Resolution Imaging of Membrane Potential via Stroboscopic Microscopy

https://is.gd/SpectroscopyPDF

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

https://science.n-helix.com/2023/06/map.html
}

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

(c)RS

**********************************

Technology Super temporal Resolution Imaging (STRI)

Technology called Super temporal Resolution Imaging (STRI), which uses SiMD, matrix, and math to achieve higher temporal resolution than traditional imaging techniques. STRI has the potential to revolutionize the field of medical spectroscopy, as it could be used to study biological processes in unprecedented detail.

The text also links to a number of articles and websites that provide more information about STRI. The article from the American Chemical Society (ACS) provides a detailed overview of the technology, while the website from N-Helix discusses the potential applications of STRI in medical spectroscopy.

Overall, the text provides a good overview of the new technology of STRI. It is clear that STRI has the potential to make a significant impact on the field of medical spectroscopy, and it will be interesting to see how this technology develops in the future.

Here are some additional thoughts on the potential of STRI:

STRI could be used to study the dynamics of biological processes in real time. This could lead to new insights into the mechanisms of disease and the development of new treatments.

STRI could be used to image individual cells and organelles. This could provide new information about the structure and function of these cellular components.

STRI could be used to image tissues and organs in vivo. This could provide new insights into the functioning of the human body.

The potential applications of STRI are vast, and it is likely that this technology will have a major impact on the field of medical research in the years to come.

Here are some specific examples of how STRI could be used in medical spectroscopy:

I do not expect to think of everything.. Rupert S

To Examine technology in production for defects.
To Study earth minerals, Chemicals & Compounds.
To Study Physical Dynamic Effects such as Atom polarity & Physics.

To study the dynamics of cell signaling.
To image the movement of molecules within cells.
To visualize the activity of individual proteins.
To diagnose and monitor diseases.
To develop new drugs and treatments.

The possibilities are endless, and it is exciting to think about how STRI could be used to improve our understanding of human health and disease.

(c)RS

*

Reference Examples Spectroscopy :

Super temporal Resolution Imaging of Membrane Potential via Stroboscopic Microscopy
https://pubs.acs.org/doi/epdf/10.1021/cbmi.3c00054

Synchrotron X-ray Studies of the Structural and Functional Hierarchies in Mineralised Human Dental Enamel: A State-of-the-Art Review
https://www.mdpi.com/2304-6767/11/4/98

Spectroscopy - Spatial-Super-Sample SpectralRay Attention-Enhanced Generative Adversarial Network for Hyperspectral Imagery Spatial Super-Resolution
https://www.mdpi.com/2072-4292/15/14/3644

Enterobacter hormaechei -Driven Novel Biosynthesis of Tin Oxide Nanoparticles and Evaluation of Their Anti-aging, Cytotoxic, and Enzyme Inhibition Potential
https://www.researchgate.net/publication/372427993_Enterobacter_hormaechei_-Driven_Novel_Biosynthesis_of_Tin_Oxide_Nanoparticles_and_Evaluation_of_Their_Anti-aging_Cytotoxic_and_Enzyme_Inhibition_Potential

Spectral Observations and Modeling of a Solar White-light Flare Observed by CHASE
https://iopscience.iop.org/article/10.3847/2041-8213/ace18c

Audio presentation & play

"I made a codec but I am not sure how to improve it! probably interpolation"

Audio presentation & play (c)Rupert S

Available for Bluetooth, VESA, HDMI & DisplayPort & Hardware such as GPU, CPU & Equipment.

Well the thing is that Wavelets (Dynamic mathematical NDimension Nd Shape objects),
& Also PCM is Pictorial 2D & 3D shape in forms such as BitMap.

To explain bitmap; This is a picture; Now with a picture we can present an enhanced version using bilinear interpolation & Trilinear Interpolation...

PCM is a BitMap or JPG or WebP Wavelet 2D drawing of a graph that translates into Audio by copying the frequency & volume.

So basically any operation used on Audio can be used on visual elements; Including wave filters & resonators or WaWa Bars,

Digital Audio presented as BITMAP presents an ideal situation where we can enhance it with Graphical effects such as sharpening & shaping or smoothing..

We can also present the Audio in 3D through a non literal presentation of 3D through Colour or shade on the drawing; or present that audio in a parallel bars or side by side presentation..

The Sound Colour Table : RS

We can use colour to present precision, Warmth & vibrational intensity & amplitude..
We can use cross shading to present repetition, Translation & transition..
We can present so many ways, But more importantly we can compress colour in ways like wavelet
We can Present 3D & Virtual Surround through Colour

We can also present the Audio as WebP or Textures including our compressed forms; However we have to reduce our compression so that no artifacting occurs.

New Audio Formats:

Wavelet Bitmap
Texture formats such as STC, ATC, HDR, Deep Colour

Texture formats such as Drill & SLLRL, ASTC, EAC, DXT, PVRTC & DSC
https://is.gd/Dot5CodecGPU , https://is.gd/CodecDolby , https://is.gd/CodecHDR_WCG , https://is.gd/HPDigitalWavelet

32Bit Float
24Bit Float
16Bit Float

We can potentiate the floating point by using it to present 3D Audio virtualisation or to improve audio precision.

Rupert S

*

XeSS Is here and is great! #Exclusive

https://www.youtube.com/watch?v=uMqKFgJcr-U

Lets use both XeSS & FSR to do Audio Sampling in 3D Wavelet (audio PCM
is just a BMP Saved!
We can do much more & compress more & still have better quality!

*****

O!DMD : Original Dynamic MIDI Audio Device(tm) : Wavelet Vocal & Music/Action/Audio Sample, Instruments & Percussion Simulation, The principle is as follows: (c)RS

24Bit Audio Sample + 8 Bit for audio modifications: 3D Audio, Resonance, Tempo, Pitch, Style Etcetera

A Wavelet is a Shape; A Shape is a LPCM, MP3, MP4 & AC3 & AC4 Wavelet according to the MP4 Standard...
A Wavelet is 12Bit to 32Bit in precision Sample & from 32Kbs to 384Kbs in Bitrate Samples
A Voice/Sample Synth Quality is determined by the Bitrate; We can use Wavelet Sample to Simulate!
We can simulate any Sound with a sample; We can vary the Sound Style, Tempo, Scale & Range...
We can use real processed samples; We can resample Live & Locally or in cloud
Emulation does not need to be 2D, 3D or Processed into 3D & 2D with the same size room in mind for reverb & echo & VR 3D Audio

8Bit Modifier can be 4Bit Modifier + 4Bit 3D VR + 24Bit Audio Sample

(c)Rupert S

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

https://science.n-helix.com/2023/06/ptp.html
https://science.n-helix.com/2023/06/map.html
https://science.n-helix.com/2023/06/tops.html
https://science.n-helix.com/2022/01/ntp.html

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

Sparse matrix multiplication in SRM array
https://www.science.org/doi/10.1126/sciadv.adf7474

Error Correction Options & Mitigation
https://futurism.com/ibm-breakthrough-quantum-computing

*****

Soft Interrupt IRQ: Faster CPU Cycles: RS

A Soft Interrupt is where you direct the interrupt register to a compiled Code Block..
The code block handles the Wait Queue in a gentle way that allows processing to continue & Ram to be accessed..

While the HDD directly writes the IRQ messages to the Code Block; The Code block is below the size of Cache on the Processor..

In advanced scenarios the Soft Int Caches Read/Write in RAM while Directing DMA & R/W Cached Cycles; Good Bioses & Software do this.

But in a processor Internals you have to call the Main Micro loops (Soft Int) in your App; & OS Task Instruction cache.

RS

Interrupts particularly effect the Processor functions such as..
Machine Learning Load & Store of Frames, Also the internet..
In such as Network cards offloading is often required to handle interrupts..

https://science.n-helix.com/2023/06/map.html

*****

Compression formats:

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

Data Saving by inexact replication & Double layer wavelet shaping which are both one believes compatible with analog output & also with adjustment repeat play.

