Friday, March 24, 2023

Path-trace-RTDL (c)RS - The combination of Ray Tracing & Path Tracing & FSR_DL; The advantage being a combination of RayTrace CU & General SiMD

Path-trace-RTDL (c)RS

The combination of Ray Tracing & Path Tracing & FSR_DL; The advantage being a combination of RayTrace CU & General SiMD, RS 2023-03 in response to the RS Technology being implemented.

Path Tracing define: RS

Path tracing is when you take an objective viewpoint; A number of viewpoints to the receptor (Observer, such as gamer or camera

VP = View Point, Observer is camera, RT Path = RT Core Ray

View point Mesh, That is directional

                             VP : VP : VP : VP : VP

                             VP : VP : VP : VP : VP

                             VP : VP : VP : VP : VP

                             VP : VP : VP : VP : VP

VP : VP : VP : VP : VP {Forward} VP : VP : VP : VP : VP

VP : VP : VP : VP : VP {Observer} VP : VP : VP : VP : VP

VP : VP : VP : VP : VP {Backward} VP : VP : VP : VP : VP

                             VP : VP : VP : VP : VP

                             VP : VP : VP : VP : VP

                             VP : VP : VP : VP : VP

                             VP : VP : VP : VP : VP

The location VP initiates a SiMD view directly to & from reflective objects & calculates distortion of view & texture with FSR_DL

In this view i would like you to consider a reflective bounce camera viewpoint & think of the energy that saves you.

RayTracing Define:

Ray is cast from object & calculated to target vector; With Distortion calculation & reflections.

We Combine minimum intersection with the VP; Using a cast Ray; So we know the viewpoint is active,
We trace the route back as the observer & calculate each intersection as an observer...

FSR_DL handles surface distortions & fogs of war...

We minimise the viewpoints memory footprint by altering the scale of the viewpoint in respect to the observers screen resolution / Distance .... We can also upscale the pretend frame!

We can cache the frame & discard if we wish!

Raytracing also provides distortion defines for viewpoints & Ray Distortion & Direction Calculations.

RT-Sparse-Field Pre Calculation Cache : RS & Lisa Lue

During the initiation of the frame we calculate polygon placement,
We Cache the metrics & use them for our distance fields.

Long term Non Volatile Cache
Short term recalculation cache
Validate Cache & use for ray tracing RayMarch & lighting.

Real Time Sparse Distance Fields:

Distance Fields are defined as Object detection with range finding,
In GPU SiMD we can reduce the Field Multiple Recount,

Low cache containment Serial processing; Is where we have not got all the Polygon distances counted & in cache...

We can however count on the GPU having the Polygon Map in RAM for a small segment of polygons; But due to the fact that we place the polygons in precise locations; We already have Distance.

Distance fields are helpful because; Ray-forwarding (Ray March) does not need to do more than,
Process; Distortion & Viscosity & Density & transparency & Reflection,

But we can do this over larger fields in areas with lower levels of modification property with counts as a lower required precision!

(c)Rupert S

Path-trace-RTDL : This could be us : Path Tracing all light reflection, Does not require something as high on GPU as RX6500! Can be CPU SiMD/AVX on the Vectors, So can be a regular thing!

We can even super sample our cube maps dynamically; So that we take the vector locations & transform the cube maps into fully RayMaped Polygons.

The results are all about how we plan to Dynamically Optimise & Draw Vectors.



PoCL Source & Code

Bus Tec :

Audio BT Codec

DSC, ETC, ASTC & DTX Compression for display frames

Monday, February 27, 2023


Similar Wavelet Conversion with minimal reprocessing : Smart Access : RS

(repeated encoding cost reduction) i know you are a coder, you could help ffmeg & avx on the FX8320E, Likewise consoles face same issue with FFPEG & Codecs & likewise with media acceleration by non repetition of encoding

Similar Wavelet Conversion with minimal reprocessing : Smart Access : RS

Printing Technology 'When you "Tie" the Knot' : 
We want those Hand drawn Donald duck, Micky & Daffy in true line drawn splendour, 
But hand drawing 8K is hell, 
Remaster printing technology : For all monitors, TV's & Operating systems : DTS, Dolby : Functioning wave conversion

Smart-De-Compression : repeated encoding cost reduction : (c)Rupert S

Wavelet Classifiers

Compressed Data, GZip, BZip, LZH

Primarily our goal is to Originate Encode in a form that is Compatable with the hardware chain,

For example in the case of HDD > CPU > GPU the right Texture & Number formats, Often 16Bit or 32Bit float & Texture,

However with Video we have to expand the frame wavelets into Compatable Texture formats!

