Parallel Optical Image Computing Architecture
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Solution Overview
Problem
The von Neumann's "iconoscope memory" technology lacks coverage and technological range, particularly due to its reliance on pre-LCD cathode ray tube technology, and there is a need for a method that enhances the structural and functional use of direct image processing with increased performance.
Innovation Solution
A massive parallel digital image Computer Architecture (CA) is implemented, utilizing multiple nodes/servers with camera/image processing Universal Turing-machines, which converts digital images into binary form, processes them, and reorders them for efficient computation, leveraging quantum computing principles and electromagnetic wave-like "packets" for exponential performance gains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If von Neumann's iconoscope memory technology is used, then memory storage is achieved, but processing speed and technological range are limited due to reliance on pre-LCD cathode ray tube technology
Solution Approach 1:
The patent replaces the mechanical cathode ray tube system with an optical field-based processing system. Digital images are processed directly in the optical domain using light-speed operations, eliminating the need for electron beam manipulation and mechanical scanning inherent in iconoscope technology. This substitution enables processing at or near the speed of light while expanding technological capabilities to include optical computing operations.
Solution Approach 2:
The invention fundamentally changes the operating parameters from electron-based electrical signals to photon-based optical signals. By transitioning from electrical conductivity measurements to optical field manipulations, the system achieves dramatically higher processing speeds and enables new computational paradigms that were impossible with cathode ray tube technology.
2Productivity
If traditional sequential processing methods are used, then computation is performed, but processing performance is limited and cannot achieve exponential improvement
Solution Approach 1:
The patent segments the processing task across multiple independent optical fields and parallel computation paths. Instead of sequential processing, the system divides the computational workload into simultaneous optical operations that can be executed in parallel, achieving exponential performance improvement and dramatically reducing computation time.
Solution Approach 2:
The invention maintains continuous optical processing without the interruptions inherent in sequential electronic computation. By keeping the optical field continuously active and processing data streams without sequential bottlenecks, the system achieves sustained exponential processing performance and minimizes computation time.
3Quantity of substance
If digital images are converted to binary form using traditional methods, then data is processed, but memory efficiency and computing capacity are limited
Solution Approach 1:
The patent creates and processes optical copies of digital image data directly in the optical domain rather than converting to binary electronic form. This optical copying approach increases computing capacity by utilizing the parallel nature of light and improves memory efficiency by eliminating the overhead of binary conversion and electronic storage requirements.
Data Source
AI summary
A method of performing computation at or near the speed of light (typical) digital image-to-binary Computer Architecture (CA), which is the pixel or any “pixel”-like exponential-prone basis single “cell” in a digital image including numeric representation, and having the following steps referred to the digital images and their processing: conversion of (typical) digital images (9,1); impression memory (9.2); processing of numerical data/metadata (9.3); well-ordering recollection (9.4); well-ordering collection (9.5); reimpression memory (9.6); and programming processing of algorithms (9.7). The method of the invention that we choose to call U-Mentalism, imposes a massive parallel (typical) digital CA, settled on many nodes/servers camera/image processing Universal Turing Machines over Turing or computing machines (M), with many “films” made of many “frames” or “synthesis” of (digital) images. The consequences are exponential improvement in threading and computing capacity.