Compression matrix
https://drive.google.com/file/d/1xQ0t7LEYltQ8TR3MDsV4IHE8wrfsfWV0/view?usp=sharing

SLLRunLength : Compressed Pixel
https://drive.google.com/file/d/148-BpVSfT6bA5nPjKoiZ41vwuI9n7P_f/view?usp=sharing

Drill texture & image format (with contrast & depth enhancement)

https://drive.google.com/file/d/1G71Vd9d3wimVi8OkSk7Jkt6NtPB64PCG/view?usp=sharing
https://drive.google.com/file/d/1u2Qa7OVbSKIpwn24I7YDbwp2xdbjIOEo/view?usp=sharing

https://is.gd/Dot5CodecGPU
https://is.gd/CodecDolby
https://is.gd/CodecHDR_WCG
https://is.gd/HPDigitalWavelet

https://is.gd/BTSource

https://is.gd/LEDSource

Secure Configuration:
https://is.gd/SecurityHSM
https://is.gd/WebPKI
https://is.gd/SSL_NetSecurity_NTP_PTP
https://is.gd/EthernetTunnelOpt

PTP & NTP Improve security WW https://is.gd/PTP_TimeStream
Open Streaming Codecs 2023 https://is.gd/OpenStreamingCodecs

OVCC_ANS : Optimised Vector component Compression with Alpha Numeric Sequencing & Compression

OVCC_ANS : Optimised Vector component Compression with Alpha Numeric Sequencing & Compression (c)Rupert S

*

Suitable for codec, Texture, Video Element, Firmware & ROM, Executable, Storage & RAM, DLL & Library runtimes, CSS & JS & HDMI & DisplayPort VESA Specifications : 

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

https://science.n-helix.com/2022/11/frame-expand-gen-3.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

*

OVCC_ANS : RS

Suitable for codec, Texture, Video Element, Firmware & ROM, Executable, Storage & RAM, DLL & Library runtimes, CSS & JS & HDMI & DisplayPort VESA Specifications

Storage Problems EEPROM : Small powerful packed firmware for Devices, Routers, TV's Cameras & Computers

*

Devices, Drivers, VESA DSC & Active display drivers
PoCL & CL Kernels are used for the codecs & shading; Simply from the point of view multithreading SysCL & OpenCL are most effective at headless worker kernels; Frame buffer not required.

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/2022/10/ml.html

https://science.n-helix.com/2022/03/ice-ssrtp.html
*

Cache Cyclic load segment Code Replication is quite a bit more efficient from the Shader, OpenCL, SiMD & Float expression point of view.

With code replication you do not necessarily have to depack the RAM to run the code; But that is a question of Jumps or Cache Cycles!

Similar to vector render on the optimised Vector component input compression is a layer of compression that renders fine lines, Curves & circles & points & basic gradients,

*

Principle of the Repeater with Co-modifier Gradient Wavelet & Numbers: RS

The primary principle to remember is that a gradient wavelet is in effect (in music terms):

A Sustain (Echo note)
A Pause (A silence (Space is taken in a file for this)

A Register Shaped Sustain (Where we move up the scale or down the scale or in a curve; With the same resonance sample, Example Trumpet or Piano or Harp)

A Repeater note : Exact repeat, Varied over time repeat, Quieter or louder, Modified by a coefficient.

So principle is : Copy Note sound & Modify over time, Repeat over time, Repeat & modify over time.

Also repeating for lines in an Image & hence video.

For example Bumps on a door or the texture of paint,
Light & shadow over the same texture; How complex this is depends on required quality!

Image, Number Or Audio sample: Data Complexity & How many SiMD Computation Cycles are required..
The more repeats or how large; Varies the processing workload.

Example: Hello World

Hello World Sample : [HWS] , Silent Echo Sample : [SES]

#PrintF Hello World

[SES], [HWS], [SES]x2, [HWS]x2(louder), [SES](Quieter), [HWS]x4(Louder to quieter),
[SES]x4 (Quieter to much quieter), [HWS]x4(quieter to Louder), [SES]x2(louder to quiet), [HWS]x4(Louder to quieter),

*

Wavelet Float forms

Wavelet bF16, F16 are quite useful for MP4 Standard compression
Wavelet bF32, F32 are quite useful for MP4 Enhanced Precision compression
Speed = bF16 (with advantages of long chain integer & small exponent)
For AVX F32 up to F64 are variously advantaged in multithreading,
Exceptionally bF16 & F16 NANO SiMD
*

OVCC is used to apply layers of vector graphic elements with optimised wavelets..
In principle the file is saved like so:

OVCC Layers

V = Vector
W = Wavelet
Gv = Gradient vector
Ns = Numeric Sequence
As = Alphabet Sequence
Ans = Alpha Numeric Sequence

{Load Binary or code: DLL,Exe, Library, WebJS for example}: {Firmware, Separate or joined}
{ Header }
{ Value storage for replication }
{ Gv:1>n, W:1>n, V:1>n }
{ Cans:1>n, Ns:1>n, As:1>n, Ans:1>n }

Vector Storage

[Gv];[Gv];[Gv]
[V];[V];[V];[V]
[W];[W];[W];[W]
[V];[Gv];[V];[Gv]
[W];[W];[V];[Gv];[W];[W];[V];[Gv]

Sequence Storage

[Ans];[Ans];[Ans]
[Ns];[Ns];[Ns];[Ns]
[As];[As];[As];[As]
[Ns];[Ans];[Ns];[Ans]
[As];[As];[Ns];[Ans];[As];[As];[Ns];[Ans]

Code Sequence Storage

[Loader]
[Cans];[Cans];[Cans]
[Ans];[Ans];[Ans]
[Ns];[Ns];[Ns];[Ns]
[As];[As];[As];[As]
[Ns];[Ans];[Ns];[Ans]
[As];[As];[Ns];[Ans];[As];[As];[Ns];[Ans]

You can use vector compression on plane transparency & Greyscale adding a lot to sharpness if optimised.

*
You see at the worst Drivers are compiled with last stage DSC Compression as Pixel shaders or compute shaders,

Thus avoiding bad bios DSC VESA But you can use OpenCL & directly render the frame as smoothing is not particularly required!

Even though before DSC a Smooth Wavelet is a big advantage to compression ratio & sharpness

But OpenCL Can smooth & sharpen with AA & SS Implemented.

Could We make all codecs compress & decompress ? We can!
I might have an MP4 DVD & also HPC requires WebP compression feature
& also HDR formats like JPGXL & JPG2000 & WebP & H264 & H265 & VP9 & AV1 on systems,
Like the RX570 & ARM, CPU & GPU; With OpenCL Support in all programs & for the operating system

OpenCL Hardware Compression is possible for all encoding formats & textures

VP9, AV1, Media compression acceleration!
But what to use based on de/compression performance?
VP9/H265 Currently Hardware Accelerated 90% of the time.

*

DSC/AV1/VP9/MPEG/H265/H264 Block Size Streamlining (c)RS

Code/JS/OpenCL/Machine Learning Processing Block Size Streamlining (c)RS

Dataset AV1/VP9/MPEG/H265/H264 : case example
My personal observation is that decompression & compression performance relates to block size & cache

SiMD 8xBlock x 8xBlock Cube : 32Bit | x 4 128Bit | x 8 256Bit | x 16 512Bit
Cache Size : 32Kb Code : Code has to be smaller inline than 32Kb! Can loop 4Kb x 14-1 for main code segment


Cache Size 64Kb Data : Read blocks & predicts need to streamline into 64Kb blocks in total,
4Kb Optimized Code Cache
4Kb Predict (across block for L2 Multidirectional)
16Bit Colour Compressed block 4x16Bit (work cache compressed : 54Kb
Lab Colour ICC L2 & block flow L2

*

The advice i give is given with honour & is stated true, We all need a good VP9 & AV1 & Media Codecs!
The advice, is to refresh the stream & restart the browser; You can see the world better with #True-Sourcery

Get rid of 90% of your intel & other device Codec Glitches and errors..
Compile right!

*

Compression, Dictionary Sort & Same Size Copy Match & Unite Same with location in 2D Matrix #JS #C #Python RS 2023

https://is.gd/CJS_DictionarySort

*

*****

Ellipso formula for compressed media:

The headers are encrypted with AES:{GCM, CCM}, CHACHA20-POLY1305
The header containing compression words, File List, Directory & Data chunks for replication..

Ellipso encoded data segments for example graphs, Curves, Shapes, A:B:C colour or audio & math scaling curves,
Representing data curves such as colour gradients & corners or ellipses; In Lines or Cubes..

Conception is similar to compression data compression shapes; But defining most shapes & colour or sound samples.