We convert the Video Wavelet in Smart Access to the closest Texture format wavelet; Or directly play the video! But suppose we are using Bink Video? We directly convert & keep wavelets that are the same in the new texture,

We therefore select a texture format like NV12 or ETC2; One that has the most Similar Wavelets & can therefore reduce Conversion Cost of the frame by as much as 100% (If all wavelets are the same)!

We know Wavelet types & Colour depth of all texture classes; So we will select one with a good range,
In most cases we play MP4+ Wavelets; So we can Use a JPG type texture; So all the compression wavelets remain minimally processed.

A single Frame + previous B Frame; Into a single texture of the same Wavelet Compression Classification,

The result is minimal processing CPU Cycles.


Overall reducing costs of higher resolution resolving; As available in 264 > 265 > 266/VVC & other Media Encoders : Rupert S

You can see that, formats such as 265 & 264 are related, Obviously at a higher resolution in the case of 265!
But in many Wavelet transform cases we can minimise the Processing cost, We do however need to know like Google's ML Voice Encoder; The ones we do not need to change (minimum benefaction)

My chief challenge of Wavelet thought is a multiple frame picture of an eye (WebP for example),
The resolution is 640x480 & We know in most probabilities that; The Eye was transformed to wavelet in HD,

So we have a wavelet curve; Black centre & A surrounding Iris!
We need to expand that wavelet so we will suppose that the higher precision version of the wavelet will add details?

We must explore how the wavelet transforms a Higher Resolution form into a lower resolution form,
We can therefore in theory use the same wavelet at higher resolving depth?

We might be able to convert a lower resolving wavelet in 12Bit into the 16Bit version & have a better understanding of the higher quality version!

We can therefore most probably reuse the wavelet; Transforming from 264 to 265 & upscale & compress more,

Overall reducing costs of higher resolution resolving; As available in 264 > 265 > 266/VVC

#WaveletProve Both that the wavelet is infinite & that; The Breton
shirt wavelet has a pattern represented in 12Bit but liberating into
the profound on 16Bit, 32Bit & more!

(To understand wavelet context, in textile & theory & of course Audio & Video)

Can we prove the wavelet of a Breton shirt for infinity, like mauri
My augment being that we can upscale that Breton shirt! & prove it's
17th century values...
Both that the wavelet is infinite & that; The Breton shirt wavelet has
a pattern represented in 12Bit but liberating into the profound on
16Bit, 32Bit & more!

Example Wavelets to prove upscaling is possible

Rupert S

Wavelet Upscaling : JPG / Video / Games

Example 2 Voxel to High Quality : RS

The Story : HP : V-FX Wavelet Voxel Transforms : V-FX-WVT (c)RS (Harry Potter + More)

I was wondering what to add to Wavelet transforms; Well i was thinking about Harry Potter,
Full body FX are Half Resolution; In Fact they are Depth of Field Voxels,

For people who don't know Voxel is when you make a Cube of the right shade from a picture & set it at the right depth!

For those criticizing such an act as lazy; You would have to understand how fast technology has developed!

Some characters Fly at a very low resolution & Others like Harry Potter & Melfoy Don't!

You would have to realise that V-FX is based on the ability of the person to be in the role... They perform ;-)


V-FX Wavelet Voxel Transforms : V-FX-WVT (c)RS (Harry Potter + More)


The Wavelet is the JPG Pixel Group of a single Group of pixels at the same size as the composing Voxels of the V-FX

A Voxel is a Cube of Pixels set in 3D

When it comes to Transforms; This piece is called:

Transforms for classic movies : How you upscale VFX : RS

Firstly the VOXEL (Simple Wavelet Cube) needs to be compared to a fully dressed original character,

Then you need to map the correct features into The voxel cube space; After you Average Anti-Alias & Upscale the Cube Map (Original V-FX + Original Video Frame Person)

You then need to map an effective Wavelet of the Original V-FX with a modifier Layer of transparent Wavelet (The Photo in High Detail, This is also a Wavelet Series)



Example 3 : Lessons to learn : Wavelets : Upscaling (c)RS

Now about the Voxel 4x4 cube map 'Transform wavelet' is a simple JPG Wavelet
(if used properly compressed & older games did not because processors where not very fast (33Mhz)

High resolution 'Transform Wavelet' (Overlayed) is a full to higher resolution JPG Wavelet
In Upscaling we need to get from one to the other,
Transform Wavelet from Voxel Wavelet,

Sample Scaling:But supposing we have samples of like minded objects?
We can use Machine Learning to imprint a pattern!

