C++ LIB 'zinc' Adurino prototype board firmware update :: MIT package(s) for 'Silicon life' engineering tools :: Concurrent; Embedded control systems, Core, Post-process, Networking, Full stack development, System bussing., Binary neural intelligence.
Is planned to become a part of as part of Grittith University - Nathan Open Source comtrubitation to MIT packages for my master thesis project, is an open-source development project hosted on GitHub under the Silicon Life ecosystem.
Via concurrency, 'zinc' and 'slif' libraries double the combined input and output efficiency with three "Threads; Input, Output, Task." Expect a united trio, making developer / editors protytype board(s). xilinx, Arduino, Raspberry Pi. All making boards for editors with multiple cores. PRAM Model and the BNI Thread for your custom BNI tasks. Such needed to fully test-bench a Concurrent Full Stack Development side for a Server inside a firmware Application.
Wi-Fi dual bandwidth each railed to an Interrupt Request Stack array, reading the bandwidth array, writing to the Bus loader for rail. Super computer injection and extraction on independent threads for task algorithms via concurrent I and O. Building concurrent rail systems as RTCOS (Real-Time-Concurrent-Operationg-System).
Wi-Fi 2.5 Input 64 pins, Wi-Fi 2.5 Output 64 pins, Wi-Fi 5 Input 64 pins, Wi-Fi 5 Output 64 pins.
The repository is officially marked as "UNDER DEVELOPMENT" and serves as a collection of full-stack concurrent programming packages.
The project contains architectural implementations centered heavily around high-concurrency, systems-level logic, and early-stage artificial intelligence:
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Concurrent Programming Tools: Implementations for full-stack concurrent pipelines, including custom mutex locks, mutex synchronization, and concurrent queues.
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Silicon Life Concepts: Targeted frameworks designed for "Silicon Life" computing architectures.
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Neural Networks: Repositories and logic patterns explicitly tagged for handling Artificial Neural Networks (ANN) and Binary Neural Networks (BNN).
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Packaged similar with respect to LWJGL, implementing 'generate; Program, Handle'. member functions.
- Google. (2026, 09 28). GitHub OpenAvril slif. Gemini AI search. (https://www.google.com/search?q=github+openavril+slif&rlz=1CDGOYI_enAU1216AU1216&oq=GitHub+OpenAvril+slif&gs_lcrp=EgZjaHJvbWUqBggAEEUYOzIGCAAQRRg7MgYIARBFGDwyBggCEEUYPDIGCAMQRRg8MgcIBBAhGKABMgcIBRAhGKABMgcIBhAhGKABMgcIBxAhGKABMgcICBAhGI8C0gEJMTU4ODRqMGo5qAIBsAIB4gMEGAEgXw&hl=en-GB&sourceid=chrome-mobile&source=chrome.ob&ie=UTF-8#lfId=ChxjMe).
The Silicon Life Project reverlates the field of digital electronics post epitome, which is what I bring after six year reduced hours. A master by coursework with five specialisation electives, I propose Convener of Masters of Engineering – Silicon Life Engineer; (1) Concurrent Embedded Control Systems, (2) Concurrency; Core, Post-Process., (3) Concurrent Networking, (4) Concurrent Bus Systems. (5) Concurrent Full Stack Development, (6) Hemesphoric Binary Neural Intelligence..
- 3x Zones: Id, Ego, SuperEgo.
- 2x Hemisphores; Left, Right. per Zone, and 'x' number of Junctions to all parts of the Hemisphore.
- [(x/2)^2 - (x/2)] number of Busses.
- Id : binary neural algorithms. : left hemisphore as self requested tasks, right hemisphore as communicated tasks; for 'slif_epicentre'.
- Ego : binary neural controls.
- Super-Ego : binary neural Directive Feng Shui Karmas.
slif_epicentre INJECTION paths:
- left hemisphore as self requested tasks.
- right hemisphore as communicated tasks.
- BOOLEAN states of "desire" = 'active', 'idle'., for all 'praise-Id' events.
- Scorpio - Trust in Truth.
- Sagittarius - Intellect in Intuition.
- Capricorn - Expression in Perception.
- Aquarius - Wisdom in Thought.
- Pisces - Flexible in Adapting.
- Aries - Assertive in Motivation.
- Taurus - Power in Momentum.
- Gemini - Adaptable in Intellect.
- Cancer - Comfort in Emotion.