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/ice-ssrtp.html

Bluetooth dongle LE Protocol
https://drive.google.com/file/d/17csRnAfdceZiTSnQZvhaLqLSwL__zsIG/view?usp=sharing

Rupert S

*****

2 layer/Plane Codecs: RS

Texture Compression & video Compression for quality 12Bit & 16Bit HDR & WCG,

Can also be used in displays for tiling & animation of screen array with multiple frames single post,
Cache & post commands; Single DIMM Post with multiple frames for lower Processor Cycle costs..
Screen brightness & colour control per tile; Single line post or Screen Post Cube Suggested.

In applications 2 layer/Plane texture can post to GPU & animate multiple frames with overlay texture or animation.

In video codecs can animate frame on base layer (background for example)

2 Planes / 2 Layer : Monitor, TV & Codec to screen cycle (advantageous to GPU & ARM Configured units & displays)

Animated or Image or 2 plane static + Animation frame (BumpMapping)

More than 2 Layers is possible but 16Bit & 32Bit SiMD & ALU suggest a range:

*

16Bit Effective ++ List : 2 Layer : ETC, ASTC Etcetera : Compatible Compression

10Bit + 4Bit + Modifiers

12Bit + 4Bit

10Bit + 6Bit

8Bit + 6Bit  + Modifiers

8Bit + 4Bit  + Modifiers

8Bit + 8Bit

8Bit + 4Bit

*

Basic 2 layer involves using another Plane/Layer as a mask,

Primary layer is 8Bit, 12Bit, 16Bit <> NBit Texture; Secondary layer is a mask:

Mask Methods:

1 Layer Texture : Can be animated but second layer will be Sync Timed.

2a layer is darker / lighter Image, Grayscale : HDR + small varieties in shade = WCG
2b layer is darker / lighter Image, Colour, Additive to Colour range + Light/Dark : WCG & HDR
2c Layer subtracts or Adds , Multiplies / Divides : Basic maths operations : Work = Depth

https://is.gd/BTSource

https://is.gd/Dot5CodecGPU
https://is.gd/CodecDolby
https://is.gd/CodecHDR_WCG &
https://is.gd/HPDigitalWavelet

DSC, DXT5, ETC, ATC, PVRTC, ASTC & DTX Compression for display frames

These are the main XRGB : RGBA Reference for X,X,X,X
https://drive.google.com/file/d/1AMR0-ftMQIIC2ONnPc_gTLN31zy-YX4d/view?usp=sharing
https://drive.google.com/file/d/12vbEy_1e7UCB8nvN3hYg6Ama7HIXnjrF/view?usp=sharing

(c)RS

*****

F16b Adaptive Float value : Texture Color Palette 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

*

{Solve} : {Maths Roll Error}

{Maths Roll Error on 24Bit Audio versus 32Bit} ~= Stutter

Additional roll, Error margin on 32Bit maths Float with 24Bit 5 point margin roundups,
A 32Bit float rolls up on a single operation 226526554817.{24Bit float + Error roundup} .9> .49 = .5+ = roll up..

R={5+ or 4- | 0.45+ or 0.44-} : or {0.445, |> 0.444444444445 |> 0.4 N4 +Decimal Places +5}

Clipping operation depth of float; Is 3 operations or 2 with Stop count = 1 to 24 bit places + 1 or 2 for error rolling, up or down.

Precision Clip
Math OP | Clip > Cache {Math OP <> Use}

Precision Counter
Math OP + Counter(internal to FPU:CPU | Stop > Cache {Math OP <> Use}

*

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.

https://is.gd/LEDSource
https://is.gd/MLCodecShaping

*

Drill texture & image format (with contrast & depth enhancement)

https://drive.google.com/file/d/1G71Vd9d3wimVi8OkSk7Jkt6NtPB64PCG/view?usp=sharing

https://drive.google.com/file/d/1u2Qa7OVbSKIpwn24I7YDbwp2xdbjIOEo/view?usp=sharing

Scanline Coder Compression
https://drive.google.com/file/d/148-BpVSfT6bA5nPjKoiZ41vwuI9n7P_f/view?usp=sharing

WebP
https://github.com/webmproject/libwebp
https://github.com/webmproject/libwebp/blob/main/ChangeLog

AV1
https://github.com/AOMediaCodec

HEIF:HEVC
High Efficiency Image Format (HEIF) is being introduced : 10Bit>16Bit HDR
High Efficiency Video Codec (HEVC)-encoded storage system for intra-images and HEVC-encoded video image sequences in which inter-prediction is applied; Also for still images compressed with the HEVC (H.265) codec.
https://www.photoreview.com.au/tips/shooting/heif-what-you-need-to-know/
https://www.howtogeek.com/345314/what-is-the-heif-or-heic-image-format/

File Compression Logic
https://is.gd/BitStreamSpec
https://is.gd/IFFByteOrder

Compression Speed Results
https://quixdb.github.io/squash-benchmark/#results-table

File & Texture Compressors
https://github.com/GPUOpen-LibrariesAndSDKs/brotli_g_sdk
https://github.com/BinomialLLC/basis_universal
https://github.com/darksylinc/betsy
https://github.com/ARM-software/astc-encoder/
https://github.com/synfosec/packz
https://is.gd/CJS_DictionarySort

Python & JS Configurations
https://is.gd/DictionarySortJS

To Compress using CPU/GPU: MS-OpenCL
https://is.gd/MS_OpenCL
https://is.gd/OpenCL4X64
https://is.gd/OpenCL4ARM

PoCL Source & Code
https://is.gd/LEDSource

VVC
https://github.com/fraunhoferhhi/vvenc
https://github.com/fraunhoferhhi/vvdec

https://gitlab.com/AOMediaCodec/SVT-AV1/-/blob/master/Docs/CommonQuestions.md#improving-decoding-performance

Reference : "Patent license terms" https://en.wikipedia.org/wiki/High_Efficiency_Video_Coding#2022

Secure Configuration:
https://is.gd/SecurityHSM
https://is.gd/WebPKI
https://is.gd/SSL_NetSecurity_NTP_PTP
https://is.gd/EthernetTunnelOpt

PTP & NTP Improve security WW https://is.gd/PTP_TimeStream
Open Streaming Codecs 2023 https://is.gd/OpenStreamingCodecs

Codec Parallelism - Dataflow model PREESM, OpenMP and OpenCL
OpenVVC & OpenHEVC Decoder Parameterized and Interfaced Synchronous DataFlow Tile Based Parallelism (PiSDF)

Create the dataflow model is called PREESM. This tool allows the automatic scheduling of tasks according to the number of used cores and the automatic generation of multicore algorithms.
https://link.springer.com/content/pdf/10.1007/s11265-022-01819-7.pdf

"State-of-the-art approaches such as OpenMP and OpenCL"
https://is.gd/BTSource

https://is.gd/LEDSource

(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/2022/11/frame-expand-gen-3.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

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

Suitable for codec, Texture, Video Element, CSS & JS & HDMI & DisplayPort VESA Specifications : https://science.n-helix.com/2022/09/ovccans.html

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

Strobe Line by Line Run Length Compression DVB, NTSC, VESA :RS Approved
https://drive.google.com/file/d/148-BpVSfT6bA5nPjKoiZ41vwuI9n7P_f/view?usp=sharing

Networking & Management
https://science.n-helix.com/2023/06/map.html
https://science.n-helix.com/2023/06/tops.html
https://science.n-helix.com/2023/06/ptp.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

https://www.gyan.dev/ffmpeg/builds/

https://github.com/GyanD/codexffmpeg/releases/tag/tools-2022-01-01-git-d6b2357edd

https://github.com/GyanD/codexffmpeg/releases/tag/5.1.1

https://www.gyan.dev/ffmpeg/builds/ffmpeg-tools.zip

https://github.com/GyanD/codexffmpeg/releases/download/5.1.1/ffmpeg-5.1.1-full_build.zip

https://ffmpeg.org/download.html

https://ffmpeg.org/releases/ffmpeg-snapshot.tar.bz2

Full H265, H264 & AV1 Support https://drive.google.com/file/d/1Xka_QSRmVBCqnyCZwrA_yjnqwSl4g0ml/view?usp=sharing

VP9, AV1, Media compression acceleration!
But what to use based on de/compression performance?
VP9/H265 Currently Hardware Accelerated 90% of the time

Get rid of 90% of your intel & other device Codec Glitches and errors..
Compile right!