But great looking as this is, not perfect as seen in Example 3 About Example 2 : HP!

Wavelet permutation:

Resolve the wavelet to full precision, Workable; But we need to know the result is correct!ML Can help; But that is very subjective..

Mostly this works.

Identity Follow through:

Machine Learning that identifies the subject matter [Samsung & LG TV's 2020+ Example]

So what do we do? We Add the lot! haha

Rupert S


Example 4 : Lessons to learn : Wavelets : Upscaling (c)RS

2 Pattern Matrix Wavelet (c)RS

Wavelets are patterns; With Colour infilling (why not a wavelet itself!

Well wavelets come in forms (Gif)8Bit, 10Bit, 12Bit, 16Bit(JPG)

We can advance the precision by using a higher Precision (16Bit, 24Bit, 32Bit); But we need to save storage space!

First thing is to use bF16 & bF32; This keeps the majority of the data from being sub pixels.

Second thing is to make maximum use of multiple Precisions, Mix F16 with F32..
Google Lyra Codec demonstrates this in Machine Learning.

Third : Keep Precision within margins, Small Textures do well in 8Bit Matrix Wavelets...
But 16Bit Colour Precision & 16Bit Precision both look good in HD High Quality HDR WCG

(Usable as encryption archetype): Chaos:A:B:T:Pi:Arc:Sin:Tan
Very usable /dev/rnd Random Ring : TRNG : GPU : CPU : Asics : Using Chaos Wavelet

{Wavelet:Colour Point) A to B as expression of Pi
{Wavelet:Colour Point} A to B as expression of Arc, Sin, Tan

[2PMW File Array]
[Header : Easy Identifier : Basic Name]
{Header Packed Wavelet Groups] [1 Image Wavelet : Colour Shading Wavelet 2, 4, 8 Group]

[Image Array lines]
|Packed Groups of] : [ Image Wavelet 1 : Colour Shading Wavelet Associations, 1 to 8]
[Packed Groups of] : [ Image Wavelet 1 : Colour Shading Wavelet Associations, 1 to 8]
[Packed Groups of] : [ Image Wavelet 1 : Colour Shading Wavelet Associations, 1 to 8]



Audio/Video/Image Format : Packing Vectors (c)RS

Vector Wavelet Examples : Math object

Wavelet Curve compress, Normally from left because we code Left to right & that is optimal for our hardware.
Can be numeric sequence Direction point 1=D D=1,2,3,4 2=Db = 1,2,3,4 | Displacement Dp = 1,2,3,4 Assuming Left To Right or curve displacement = Time

Distance N from source edge, Curve:Sin/Tan
(Example) D=1 Db=3 Dp1=2 Dp2=3 | Curve = Tan3+Db2

Logarithmic Pack,
Integer Comparator : N+N2+N3=N+1+2+3 | Sequence

Example 5 : Predict Scaling : SiMD/AVX.SSE3 : (c)RS

SiMD Interpolation grids & Predict with Raytracing & General SiMD
Reference Grid

With the Interception/Processing of Predict Statements in Frames of Video & Audio; Using a simple Grid:

Pr = Predict (motion) Px = Pixel t1:2:3 time period


Basically you can see the pixels move in frame Px1 & Predicted in Pr2 & Pr3,
Raytracing SiMD predict future motion though maths; We can use the SiMD to,

Both predict & interpolate/Upscale from 8bit, 10Bit, 12Bit, 14Bit to 16Bit values or rather wavelets,
Because Raytracing SiMD are high precision maths; They prove advantageous if we have them; SiMD/AVX.SSE3

Interpolation : Prxi Pxri : {PxPrPi} Theory : RS

We must present a point between Px (pixel) & Pr (predict); In maths this would be a remainder,
We can draw a pixel in the Remainder Point; The Interpolation point (PI); When? When we upscale!,
We can use two principles, Px (actual pixel), Pr (Predicted Pixel), PI Pixel Interpolation!

