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

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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

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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
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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

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(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

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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

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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
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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

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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