Easy Install Codecs : https://is.gd/DilyWinCodec

The advice i give is given with honour & is stated true, We all need a good VP9 & AV1 & Media Codecs!
The advice, is to refresh the stream & restart the browser; You can see the world better with #True-Sourcery

*
'Study Observation' YouTube switches from pushing AV1 by majority to
VP9 & H265 which encodes slightly less, I mean slightly because my own tests
indicate a 300MB/h HD.. So VP9 & H265 Rock with E-AC3 & E-AC4 5.1:

The majority of GPU acceleration of VP9 & H265 & H264 is a good
reason! So let us clarify H264, H265 & VP9 Will become better with
this document. Rupert S

To clarify major improvement to H264, H265 & VP9 are clearly required for class leader,

There may be some doubt as to H264 but not of H265 & VP9!,

However this is 'In 'Statute'' fundamental versioning..

Allowing GPU to continuance to provide a quality of service of exceptional quality for the available price!

Our continued support of the aged & the mentally fit & the able; Of this world & of our society.

OpenCL Compatibility is making these codecs faster: For the highly expectant x64 FFmpeg crew, 

A Most compatible; Easy Install Codecs: https://is.gd/FFmpegWinCodec

Easy Install Codecs: https://is.gd/DilyWinCodec

Easy Install Codecs 4 ARM: https://is.gd/DilyWinARMCodec

Example : https://drive.google.com/drive/folders/1JwbEGHiCzbeDFoRnF43VUHUDZlwcibcX?usp=sharing
* 

OpenCL & other Hardware Acceleration : FFMPEG
https://ffmpeg.org/ffmpeg-all.html
https://ffmpeg.org/documentation.html

https://ffmpeg.org/download.html
https://ffmpeg.org/releases/ffmpeg-snapshot.tar.bz2
https://github.com/FFmpeg/FFmpeg
https://github.com/FFmpeg/FFmpeg/releases/tag/n3.0

HQImage
https://apps.microsoft.com/store/detail/webp-image-extensions/9PG2DK419DRG
https://www.microsoft.com/en-us/p/heif-image-extensions/9pmmsr1cgpwg
https://www.microsoft.com/en-us/p/hdr-wcg-image-viewer/9pgn3nwpbwl9
https://www.microsoft.com/en-us/p/raw-image-extension/9nctdw2w1bh8

HQVideo
https://www.microsoft.com/en-us/store/p/web/9n5tdp8vcmhs
https://www.microsoft.com/en-us/p/mpeg-2-video-extension/9n95q1zzpmh4
https://www.microsoft.com/en-us/p/av1-video-extension/9mvzqvxjbq9v
https://www.microsoft.com/en-us/p/vp9-video-extensions/9n4d0msmp0pt
https://www.microsoft.com/en-us/p/hevc-video-extensions/9nmzlz57r3t7

*****

https://www.phoronix.com/news/Rust-UEFI-Firmware-Hope-Tier-2

https://rust-lang.github.io/compiler-team/

https://dvdhrm.github.io/2022/09/07/towards-stable-rust-uefi/

https://doc.rust-lang.org/nightly/rustc/platform-support/unknown-uefi.html

https://github.com/rust-lang/compiler-team/issues/555

Yes Firmware Codec Development is the Dinosaur!
DOLBY ATMOS 7.1.2 "Dinosaurs in Atmos"- OFFICIAL THEATER DOLBY VISION [4KHDR]
https://www.youtube.com/watch?v=0EKBYVUj4w0

*****

Stone Effect : Image compression for all skin types & Art (c)Rupert S (available to all games):RS

Marble is a beautiful product; People draw it too low quality (in older games) Or too high ôo Oblivion,
Several properties exist in Marble & stone,
Firstly Marble is a co-modifier colour range of mostly gray & white with black over a 1cm² to 10cm² Aria,
As in the pattern has points; Draw the curves and shapes from a central higher contrast area; With tiny modulations of light & dark &or One colour subtly blended with another...

This can be done two ways:

Highly detailed Texture in HDR & WCG.... 4MB texture

Highly detailed Texture in HDR & WCG, But Pallet Limited to 4 zones,
These 4 zones are White & off-White, Dark & Off-Dark, Green, gold, Brown, Gray & White.
These colours apply colour culling between the primary group & therefore reduce the colour pallet by 50%; You compress the file with the off colour zone colours Culled & Save storage file size.
.... 1.5MB texture

Extra detail is payed to which patterns are sharp high contrast & which patterns are smooth & useful to blend with the AA SSA Shader (post render & recache)

Pay attention to animation because not all skin types require direct texture refresh & shaders can micro map a layer on top & thus keep the texture flawless for little cost.


Raytrace into the filter layer (Transparency Depth) (a layer of Shader, BumpMapping, & light textures & Animations)

*****

Good stuff for all networks nation wide, the software is certificate signed & verified
When it comes to pure security, We are grateful https://is.gd/SecurityHSM https://is.gd/WebPKI
TLS Optimised https://drive.google.com/file/d/10XL19eGjxdCGj0tK8MULKlgWhHa9_5v9/view?usp=share_link
Ethernet Security https://drive.google.com/file/d/18LNDcRSbqN7ubEzaO0pCsWaJHX68xCxf/view?usp=share_link

These are the addresses directly of some good ones; DNS & NTP & PTP 2600:c05:3010:50:47::1 2607:fca8:b000:1::3 2607:fca8:b000:1::4 2a06:98c1:54::c12b 142.202.190.19 172.64.36.1 172.64.36.2 38.17.55.196 38.17.55.111

JIT Compiler Dongle - The Connection HPC 2022 RS

JIT Compiler Dongle - The Connection HPC 2022 RS (c)Rupert S

JIT Compiler Dongle makes 100% Sense & since it has no problem acting like a printer! It can in fact interface with all printers & offload Tasks,

However in High Performance Computing mode of operation the USB Dongle acts as the central processor from the device side; That is to say the device such as the printer or the Display...

You can supply a full workload to the dongle & of course it will complete the task with no necessity of assistance from the computer or the device.

The JIT Compiler comes into its own one two fronts:

Compatibility between processor types.

Aiding a device in processing &or passing work to that device to run; Work that is shared & if required workloads are passed back & forth & shared,

Shared & optimised...

The final results for example are post-scripts? no problem!
The final results for example are Directly Compute Optimised Printer Jet algorithms? no problem!
The task needs to compute specifics for a DisplayPort LED Layout ? no problem!

The device is powerful so share, JIT Compiler for real offloading & task management & runtime.

Functional Processing Dongle Classification USB3.1+ & HDMI & DisplayPort (c)RS

Theory 1 Printer

Itinerary:

Printers of a good design but low manufacturing cost of ICB printed circuits have a printhead controller,

But no Postscript Processor; But they do have a print dither controller & programmable version need to interface with the CPU on the printing device,

Print controlling is a viable Dongle & also Cache but workload cache has to have a reason!

That reason here given is the JIT Dongle that is able to interface with both Web print protocol & IDF Printing firmware.

But here we have postscript input into the JIT Compiles Kernel & output in terms of Jet Vectors & line by line Bitmap HDR & head motion calculations,

We can also tick the box on Postscript offloading on functioning PostScript printers; But we prefer to offload JIT for speed & size..

Vectors & curves & lines & Cache.

Theory 2 Screen

Itinerary as of printers but also VESA & line by line screen print & VESA Vectors & DisplayPort Active displays,

Cable Active displays require the GPU to draw the screen & calculate the Line Draw!

The Dongle activates like a screen with processor & carries the screen processing out; Instead of a smartwatch or small phone that does not have a good capacity for computer lead active display enhancements.

Theory 3 Hard Drives & controller such as network cards & plugs for PCI

Adapting to Caching & processing Storage or network data throughput commands, While at the same time being functionally responsive to system command & update makes JIT Dongle stand out at the head of both speed & function...

Network cards can send offloading tasks to the PCI socket & the plug will process them.

Hard-drives can request processing & it shall be done.

Motherboard ROMs & hardware can request IO & DMA Translation & all code install is done by the OS & Bios/Firmware.

Offloading can happen from socket to Motherboard & USB Socket & URT..

All is done & adapts to Job & function in host.