We can guess with both Px & Pr on the content of PI & both Predict & Interpolate the pixel...
As additional Data; This does not worry us a lot.


(c)Rupert S


Interpolation & Extrapolation Policy : RS

We can conclude Interpolation & Tessellation have requirements : 2D & 3D Spline Interpolation & Extrapolation; Gaussian methods on linear surfaces,

We extrapolate the new; Such as blade edge; We can however layout a simple grid to our supposition edge & interpolate.

We do not need to extrapolate where we have planed to draw; With so much as a 3cm polygon with 4 Lines & 2 edges,

We can however draw a fractal blade; For example : HellSinger from Elric Melbone.
Massive Datasets

Python Libraries Interpolation:

15 Types


JIT Compile Displacement Micromap : Interpolation & Extrapolation Policy : RS

Compress its internal geometry representations into the compressed format Just in time,
Optimizing, Allocating & de-allocating in accord with Mesh Shaders & Cache availability.

VK_NV_displacement_micromap, which for Vulkan ray-tracing can help with added detail
No Comment
VK_NV_displacement_micromap allows a displacement micromap structure to be attached to the geometry of the acceleration structure,
allow the application to compress its internal geometry representations into the compressed format ahead of time.


Our options for interpolation (don't forget Gaussian)

bsplin3val — 3d spline arbitrary derivative evaluation function
cshep2d — bidimensional cubic shepard (scattered) interpolation
eval_cshep2d — bidimensional cubic shepard interpolation evaluation
interp — cubic spline evaluation function
interp1 — 1D interpolation in nearest, linear or spline mode
interp2d — bicubic spline (2d) evaluation function
interp3d — 3d spline evaluation function
interpln — linear interpolation
linear_interpn — n dimensional linear interpolation
lsq_splin — weighted least squares cubic spline fitting
mesh2d — Triangulation of n points in the plane
smooth — smoothing by spline functions
splin — cubic spline interpolation
splin2d — bicubic spline gridded 2d interpolation
splin3d — spline gridded 3d interpolation


2D-3D Spline Interpolations with background complementary colour layer smooth blend

Right on the kindle paper white 2D Spline is good for a single layer, 3D Spline is good if you rasterize a shader behind the text and shade it: The method would not cost over 1% of processing power on a 2 core ARM 400Mhz, If the image is relatively static.

On full Colour HDR WebBrowser, The 3D Spline method makes sense with complementary colour blending...
On mostly static content; 3% of total page processing costs.
On mostly Static Text with mobile images a combination of 2D & 3D Spline; 7% to 15% of cost.

interp2d — bicubic spline (2d) evaluation function
interp3d — 3d spline evaluation function

Rupert S

Specification for Open Compute & Gaussian Interpolation & JIT Compile
Displacement Micromap : Interpolation & Extrapolation Policy : RS,,,,


Texture Compressors

To Compress using CPU/GPU: MS-OpenCL

PoCL Source & Code


The Smart-access

[Innate Compression, Decompression, QoS To Optimise the routing, Task Management To optimise the process] : Task Managed Transfer : DMA:PIO : Transparent Task Sharing Protocols

The following is the initiation of the Smart-access Age

QoS To Optimise the routing:Task Management To optimise the process

Transparent Task Sharing Protocols

Innate Compression, Decompression

Examples of compression

Thursday, February 23, 2023

PM-QoS - Processor Model QoS Tree for TCP, UDP & QUICC

Quality of Service Protocol & the TCP & UDP & QUICC Protocols : RS

Extremely good for HDMI & DisplayPort & USB/URT & 2.4G/Bluetooth : In regards to Codec development and flow & device control,
Audio, Video, Process & Command

Congress - Congestion Control - Combined Network QOS Routing Table Tree-Swarm - Quality of Service Protocol & the TCP & UDP & QUICC Protocols


Processor Model for TCP, UDP & QUICC : (c)RS

To put TCP, UDP & QUICC in a proper place in your minds for application,
Think about Applying them to processors; Particularly Neuromorphic, ML & GPU/CPU!

How exactly?

Address space modelling for data transfer:
Between RAM, HDD/SDD & CPU & Internally mapping across cache & Sparse Model NAND Gates.

