Router Network Design Using Graph-Based Compactness Index
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Solution Overview
Problem
Modern integrated circuit design faces challenges in efficiently configuring router networks due to the large number of possible configurations, especially when multiple components are interconnected, making it difficult to determine an optimal router network design that minimizes path costs and maximizes communication efficiency.
Innovation Solution
A computer-implemented method is used to design a router network by generating an undirected graph representing candidate data routing elements, iteratively generating tree structures, computing compactness indices, and selecting nodes for connection based on these indices to establish candidate router networks, and calculating cost values to select the most efficient network configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a large number of data routing elements are used to connect multiple components, then communication flexibility and connectivity are improved, but the number of possible router network configurations increases exponentially, making it difficult to determine an optimal design
Solution Approach 1:
The patent transforms the router network design problem from a combinatorial configuration search into a continuous optimization problem by representing the network as a graph and using edge weights to represent communication costs. This parameter transformation allows the use of continuous mathematical optimization techniques rather than discrete configuration enumeration.
Solution Approach 2:
The patent replaces the traditional mechanical approach of manually configuring or enumerating router network topologies with an automated mathematical optimization system. By formulating the design as a convex optimization problem with cost functions and constraints, the system automatically determines optimal network configurations without exhaustive search.
2Manufacturing precision
If traditional exhaustive search methods are used to find optimal router network configurations, then solution optimality can be achieved, but the computational time and resources required become prohibitively large
Solution Approach 1:
The patent substitutes brute-force exhaustive search with mathematical optimization techniques. By formulating router network design as a convex optimization problem, the system achieves optimal solutions through efficient mathematical algorithms rather than exhaustive enumeration, dramatically reducing computational time while maintaining solution optimality.
Solution Approach 2:
The patent changes the problem representation from discrete configuration selection to continuous parameter optimization. By using edge weights, flow variables, and cost functions in a mathematical program, the system transforms an NP-hard combinatorial problem into a tractable convex optimization problem that can be solved efficiently.
Data Source
AI summary
A computer-method is provided for designing a router network to connect components of an integrated circuit, where the router network comprises a plurality of connected data routing elements. The method comprises generating an undirected graph to represent a mesh of candidate router elements, where the candidate data routing elements are positioned dependent on at least one characteristic of the integrated circuit. The undirected graph comprises a node to represent each candidate data routing element and an edge to represent each connection between the candidate data routing elements. A candidate router network generation process is then performed a plurality of times, where each performance of the candidate router network generation process comprises: generating a tree structure from a plurality of possible tree structures to interconnect the nodes of the undirected graph; for each node in the tree structure, computing a compactness index indicative of a path cost associated with connections to at least a subset of other nodes in the tree structure; for each component to be connected to the router network, identifying a set of available nodes within the tree structure and connecting the component to a selected node within that set taking account of the compactness index of the nodes within the set, to thereby establish a candidate router network; and computing a cost value for the candidate router network taking into account each pair of components that are to communicate with each other via the candidate router network. One of the candidate router network is then selected as the router network based on the computed cost value for each candidate router network.