The 8M Motherboard & OS verifies the dongle, licences the dongle from the user..
& runs commands! Any Chipset, Any maker & every dongle by Firmware/Bios
What the unit constitutes is a functional Task offloader for OS & Bios/Firmware.

The utility is eternal & the functions creative & secure & licensed/Certificate verified.

Any Motherboard can be improved with the right Firmware & Plugin /+ device.

(c)RS

*****

DDM Super Immediate Display Modes with 0ms GTG : Operation Latency Zero

By initiating DDM & using the display processor aswell with DPIC JIT,
With DDM Frame Buffer Emulation & Control.

Games & Aiming for Business,
DDC & FreeSync Update today!

In order to set DDM Super Immediate Display Modes you have to set the
display as being DDM with an input frame buffer..

That way both the GPU & the Display can work on the frame in ALLM
Mode; Enhancing processing while reducing latency.

*
FreeSync - DDM - Low Latency Screen Modes

HDMI & DisplayPort : Screen Framebuffer {DDM, FreeSync, ALLM} : Minimal latency post processing : RS

Direct Drive Monitor (DDM) is a mode where the Frame is directly created by the CPU/GPU facing the screen,
The frame buffer facing the Processor must present all capacities & properties of the Screen directly..

List of common properties:

Frame Buffer & Frame buffer write control
Bit depth & FRC
DSC mode
ICC Colour Profile
Write Cache buss width
Timings
Latency
LED Colour range & profile

The GPU/CPU must have the capacity to order write cycles & DSC Decompression layer,
The GPU/CPU must not have a discussion writing to the screen; Direct Write shall be immediate!

So we need to have the frame buffer process as fast as possible & report back,
But we plan to initiate a frame buffer & process it!; Process the frame fast,
To do that we provide all the information from our frame buffer that the CPU/GPU needs to calculate..

Rupert S
*

A DDM Monitor is directly controlled by a GPU/CPU

Initiating a Direct Drive Monitor (DDM) capability enables ultra-thin monitors (and Mobile Phone Screens) With a Short Plug DSC Compression Array...

Could be simple!

Initiate a DDM Mode with DPIC: JIT Kernel to a Frame Processing Unit that directly presents as a surface; All tasks from there in will not be allowed to add latency.

(DDM) DPIC JIT Compiler Mode handles the situation of under performing hardware quite well,

The aim is to solve one of the largest issues with DDM & that is latency! & Frame Distortion such as Frame Blur,

Long cable access to a device encounters the same latency issues as RAM & Storage,
Distance means time!

By Directly compiling commands into an (ESK) Efficient Static Kernel; Stack space (Cache & RAM)...

Processing load is light & may be performed On The Edge; Close to the hardware; in our case a screen with a Single Core ARM Nano millimeters close to the screen.

No we do not need a large CPU that close; But a SiMD array & Texture decompressor & Direct screen print...

We do all our Large Problem solving previously in JIT Kernels; While doing what we can closer to the screen at our Frame Buffer,

We can also directly process commands directed from a larger processor; a CPU, GPU, HUB,

All we need to do is Initiate a DDM Mode with DPIC: JIT Kernel to a Frame Processing Unit that directly presents as a surface; All tasks from there in will not be allowed to add latency.

Rupert S

*

Direct Drive Class : Displays, Printers & Devices such as Joysticks, Mice & keyboards

You know Active Display,
The DisplayPort & HDMI Configuration,
JIT Compiler is a way of getting these to work internally inside the GPU &
In Port class units & USB Dongles that process Computation tasks,

The JIT Compiler DPIC System processes for the Display,

Therefore Able to Activate the display to the highest level of
processing with minimal requirements of necessity!

For example Active Displays with basically a Micro NUC that has an arm
processor & is 4 CM² with USB Connection,
Therefore can power an active display (the type with smaller processors)

Additionally can carry out more work & share a single NUC with
multiple Active Displays..

Bearing in mind that such a OpenCL/JIT Driver is universal to all Systems & Simply classifies by processor
class.

*

The primary motivation for Direct Drive Class displays & Equipment is to offload Processing tasks to the GPU/CPU...

However by example we can Flow Control frames on the HDMI & DisplayPort cables,
We do this by Writing a Kernel/OpenCL Code (Around 60KB) that queries the Frame Ready Flag/Property in the GPU...

Example of Coding Model {Display CPU <> GPU} : Audio : Video : Texture Set

OpenCL Kernel Runtime 512Kb (aim)

Set Properties of display screen (Size & compression & Unique properties such as Texture Types)
Request Frame memory Allocation
Frame Pull (Demand a frame)
Query Frame & Send Ready flag

When Frame Ready***

Send workloads to GPU on frame: Example
Decompression Stack
Frame Mask
Memory Load (Direct DMA access to RAM from Cable)

Sort functions,
Optimisation tasks such as Colour range optimisation & WCG, HDR Tone Mapping.

We keep these operations from sending frame & texture back; by operating on the frame analysis before sending frame...

Reception process involves sending:

Data From Tasks first
RAM Page Map (if we did this process on GPU)
Frame
Process (We send additional tasks if required from a worker thread)

Send out Query : Repeat!

#GoodFramingDirectDrive

RS

***

Plan 2023-03-07 Direct Map DDM : Efficient Monitor Direct Frame Forwarding Render : DDM ALLM : Rupert S

DDM Combined with Combining Texture converters, FSR & OpenCL (Compilable for processor types & Firmware),

Allows the HDMI & DisplayPort FrameBuffer Abstraction layer to pass fully optimized texture layers directly into Frame Rendering & therefor to be directly DMA Copied to the screen along with the Colour conversion table mapping (can be done by the GPU, The Monitor or be Hardware intrinsic to DSC.

DPIC JIT Compiler (Kernels : Small & into Precompiled Code Array Buffer)

https://drive.google.com/file/d/1D27MOBYKVkKib1JzP_eFucp8RRrzAhd6/view?usp=sharing, https://drive.google.com/file/d/1DbcifAxrG4XKfJ9Mrpsfq7kq1I4aV5ES/view?usp=sharing, https://drive.google.com/file/d/1d_bWbZl9fAZXsLbN_jZdqSxdWzraLSIz/view?usp=sharing
***

GTG : GoodToGame : Consoles, Gaming & Movies : RS

DDM ALLM Dongle use case - 10K Presentation of abstract data polygons

Dear VESA & HDMI; This gaming feature does rely on the GPU (in the main) but does have CPU Capacity; Particularly in consoles of the new generation!

Luckily in my experience the CPU is often under utilized by Vulkan API & DirectX 12.1 & therefore the use of DDM mode combined with the JIT Compiler OpenCL compile is a very logical choice! due to DDM being VESA we arrange it,

Clearly the RAMDAC does pre compute a frame & clearly a frame is no more than 15% work for a FreeSync monitor,

Combining the strengths of 2016+ TV & monitor ARM processors (600Mhz+; obviously less powerful than 550Mhz & DDM + ALLM + FreeSync + JIT Compiler is a clean logical choice)

RAMDACS are 600Mhz but we can multitask; So we shall.

Rupert S on behalf of VESA & HDMI & the gaming & Film community.