In the situation internal to Device Gates & Logic Circuits; We map address spaces across the processor,
We internalize the location logic as a network & utilise TCP, UDP & QUICC,

We do not need the sending strategy of Data Transfer to be Random; Random wastes Bandwidth!
But we do need a QOS Data Transfer policy & Networking Tactics!

Why ? Not all processor functions are directly connected in MultiChip & 3D Model Processor.


By thinking about the Processor Model for TCP, UDP & QUICC : (c)RS

We soon find the best light TCP, UDP & QUICC Network Strategy.

Think about this model designing the Network Protocols



"Kevin Cisco-Kevin

Date: Tue, 21 Feb 2023 08:32:03 -0800

Subject: Re: To think about the Network Model : Processor Model for TCP, UDP & QUICC : (c)RS

What we really need is a transfer layer mechanism modeled after Swarm

where packets are broken up into chunks and reassembled after

handshaking. But we don't live in that world."

Kevin Suggests we think about Swarm : RS : What do i think on average (Swarm)

PM-QoS - Swarm : Networking TCP UDP QUICC NTP DNS

I think that Swarm; Multi Target Networking is a primary method under consideration for QUICC & UDP & NTP Responses,

Swarm is high noise; High Volume Send & Receive,
With alteration though Statistical & Machine rout optimisation... That bandwidth cost reduces,
ML : Neural network, Send, Receive & Confirm, Swarm, In effect on globally predictable commodities such as:

NTP, DNS (popular), News & Decentralised command...

Can work! Network Command requires directly applied logic; What i mean is : Confirmed Command & Reception affirmation & Action!

So i propose the following:

Combined Network QOS Routing Table Tree-Swarm : CNetQSRT-Tree-Sw : Rupert S 2023-02

QOS Applied to QUIC, TCP, UDP Data packet Anagrams

What I mean is that QUIC is a protocol that passes data through multiple network adapters like a tree,
What we do is send information on the data transfer abilities of each adapter (locally) & prefer a route,
We prioritise routes based on data flow statistics & choose thereby optimum routes...

By Statistically collating data locally (in network adapter group, per localised network...

We will further select a route based on those statistics; Machine Learning is not obligatory & hence there is less to go wrong,

Routers do not need to be as modern & We can collect that information for routing tables & Create Optimum routes; Like a tree; With little need for control or modification...

All TCP, UDP & QUIC & NTP & DNS packets get to the required destination fast & with low latency.

QOS is clearly of advantage to QUIC, Because we can assess the data throughput of the modems/Network adapters & change routes? 
For optimum performance & minimum error or work.

Swarm:ML (Known Receiver : Known Sender)

DNS Global Submit

Network Tunnelling, For example: Torado, Large Download Acceleration

Secure Network Tunnelling, For example: VPN, VPS, Ethernet, 3G, 4G LTE, Volt, 5G Volt, Telecommunications Networking & GPS)

Defined routing with QOS Network optimisation (Localised) & Data bandwidth data (Localised)

Global Zone routing through tables...

Statistic Enhanced Routing & Delivery


QOS : Quality Of Service protocol : RS

Personally I believe QOS : Quality Of Service protocol be introduced
to all network traffic,
Primarily the Point A to point Z route needs planning first.

QOS Datagram
Network throughput Capacity of the network card
Advertise Capacity in local network
Plan routes based on network capacity

So the Quality Of Service Protocol needs to send a datagram to the
network adapter of site:

A to Z

A list of local routes needs to be cached & prioritised based on
Network point A's network capacity & priority,

The rout needs Point A to Z mapped & Z to A

We then send data with a packet listing preferred routes

[QOS][Origin : Target][Preferred route list forward sent][Network Performance Metric Packet]

[Origin : Target][Preferred route list forward sent][Semi Static Route Tunnel]

[Packet ID][Origin : Target][Data Packet]

Searching for a route with every packet costs processor Cycles; So
preferred routes need to be tunnelled & Secured with TLS

Rupert S

Code Speed


Example of a Secure Tunnel System:

TLS Optimised

Ethernet Security


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

Install and maintain as provided HPC Pack, Exactly as presented with nodes & functions; Be as generous as you can towards our research goals.



PM-QoS - Processor Model QoS Tree for TCP, UDP & QUICC

The Method of PM-QoS Roleplayed in a way that Firmware & CPU Prefetch ML Coders can understand.