- Leo - Manifestation in Thought
- Virgo - Interlect in Emotion.
- Libra - Balance in Harmony.
PSUDOCODE Repository : Binary Neural Intelligence - Java.
Exclusive Cohesion Mutex Queue:
CLIB Request, Wait, Write-Read for 'ThreadId' at 'DataCluster'.
Via concurrency, 'zinc' and 'slif' libraries double the combined input and output efficiency with three "Threads; Input, Output, Task." on Raspberry Pi & Arduino via respectivly.
System Bussing for Zinc Neural Hemisphoric Chip:
CLIB Concurrent System Bussing.
Open Concurrent SCADA.
Triple MutexQue into a set/get data buffer of bus for route of paired junctions.
MainStreamBussing: CLIB Compound of ExclusiveCohesionMutexQueue(s). An array of a single Bus with route array of Stations. A single Bus deploying an ExclusiveCohesionMutexQueue('AccessId_A=StationId','DataClusterId_A=BusId'), and each Station deploying an ExclusiveCohesionMutexQueue('AccessId_B','DataClusterId_B=StationId').
Left Hemisphore Task Launcher:
CLIB Request, Wait, Launch for 'ThreadId' at Server-Client.
Concurrency; Core, Post-Process.
Left Hemisphore Logic Task Result Deducer:
Consumer of spare threads.
Left Hemisphore Logic Task Result Deducer: CLIB Concurrent Server with independent task threads and IO wrapper.
TEMPLATE for user Compilation
- ThreadsLog: UNDER DEVELOPMENT
Neural Chip Thread Logging:
CLIB Console output via MutexQue, DataCluster is 'Console'.
- RightHemisphore: UNDER DEVELOPMENT
Wi-Fi hi and low bandwidth direct injection to a independent thread 'access-id (ThreadId)' of stemisphore.
version: Ubuntu 24.04.4 LTS.
Version: 2026.1.2.
sudo apt install git
sudo apt install build-essential
sudo apt install cmake
sudo apt install snapd
sudo snap install clion --classic
- Native Build Tools.
- Cmake.
- CLion C and C++.
- File - > New -> Project from Version Control.
- URL : user entry "https://github.com/OpenAvril/zinc"
*** Load Root CMake Project ***
cmake -B build
cmake --build build
*** run TESTBENCH ***
(1)A Binary Neural Intellijence in || with the following, while training and doing tasks.
// Networking I and O.
(2)B Networking into Core_Injection, double loop for I and O 1028 bytes,
// Shell - Server_Assembly.
(3)C Input_Scanner server interface input (concurrentTask(s)_5) into Core_Injection, I data for class Input,
(4)C Core_Injection,
// zinc_epicentre.
(5)D concurrentTask(s)_1,
(6)D concurrentTask(s)_2,
// Shell - Server_Assembly.
(7)C Core_Extraction into Ouput_Draw O data for class Output || Networking O 1028 bytes,
(8)C Ouput_Draw server interface output (concurrentTask(s)_6),
// SIMULATION I and O.
(9)E SIM_IN (concurrentTask(s)_3),
(10)E SIM_OUT (concurrentTask(s)_4).
thread => SIM_IN
(1) SIM_Input_SAMPLE (HandleId_SIM_Input_Sample_R-W-Buffer = MutexQue::generateHandle()),
thread => Input_Scanner || NETWORKING
(2) Input_Sample_Buffer (HandleId_Input_Sample_R-W-Buffer = MutexQue::generateHandle()),
thread => Core_Injection
(3) zinc_epicentre : Stack_of_Input (HandleId_Stack_of_Input_R-W-Buffer = MutexQue::generateHandle()),
thread => CONCURRENT
(4) zinc_epicentre : Stack_of_Output (HandleId_Stack_of_Output_R-W-Buffer = MutexQue::generateHandle()),
thread => Core_Extraction,
(5) Output_Sample_Buffer (HandleId_Output_Sample_R-W-Buffer = MutexQue::generateHandle()),
thread => Ouput_Draw || NETWORKING
(6) SIM_Output_SAMPLE (HandleId_SIM_Output_Sample_R-W-Buffer = MutexQue::generateHandle()),
thread => SIM_OUT
Copyright (c) 2026 King Brenton James Maddocks BEng(CompSys) - Emperor of Queensland to the King of the Commonwealth (echelon three).