*****

Example Display Chain (Can be USB/Device Also For the OpenCL Runtime; To Run or be RUN) (c)RS

How a monitor ends up with an OpenCL : CPU/GPU Run Time Process: Interpolation & Screen enhancement: The process path

Firstly we need to access the GPU & CPU OpenCL Runtime such as:

Components that we need:

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/2022/10/ml.html

FPGA 'Xilinx Virtex-II' HPC application Multiple-Applications & Image-Net & Matrix-Multiplication - H-SIMD machine _ configurable parallel computing for data-intensive HPC
https://digitalcommons.njit.edu/cgi/viewcontent.cgi?article=1836&context=dissertations

A SIMD architecture for hard real-time systems
https://www.repository.cam.ac.uk/bitstream/handle/1810/315712/dissertation.pdf?sequence=2

Ideal for 4Bit Int4 XBox & Int8 GPU
PULP-NN: accelerating quantized neural networks on parallel ultra-low-power RISC-V processors - Bus-width 8-bit, 4-bit, 2-bit and 1-bit
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6939244/

Predict Scaling : SiMD/AVX.SSE3:
https://science.n-helix.com/2023/03/path-trace.html

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

Firstly, we need an OpenCL Kernel : PocCL :

PoCL Source & Code
https://is.gd/LEDSource

MS-OpenCL
https://is.gd/MS_OpenCL

https://is.gd/OpenCL4X64
https://is.gd/OpenCL4ARM

Upscale DL
https://is.gd/UpscaleWinDL

https://is.gd/HPC_HIP_CUDA

HIP_CUDA on OpenCL & SPIRV
https://github.com/CHIP-SPV/chipStar

HIP_CUDA on OpenCL & SPIRV : ZIP
https://is.gd/HIP_CUDAonOpenCL

X86Features-Emu
https://drive.google.com/file/d/15vXBPLaU9W4ul7lmHZsw1dwVPe3lo-jK/view?usp=usp=sharing

Crucial components:

Microsoft OpenCL APP
Microsoft basic display driver OpenCL component (CPU)

CPU/GPU OpenCL Driver
PoCL Compiled runtime to run Kernels https://is.gd/LEDSource

We need an Ethernet connection to the GPU (Direct though the HDMI, DisplayPort),
A direct connection means no PCI Bus or OS Component needed,
(But indirect GPU Loaded OpenCL Kernel loading may be required)

Or

We need an Ethernet connection to the PC or computer or console!
Then we need a Driver (this can be integral or Drive) to load the OpenCL Kernel; This can have 3 parts in the main to run it!

Microsoft OpenCL APP
Microsoft basic display driver OpenCL component (CPU)

CPU/GPU OpenCL Driver
PoCL Compiled runtime to run Kernels https://is.gd/LEDSource

The compiled Kernel itself & this can be JIT : Just In Time Compile Runtime

Rupert S

*****

Example of low latency Kernel Runtime to run process sharing between the processors of a system.

VESA DDM is much better with a resident kernel in the GPU & CPU that can run the tasks of display refreshing & forward frame rendering..

One simply needs to know that the display cable has ethernet; Through Ethernet local networking the OpenCL Kernels can be compiled & run..

Enabling any tasks to be shared & averaging processor load & usage of an entire system.

RS

*****

Offloading JITcompiler : Device Driver Offloading Acceleration Pool

Microsoft makes a note of Audio Offloading in the latest chrome update,

It makes sense to note that JITcompiler is a highly efficient transparent offloader,

With CPU & GPU & Processor OpenCL compilers; There is a good chance of your function being supported!

Simple or complex maths & logic is ideal for OpenCL & the creation of a general pool for offloading functions..

OpenCL is able to cater to many maths functions & with calls to security & networking functions,

OpenCL will be very capable in that capacity.

Rupert S

References : https://is.gd/DictionarySortJS

https://science.n-helix.com/2023/06/tops.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/2021/03/brain-bit-precision-int32-fp32-int16.html
https://science.n-helix.com/2022/10/ml.html

Firstly, we need an OpenCL Kernel : PocCL :

PoCL Source & Code
https://is.gd/LEDSource

MS-OpenCL
https://is.gd/MS_OpenCL
https://is.gd/OpenCL4X64
https://is.gd/OpenCL4ARM

*****

The DPIC Protocol in use for display, robotic hardware (arms for example) & Doctor Equipment arms & surgeries, Website loading or games.

In context of load for DPIC, We simply need a page (non-displaying Or Displaying (for example Monitor Preferences)) Inside the GPU..

Can use WebJS, WebASM : WASM, OpenCL : WebGPU : WebCL : WebGPU-ComputeShaders...

RAM Ecology wise between 1MB to 128MB RAM (But should inform client in print of options); I cannot really imagine you would need more apart from complex commands (cleaning for example & robots)

Direct Displayport & HDMI Interface; With or without use of USB Protocol HUB..

Touch screen operation examples:

Can additionally Smart pick diagnostic process of operations or equipment placement & screw & nut & bolting operations & welding or cutting!

For example, the DPIC Protocol can interface & runtime check Operations, Rotations, Motions & activations in well managed automatons; While directly interfacing the ARM/X64/RISC Processor tools & where necessary optimise memory & instruction ASM Runtime Kernel.

*

How does PTP Donation Compute work in business then:

Main JS Worker cache (couple of MB)

{ main . js }

{

{ Priority Static JS Files }

{ Priority Static Emotes & smilies (tiny) }

{ Priority Application JS & Static tiny lushi images (tiny) }

}
{

{ Work order sort task }

{ Sub tasks group }

{Compute Worker Thread }

}

*

(c)Rupert S

*****
Technology Demonstration https://is.gd/DongleTecDemo

Combining JIT PoCL with SiMD & Vector instruction optimisation we create a standard model of literally frame printed vectors :

VecSR that directly draws a frame to our display's highest floating point math & vector processor instructions; lowering data costs in visual presentation & printing.

(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/2022/06/jit-compiler.html

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

Bus Tec : https://drive.google.com/file/d/1M2ie8Jf_bNJaySNQZ5mqM1fD9SAUOQud/view?usp=sharing

Audio BT Codec

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

DSC, ETC, ASTC & DTX Compression for display frames

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

https://science.n-helix.com/2023/02/smart-compression.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/2023/03/path-trace.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

*****

Good stuff for all networks nation wide, the software is certificate signed & verified
When it comes to pure security, We are grateful https://is.gd/SecurityHSM https://is.gd/WebPKI
TLS Optimised https://drive.google.com/file/d/10XL19eGjxdCGj0tK8MULKlgWhHa9_5v9/view?usp=share_link
Ethernet Security https://drive.google.com/file/d/18LNDcRSbqN7ubEzaO0pCsWaJHX68xCxf/view?usp=share_link

These are the addresses directly of some good ones; DNS & NTP & PTP 2600:c05:3010:50:47::1 2604:6600:2000:45::1 2604:6600:2000:2b::1 2a06:98c1:54::c12b 142.202.190.19 172.64.36.1 172.64.36.2 108.181.201.22 108.181.165.159

SiMD Chiplet Fast compression & decompression (c)RS

SiMD Chiplet Fast compression & decompression (c)RS

*
Subject: SiMD Compression / Decompression chip of 2mm on side of die Chiplet (c)RS

Compression / Decompression chip of 2mm on side of die Chiplet (c)RS

Additional CPU & APU Compression / Decompression chip of 2mm to
feature on chiplet console APU's this is planned so that the Chiplet
does not require modification to the console APU,

Additionally to feature pin access Direct Discreet DMA for storage :

https://www.youtube.com/watch?v=1GvUdPn5QLg

*

Configuration of SiMD : Huffman & Compression : RS

To pack the majority of textures to 47 bit, one presumes a familiarity with Huffman codecs & the chaotic wavelets these present...

AVX256 Tasks x 4 = 64Bit
SiMD 16Bit x 2 = 32Bit / Alignment with AVX == x8
SiMD 32Bit x 2 = 64Bit / Alignment with AVX == x4

Closest to 47 = 40Bit Op x 2 (2.5Oe) | 80Bit/2 | 2 op x (1.5Oe)

So 40 Bit x2 parallel 6 Lanes

So on operation terms of precision :
32Bit Satisfies HDR,
40Bit Very much satisfies HDR,

16Bit satisfies JPG (basic)
64Bit satisfies LUT & Wide Gamut HDR Pro Rendering

*
Drill texture & image format (with contrast & depth enhancement)

https://drive.google.com/file/d/1G71Vd9d3wimVi8OkSk7Jkt6NtPB64PCG/view?usp=sharing
https://drive.google.com/file/d/1u2Qa7OVbSKIpwn24I7YDbwp2xdbjIOEo/view?usp=sharing

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

Research topic RS : https://is.gd/Dot5CodecGPU https://is.gd/CodecDolby https://is.gd/CodecHDR_WCG https://is.gd/HPDigitalWavelet https://is.gd/DisplaySourceCode

*

GPU acceleration process : Huffman (c)RS

In the case of dictionary we create a cubic array: 16 parallel Integer cube, 32 SiMD,

FPU is used to compress the core elliptical curve with SVM Matrixing in 3D to 5D for files of 8Mb,FPU is inherently good versus Crystalline structure, We use the SiMD for comparative matrix & byte swap similarity.

It is always worth remembering that comparative operations are one of the most fundamental SiMD functions; But multiply, ADD & divide exist within SiMD,
Functional FPU code can always use arrays of SiMD to handle chaotic play in the field..