Multiple Busses &or Processor Features in an Open Compute environment with competitive task scheduling

[Task Scheduler] Monticarlo-Workload-Selector

We prioritise data traffic by importance & Need to ensure that all CPU Functions are used...

In the case of a Chiplet GPU We need to assign function groups to CU & QoS is used to asses available Multiple BUSS Capacities over competing merits,
[Merits : Buss Data Capacity, Buss Cycles, Available Features, Function Endpoint]

PM-QoS is a way of Prioritising Buss traffic to processor functions & RAM & Storage Busses that:

States a data array such as:

Buss Width

divisibility ((Example) Where you transform a 128Bit buss into 32Bit x 4 Data motions and synchronize the transfers,

Data Transfer Cycles Available

Used Data Rate / Total Data Throughput Rate = N

(c)Rupert S

**************************** Reference Ambition

Title: Specifying New Congestion Control Algorithms

Date: Fri, 17 Feb 2023 16:39:25 +0100

Title: Specifying New Congestion Control Algorithms

Document date: 2023-02-17



The IETF's standard congestion control schemes have been widely shown

to be inadequate for various environments (e.g., high-speed

networks). Recent research has yielded many alternate congestion

control schemes that significantly differ from the IETF's congestion

control principles. Using these new congestion control schemes in

the global Internet has possible ramifications to both the traffic

using the new congestion control and to traffic using the currently

standardized congestion control. Therefore, the IETF must proceed

with caution when dealing with alternate congestion control

proposals. The goal of this document is to provide guidance for

considering alternate congestion control algorithms within the IETF.

The IETF Secretariat

Saturday, December 3, 2022

Precision Differential Rollover Math Error Solve - RS

Precision Differential Rollover Math Error Solve - (c)Rupert S

{Solve} : {{Maths Roll Error on 24Bit Audio versus 32Bit} ~= Stutter} : Windows 3D Audio, DTS & Dolby Atmos 2022-11-30 RS

Windows 3D Audio, DTS & Dolby Atmos 2022-11-30 RS

Solve Basic numeric math rollover errors on float and integer operation in applications; runtimes; applications & DLL & Processors : RS


{Solve} : {Maths Roll Error} : (c)RS
{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}



Several Problems that are solved by application of PDRMES: Rollover Error solve:

JPG's use 16Bit Wavelets & AVX is 128Bit, So a small bit of precision can be added & more data saved for a reduced storage cost; Additionally Traditional JPG used 8Bit per channel (24Bit) Colour pallet & we can solve a subtle colour differential in the pallet.

MP3 14Bit Wavelet; MPG4A used 16Bit wavelets; So wavelet precision improvement means a better audio experience.

Any form of Texture or Image or video type that traditionally saves to 8Bit, > 16Bit would see improvements:

Rollover Error High importance Error table:

Wavelet: 8Bit to 16Bit & more
Colour table
Colour Conversion
Colour Lookup Table : LUT

Down-Sampling & Up-Sampling.

Rupert S


Windows 3D Audio, DTS & Dolby Atmos should do to at least 32Bit 384Khz 7.1 Channels,

There is absolutely no reason a 64Bit processor cannot do 64Bit audio,
Mind you 32Bit Integer is around 60% of total CPU Support with 64Bit divided by 2,

So 32Bit Audio is 100% speed conformant & there are few reasons to reduce it to 24Bit or 16Bit without processing benefaction; Such as Error management on 24Bit on 32Bit instruction:

Both AMD & Intel X64

Rupert S 2022-11-30

"State-of-the-art approaches such as OpenMP and OpenCL"

FSR_FL RT: Proven

ML Training Telescope, Camera, Video & Image Display Enhancement, Produced 2 Hours ago! 2022-12-02

Sunday, November 20, 2022

The principle of the Bit'...' DAC (c)RS

The principle of the Bit'...' DAC (c)Rupert S

(yes since 1992)

To the world I presented the 1Bit DAC,

Principally it draws waves like a pencil by frequency; So 500Mhz DAC is great!

DAC 1Bit :

 . . .
. .. .. . .
 . ..

DAC 3Bit : Dithers/Interpolates the pattern with 3 Points per one & averaging

 . . .
. .. .. . .
 . ..

