Calculation Device Vector Update for Optimization Speed
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Solution Overview
Problem
Existing calculation devices face challenges in efficiently solving optimization problems, particularly the Ising problem, with existing methods being slow and requiring extensive computational resources.
Innovation Solution
A calculation device is designed with a processing procedure that updates vectors iteratively, using a combination of first, second, and third updates to optimize vectors, allowing for binary and non-binary outputs, and incorporating a third vector to manage inequality constraints, enabling efficient solution of optimization problems without the need for Hessian matrix calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing calculation methods are used to solve optimization problems, then the problems can be solved, but the calculation speed is slow and computational resources are extensively required
Solution Approach 1:
The patent segments the optimization problem into multiple vector components (first vector x, second vector y, third vector u) that can be updated independently through separate update procedures. This segmentation allows parallel computation and reduces the computational burden on single processing units, thereby improving calculation speed while reducing overall computational resource requirements.
Solution Approach 2:
The patent implements dynamic update procedures where vectors are continuously refined through iterative calculations. The first vector is updated using the second and third vectors, the second vector is updated using the first vector, and the third vector is updated using the first vector. This dynamic approach allows the system to adaptively converge to solutions more efficiently than static methods, improving productivity without proportionally increasing computational resource consumption.
2Reliability
If existing calculation methods are used for optimization problems, then solutions can be obtained, but extensive computational resources are required
Solution Approach 1:
The patent divides the computational task into three distinct vector update procedures, each handling specific aspects of the optimization problem. This segmentation allows the system to maintain solution accuracy through specialized update rules for each vector while distributing computational resources more efficiently, thereby reducing overall resource requirements without sacrificing reliability.
Solution Approach 2:
The patent implements feedback mechanisms where each vector update incorporates information from other vectors. The first vector update uses both the second and third vectors, the second vector update uses the first vector, and the third vector update uses the first vector. This cross-vector feedback ensures that solution accuracy is maintained through continuous mutual refinement while avoiding redundant calculations that would increase computational resource consumption.
3Productivity
If traditional optimization methods are used, then optimization problems can be solved, but the calculation process is complex and time-consuming
Solution Approach 1:
The patent simplifies the calculation process by segmenting it into three clear, distinct update procedures, each with a specific function. This segmentation makes the overall complex optimization problem more manageable and easier to implement, reducing the perceived complexity while improving calculation efficiency through structured parallel processing capabilities.
Solution Approach 2:
The patent creates a universal calculation framework that can handle both binary and non-binary optimization problems through the same three-vector update mechanism. This multi-functional approach eliminates the need for separate specialized algorithms for different problem types, thereby improving calculation efficiency across diverse optimization problems without increasing process complexity.
Data Source
AI summary
According to one embodiment, a calculation device includes a processing device configured to perform a processing procedure. The processing procedure includes a first update of a first vector, a second update of a second vector, and a third update of a third vector. The first update includes updating the first vector using the second vector and the third vector. The second update includes updating the second vector using the first vector. The processing device is configured to output an output of at least one of the first vector obtained after repeating the processing procedure or a function of the first vector obtained after the repeating the processing procedure.