A main example is in Huffman's the variance of a wavelet from the main path,
Routes though main wavelet types are handled by table (on the amiga for example) &or FPU!
Micro changes make SiMD viable; In the same principle as a Hive & her ants.

Inherent expansion doubles the expected SiMD use; Ideally 2MB ram per cube
Taking advantage of a known quantity & precision we code-block by 16Bit to 128Bit segments.

Self correction allows us to Cube Huffman Decode into blocks, we parallelize blocks,
To (additionally) handle error we block the original compression.

"We also use fine-grained locking for the frequency dictionary, individually locking each key-value pair. Once the symbol codes have been determined, each symbol is replaced by its code, and all symbols; So are processed in parallel.

Decompression is inherently sequential, and hence much harder to parallelize. In this case, we take advantage of the self-synchronizing property of Huffman coding, which allows us to start at an arbitrary point"

In order of SiMD
https://github.com/lemire/SIMDCompressionAndIntersection
https://github.com/lemire/FastPFor

Huffmans still worth the money!

Principally an order & load+Vec https://github.com/jearmoo/parallel-data-compression

Huffman source, Requires analysis https://github.com/catid/Zpng

https://vignan.ac.in/pgr20/20ES011.pdf
https://bestofgithub.com/repo/Better-lossless-compression-than-PNG-with-a-simpler-algorithm

ZPNG
faster than PNG and compresses better for photographic images. This compressor often takes less than 6% of the time of a PNG compressor
https://github.com/catid/Zpng

*

SiMD Chiplet Fast compression & decompression (c)RS

3 proposals

https://is.gd/BTSource

LZ77:
https://github.com/jearmoo/parallel-data-compression

The FastPFOR C++ library : Fast integer compression :
https://github.com/lemire/FastPFor

SIMDCompressionAndIntersection
C/C++ library for fast compression and intersection of lists of sorted integers using SIMD instructions : https://github.com/lemire/SIMDCompressionAndIntersection

Compressor Improvements and LZSSE2 vs LZSSE8
http://conorstokes.github.io/compression/2016/02/24/compressor-improvements-and-lzsse2-vs-lzsse8
http://conorstokes.github.io/compression/2016/02/15/an-LZ-codec-designed-for-SSE-decompression

Compression Science Docs

A General SIMD-based Approach to Accelerating Compression
Algorithms
https://arxiv.org/ftp/arxiv/papers/1502/1502.01916.pdf

SIMD Compression and the Intersection of Sorted Integers
http://boytsov.info/pubs/simdcompressionarxiv.pdf

Fast Integer Compression using SIMD Instructions
https://www.uni-mannheim.de/media/Einrichtungen/dws/Files_People/Profs/rgemulla/publications/schlegel10compression.pdf

Fast integer compression using SIMD instructions
https://www.researchgate.net/publication/220706907_Fast_integer_compression_using_SIMD_instructions

*****

The FastPFOR C++ library : Fast integer compression
Build Status Build Status Ubuntu-CI

https://jearmoo.github.io/parallel-data-compression/

GO

https://github.com/zentures/encoding

http://zhen.org/blog/benchmarking-integer-compression-in-go/

https://github.com/golang/snappy

The FastPFOR C++ library : Fast integer compression
Build Status Build Status Ubuntu-CI

What is this?

A research library with integer compression schemes. It is broadly applicable to the compression of arrays of 32-bit integers where most integers are small. The library seeks to exploit SIMD instructions (SSE) whenever possible.

This library can decode at least 4 billions of compressed integers per second on most desktop or laptop processors. That is, it can decompress data at a rate of 15 GB/s. This is significantly faster than generic codecs like gzip, LZO, Snappy or LZ4.

https://github.com/lemire/FastPFor

https://github.com/lemire/FastPFor/archive/refs/tags/v0.1.8.zip

https://github.com/lemire/FastPFor/archive/refs/tags/v0.1.8.tar.gz

Java May have a use in JS ôo
https://github.com/lemire/JavaFastPFOR

https://github.com/lemire/JavaFastPFOR/blob/master/benchmarkresults/benchmarkresults_icore7_10may2013.txt

*****

SIMDCompressionAndIntersection

C/C++ library for fast compression and intersection of lists of sorted integers using SIMD instructions : https://github.com/lemire/SIMDCompressionAndIntersection

SIMDCompressionAndIntersection
Build Status Code Quality: Cpp

As the name suggests, this is a C/C++ library for fast compression and intersection of lists of sorted integers using SIMD instructions. The library focuses on innovative techniques and very fast schemes, with particular attention to differential coding. It introduces new SIMD intersections schemes such as SIMD Galloping.

This library can decode at least 4 billions of compressed integers per second on most desktop or laptop processors. That is, it can decompress data at a rate of 15 GB/s. This is significantly faster than generic codecs like gzip, LZO, Snappy or LZ4.

*****LZ77*****

Principally an order & load+Vec https://github.com/jearmoo/parallel-data-compression

https://jearmoo.github.io/parallel-data-compression/


Summary of What We Completed

We have written and optimized the sequential version of the Huffman encoding and decoding algorithms, and tested it. For the parallel CPU version of this, we were debating between SIMD intrinsics and ISPC, and OpenMP.

However, Huffman coding compression and decompression doesn’t seem to have a workload that can appropriately use SIMD. This is because there is no elegant way of dealing with bits instead of bytes in SIMD. Moreover, different bytes compress to a different number of bits (there is no fixed mapping of input vector size to output vector size), which makes byte alignment in SIMD very difficult (for example, the compressed form for a random 4 byte input could range from 2 to 4 bytes). This is much worse for decompression, where resolving bit-level conflicts (where a specific encoding spreads over 2 bytes) is almost impossible and might actually result in the algorithm being slower than the sequential version. Therefore, we decided to focus on OpenMP.

For compression, we first sort the array in parallel, to minimize number of concurrent updates to the shared frequency dictionary, reducing contention and false sharing. We also use fine-grained locking for the frequency dictionary, individually locking each key-value pair. Once the symbol codes have been determined, each symbol is replaced by its code, and all symbols are so processed in parallel.

Decompression is inherently sequential, and hence much harder to parallelize. In this case, we take advantage of the self-synchronizing property of Huffman coding, which allows us to start at an arbitrary point in the encoded bits, and assume that at some point, the offset in bits will correct itself, resulting in the correct output thereafter.

We read about the LZ77 algorithm and explored the different variants of the algorithm. We also explored different ways to parallelize LZ77. One naive approach is running the LZ77 algorithm along different segments of the data. This approach could output the same result as the sequential implementation if we use a fixed size sliding window and reread over some of the data. Another approach is the one outlined in Practical Parallel Lempel-Ziv Factorization which uses an unbounded sliding window and employs the use of prefix sums and segment trees to calculate the Lempel-Ziv factorization in parallel.

Update on Deliverables

Our sequential implementations are close to finished, and we have some idea of how to parallelize the algorithms. Our goal for the checkpoint was to have both of these parts finished, but we have not completely met the goal. We may pivot and work on parallelizing the compression and decompression of the Huffman coding algorithm and drop the LZ77 part of the project altogether.

Our new goals:

Parallelize the Huffman Coding compression.
Parallelize the Huffman Coding decompression or LZ77 compression

Hope to achieve:
Both parts of part 2 in our new goals.

*****ZPNG

Huffman source, Requires analysis https://github.com/catid/Zpng

Small experimental lossless photographic image compression library with a C API and command-line interface.

It's much faster than PNG and compresses better for photographic images. This compressor often takes less than 6% of the time of a PNG compressor and produces a file that is 66% of the size. It was written in just 500 lines of C code thanks to Facebook's Zstd library.

The goal was to see if I could create a better lossless compressor than PNG in just one evening (a few hours) using Zstd and some past experience writing my GCIF library. Zstd is magical.

I'm not expecting anyone else to use this, but feel free if you need some fast compression in just a few hundred lines of C code.

**************************

Main interpolation references:

Interpolation 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

JIT Compiler

Driver & Firmware Integrated JIT Compiler (c)RS

Driver & Firmware Integrated JIT Compiler - DPIC Display Protocol Indirect Compute 2022

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

Integrated JIT Compiler directly into a Shader & OpenCL / Direct Compute Driver Ethernet Protocol Socket & IP

To & from all devices though Firmware Central JIT Compute Compiler

Computation tasks can be carried out by all installed Hardware & USB / Plugged devices:

WebGPU
Python
JavaScript
WebCL, OpenCL & Direct Compute
JIT compiled maths

Indirect Computation such as maths in Application : WebGPU, WebCL, OpenCL & Direct Compute.