A Room Setup : 7.1 for example is 7, 1 Bit, 3Bit, 5Bit,More, DACs...

1 per Channel

We however place one more DAC between each channel to interpolate/Dither

3D Audio is up and down speaker DACs

ADC : Analog to digital conversion presents the analogue input into the matrix sum calculator, to collect the bits into groups along the lines of : 8Bits, 16Bits, 32Bits, 48Bits ....N-Bits

Right 1 Bit DAC works By two principles: (With Capacitor)

Vinyl output is varying frequency of a continuous analogue nature & essentially replication of frequency variance, Suitable for a single line instrument of almost infinite frequency variance, defined by the Crystal output Hz multiplier..

Vinyl output but we use a higher frequency than the output Hz & we interleave the frequency submission over multiple frequencies by a Hz factor : Base Hz = 48Kzh | DAC Frequency = 48Kzh * X | = Notes/Tones Per Hz

Interleaved frequency response.

We use capacitors to solve WATT related power drops from quiet instruments dominating another 1 Bit DAC on the same line.

SBC is our model; MPEG/Codec Banding:

52 Bands = 52 Pins | 52 Pins plus 10 band hopping double note 1Bit DAC = 64Bit,

64Bit 1Bit DAC Pins has all 52 Bands of SBC Covered in a pure note + 10 Band hoppers,

Alternatively 32Bands 1Bit DAC & 32Bit Hopper 1Bit DAC.

32Bit Hopper Analog 1Bit DAC = 32Notes continual (WOW)

Higher frequency DAC = Interleaved BIT, But it has to overlay every note but need less Bit.

Rupert S

Banding Monitor, TV & 3D technologies & Codecs: RS

The frequency response of the Video DAC is around 600Mhz.

The band estimate is in reference to various technologies & Codecs:

12Bands to 35Bands on SCART Cable with a 15Mhz to 100Mhz Clock,

20Bands to 60Bands VGA Port Digital

35 Bands to 250 Bands recommended VGA+ HDMI 1.4a to HDMI 2.1b

Each band consisting of blocks of data in : Data Width : 8Bit, 10Bit, 12Bit, 14Bit, 16Bit

This consists of a high colour & contrast; WCG & HDR Content.

Compression is advised.

Rupert S



(My work does not guarantee your product is GPL you may share with me) "State-of-the-art approaches such as OpenMP and OpenCL"

LC3Plus Source for HDMI & DisplayPort Proposal

Free to build!

You know you allow LC3Plus upto 500Kb/s? why not smash a load of
"terrible codecs" & make a upto 1Mb/s band or even better 1.3MB/s &
for DisplayPort & HDMI 7MB/s ...

Bound to be a few casualties to Van Brahms! Mastery!
& while you are at it, make 3D Audio specifications for Dolby & DTS Available!

Sure they would love it.

Be lovely!

"State-of-the-art approaches such as OpenMP and OpenCL"

Sunday, November 13, 2022

Variable Sensitivity Cable Technology

Variable Sensitivity Cable Technology (c)RS

USB & HDMI & DisplayPort & Cables Transmitting Data such as PCI & RAM,

High priority technology

(The actual cable can be any Voltage you need, higher V means faster transmitting & lots more errors) (c)Rupert S

Twisted pair cable sets for HDMI & DisplayPort & other cabling need a protocol that does more than Error correct from 2 to 5 tiny cables or twisted cables per pin! with error correction...

Can in base mode transmit more than one signal; By filtering data speeds.

Transmitting multiple wave lengths; Varying frequencies....

Each cable can have a wavelength polarity transmission using quartz timing crystals & transistor energizers (converting to the faster 5v, with a transistor & Crystal)

We can do the same for light port, Light port relies on higher frequency fiber optic cable connect..

The relative speed of a static pin in a PC is not too much of a problem, frequencies of static pins can be quite high; At least 500Mhz (Shielded),

Cables in motion however are the reason we need the cables to be as motionless as possible, So errors are static to Machine Learning & Error correction by statistical observation software & firmware.

We can however with a Twisting cable set & a single pin, Multiply the frequency transmission by using per cable selectivity with Quart's timing crystals, these do not need to be complex!

Allowing our cable PIN (DP,HDMI,USB Port for example(Static)) to multiply the frequency response by multiple cables per pin.