Utilising Computation is as simple as having a V8 WebGPU function available,

May be directly available from the GPU without accessing the CPU if SDK is directly supported in GPU RAM...

So in the case of a TV BlueRay Player as an example; We may infact simply be able to integrate..

HTTPS: WebGPU, WebCL, OpenCL & Direct Compute & Methods such as JIT compiled maths.

The plan we use is to; Integrate JIT Compiler directly into a Shader & OpenCL / Direct Compute Driver Ethernet Protocol Socket & IP

Computation tasks can be carried out by all installed Hardware & USB / Pluged devices,

To & from all devices though Firmware Central JIT Compute Compiler

*

Kernel Method requires around 20Kb + Cache Kernel run on OpenCL &or Direct Compute,
Closest device runtime &or Operation infrastructure procedure call.

In the case examples:

Camera focus OpenCL Kernel Ofload
(Edge detect, No image : edges & 4pixels with gradient with jpg compression)

Audio device with buffers OpenCL Kernel Ofload
(processing input is from CPU to Audio Device : Simple Objective Pre Processing case)

SSD & HDD Firmware OpenCL Kernel Ofload
(Location & Write & Math proof of safe write &or read, Error correction)

Printer OpenCL Kernel Ofload
In the case of the printer the postscript driver "Is NOT" installed in your router,
The router prints but has basic drivers,

OpenCL Kernel Ofload (from printer),
Makes the task of processing a Postscript Font & Curl Angle print; Easy!

If you have a USB Hub with processor,
The Postscript Instruction Set is processed as OpenCL Vector Print

*

DPIC Device Protocol Indirect Compute Hub

Proposed HDMI/DisplayPort Hub (also GPU Processed)
Proposed USB Hub,
Proposed Bluetooth Hub,
Proposed WiFi Hub
Proposed Ethernet/Net Hub

with
50Mhz to 800Mhz processor with Dynamic Eco settings
*

On the aspect of HDMI & DisplayPort HTTP Ethernet protocol - DPIC Display Protocol Indirect Compute 2022 (c)RS https://bit.ly/VESA_BT

On the aspect of HDMI & DisplayPort HTTP Ethernet protocol; Several forms of Computation exist as possible for the equipment involved : Televisions, Monitors & GPU & CPU

*

(c)Rupert S https://bit.ly/VESA_BT

Research topic RS : https://is.gd/Dot5CodecGPU https://is.gd/CodecDolby https://is.gd/CodecHDR_WCG https://is.gd/HPDigitalWavelet https://is.gd/DisplaySourceCode

*

Example : JIT Optimise Dynamic code - DPIC Device Protocol Indirect Compute

Audio/Video/GPU/CPU/Urt/USB/BT : hardware to slow or fast? trade Processor Resources : How? DCP:JIT

Camera Focusing API for Web : Application,
Because Computers surely focus a camera better if we use DPIC : Device Compute
Processing JIT Compiler,
Then Latency is not the issue!

Video & Audio can do with additional processing : How? DCP:JIT

Monitor would be able to do so much more! With additional processing : How? DCP:JIT

Kernel Method requires around 20Kb + Cache Kernel run on OpenCL &or Direct Compute,
Closest device runtime &or Operation infrastructure procedure call.

Tier processing; Objectives:

High quality process,
Performance,
Shared workload,
Appropriate Computing unit

In the case examples:

Camera focus OpenCL Kernel Ofload
(Edge detect, No image : edges & 4pixels with gradient with jpg compression)

Audio device with buffers OpenCL Kernel Offload
(processing input is from CPU to Audio Device : Simple Objective Pre Processing case)

SSD & HDD Firmware OpenCL Kernel Offload
(Location & Write & Math proof of safe write &or read, Error correction)

Printer OpenCL Kernel Offload
In the case of the printer the postscript driver "Is NOT" installed in your router,
The router prints but has basic drivers,

OpenCL Kernel Offload (from printer) > (from USBHub : Some) > (Router back to printer),
In an ideal situation the Kernel processes the next tier up; In this case Pro-USBHub;
Leaving the router process free but with a very high quality printing job done.

Makes the task of processing a Postscript Font & Curl Angle print; Easy!

If you have a USB Hub with processor,
The Postscript Instruction Set is processed as OpenCL Vector Print

*
DPIC Device Protocol Indirect Compute Hub

Proposed HDMI/DisplayPort Hub (also GPU Processed)
Proposed USB Hub,
Proposed Bluetooth Hub,
Proposed Wifi Hub
Proposed Ethernet/Net Hub

with
50Mhz to 800Mhz processor with Dynamic Eco settings
*

Inter-device JIT Compiler Kernels (c)RS

JIT Compiler : Driver facing the Monitor is included with JIT Compiler Firmware
subjectively...

For the JIT Compiler to be available add the JIT Compiler to the HDMI
& Displayport Driver,

Facing from the Monitor/AUDIO/VIDEO/BUSS/URT <>
GPU <> CPU

USB & Bluetooth require both the USB, Dongle adapter <> BUSS/URT <> CPU/GPU...
To further connect Printers & other devices...

Under the same principle the Lens of a camera operating under the mounting fixture requires a fast connection,
In order to utilize Infrared/UV/Laser & Light or DIODE Controlled fixtures that require special firmware downloaded kernels,

These kernels are flexible & will speed up devices & assure top performance with:

16Bit, 32Bit, 64Bit & Float Kernels

Driving the monitor & Learning sharper graphics

https://is.gd/BTSource

Technology Demonstration

Firstly, we need an OpenCL Kernel : PocCL :

PoCL Source & Code
https://is.gd/LEDSource

MS-OpenCL
https://is.gd/MS_OpenCL

https://is.gd/OpenCL4X64

https://is.gd/OpenCL4ARM

Upscale DL
https://is.gd/UpscaleWinDL

https://is.gd/HPC_HIP_CUDA

HIP_CUDA on OpenCL & SPIRV
https://github.com/CHIP-SPV/chipStar

HIP_CUDA on OpenCL & SPIRV : ZIP
https://is.gd/HIP_CUDAonOpenCL

X86Features-Emu
https://drive.google.com/file/d/15vXBPLaU9W4ul7lmHZsw1dwVPe3lo-jK/view?usp=usp=sharing

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Code/JS/OpenCL/Machine Learning Processing Block Size Streamlining (c)RS

Dataset AV1/VP9/MPEG/H265/H264 : case example
My personal observation is that decompression & compression performance relates to block size & cache

SiMD 8xBlock x 8xBlock Cube : 32Bit | x 4 128Bit | x 8 256Bit | x 16 512Bit
Cache Size : 32Kb Code : Code has to be smaller inline than 32Kb! Can loop 4Kb x 14-1 for main code segment

Cache Size 64Kb Data : Read blocks & predicts need to streamline into 64Kb blocks in total,
4Kb Optimized Code Cache
4Kb Predict (across block for L2 Multidirectional)
16Bit Colour Compressed block 4x16Bit (work cache compressed : 54Kb
Lab Colour ICC L2 & block flow L2

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

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Combining JIT PoCL with SiMD & Vector instruction optimisation we create a standard model of literally frame printed vectors :

VecSR that directly draws a frame to our display's highest floating point math & vector processor instructions; lowering data costs in visual presentation & printing.

(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/2022/06/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

*****

Good stuff for all networks nation wide, the software is certificate signed & verified
When it comes to pure security, We are grateful https://is.gd/SecurityHSM https://is.gd/WebPKI
TLS Optimised https://drive.google.com/file/d/10XL19eGjxdCGj0tK8MULKlgWhHa9_5v9/view?usp=share_link
Ethernet Security https://drive.google.com/file/d/18LNDcRSbqN7ubEzaO0pCsWaJHX68xCxf/view?usp=share_link

These are the addresses directly of some good ones; DNS & NTP & PTP 2600:c05:3010:50:47::1 2604:6600:2000:45::1 2604:6600:2000:2b::1 2a06:98c1:54::c12b 142.202.190.19 172.64.36.1 172.64.36.2 108.181.201.22 108.181.165.159