We can however; Multiply the error correction, By varying the output voltage along the side of the pin, By varying the resistance slightly with a 2 to 5 segment pin with tiny response differences regarding frequency or voltage.

We may indeed improve classic cable connects therefore by clearly defining each transmitted frequency...

Clearly separate..

But not a problem with compatibility.

We shall see!

Rupert Summerskill 2022-11-12

Sunday, November 6, 2022

Frame Expand GEN 3

Frame Expand GEN 3 - Pre Alpha Frame Prediction Motion Compensation Micro Flow Frame & Sharpen with Texture Preload & Removal (c)RS Development 2022

On the Subject for FSR3 & XeSS & ML & TV, Frame generation, Leveraging predict for video between 2 frames would work! H264, H265, VVC, AV1, VP9, DSC; Hardware Codecs all leverage predict!

Predict is an 8x8 Pattern & gets the basic ball rolling if you have 2 frames!

We can work on 3 : 5 : 8 frame predictions, Latency would be an issue! However by leveraging in what Quantum Computing calls : Undefined Future,

We prodigy based on texture locations in reference frame (Pre finalised) & the Defined first wave (output frame)

Frame reference Table for Predicted Interframe : { TV & GPU & Renderer }


Past Frame 3 }
Past Frame 2 }
Past Frame 1 } { Frame Series A }


Finalised previous frame with textures to clear,
Current to render Frame


Future frame series; Stable to probable : { 1 : 2 : 3 }

(c)Rupert S


C.P.C : Combined Prefetch & Cache : Frame Delta Predict Optimisation : RS

Prediction of frames between our stable frames makes a frame available that is based upon our knowledge of polygon & texture locations,

We do not have to base the prediction of video frame (DSC Codec example) upon simply motion,
We can also predict upon past frames to smooth output video frame rate/FPS,
For we almost always record video from the preceding frame.

We therefore can save 'Predict' for the video from our Past, Present & Future frames,
We create the Predict for the Frame & BFrame & Delta Frame with knowledge of future frames..

We have Future frames because we preload the planned Polygon & texture paths of the GPU Compute Units & Prefetch with Cache..

Combining both Prefetch (Cache) & Preframe generation optimisations & predictions.

We combine C.P.C with texture, animation & polygon load & unload with Predict for Video/DSC/Codec

We can also predict for frame based upon what we call textures & polygon's in a frame..
Because we regard the frames content as 3D or 2D saved into a frame or series of frames.

(c)Rupert S


Frame generation By shape & motion made simple: RS

A interframe with prediction (forward leaning) composes forward into the next frame...
B Frame (Quality prediction forward leaning) loaded wavelets to reuse

Vectors saved to frame (shows likely motion & audio sync)
Prediction Vectors & Systematic Stored Motion Vectors

This indicates which pixels will need to refresh and we can then start the data loading process & set refresh & leave a refresh pull to our display panel

Easing the burdens of frame generation & refresh: Table

(Audio & Video Sync properties & Prediction Vectors & Systematic Stored Motion Vectors)

Properties :

Predict motion,
Predict what moves (as in by colour & shape),
Predict 3D Motion in 2D with generalised reference material in 2D & 3D.

Prediction Vectors & Systematic Stored Motion Vectors

Colour properties:

Same colour + Predict Vector
Different colour : From source colour + Vector

Interframe generation (Requires 1 Frame latency, Save 2 frames & Predict 3rd),
Interframe generation latency reduction is to make frames faster (fps) initially & follow

Save while processing 2 frames a vector prediction for 1:2:3 Interframes,

Latency issues are covered by generating a faster initial frame rate for 3 seconds & following this though content.

(c)Rupert S


Video Codec Reference :

Easy Install Codecs:

Main interpolation references:

Interpolation Reference doc RS


FRC Calibration >
FRC_FCPrP(tm):RS (Reference)

FRC & AA & Super Sampling (Reference)

Audio 3D Calibration

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!

Rec709 <> Rec2020 ICC 4 Million Reference Colour Profile :

For Broadcasting, TV, Monitor & Camera

ICC Colour Profiles for compatibility:

Colour Profile Professionally


This one will suite Dedicated ARM Machine in body armour 'mental state' ARM Router & TV

Android & Linux ARM Processor configurations; routers & TV's upgrade files, Update & improve


Python Deep Learning: configurations

AndroLinuxML :

Linux :

Windows :