BoxRouter 2.0: architecture and implementation of a hybrid and robust global router

Cho, Minsik; Lu, Katrina; Yuan, Kun; Pan, David Z.

doi:10.1109/iccad.2007.4397314

Cited by 13 publications

(4 citation statements)

References 25 publications

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“…Routing to minimize the total number of vertices used is NP-hard, but polynomialtime approximation algorithms exist [56]. In practice, heuristic routing algorithms scale to problem sizes much larger than current QA architectures [57,58,59,60,61].…”

Section: Routingmentioning

confidence: 99%

Solving SAT and MaxSAT with a Quantum Annealer: Foundations and a Preliminary Report

Bian

Chudak

Macready

et al. 2017

Lecture Notes in Computer Science

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Quantum annealers (QAs) are specialized quantum computers that minimize objective functions over discrete variables by physically exploiting quantum effects. Current QA platforms allow for the optimization of quadratic objectives defined over binary variables (qubits), also known as Ising problems. In the last decade, QA systems as implemented by D-Wave have scaled with Moore-like growth. Current architectures provide 2048 sparsely-connected qubits, and continued exponential growth is anticipated, together with increased connectivity.We explore the feasibility of such architectures for solving SAT and MaxSAT problems as QA systems scale. We develop techniques for effectively encoding SAT -and, with some limitations, MaxSAT-into Ising problems compatible with sparse QA architectures. We provide the theoretical foundations for this mapping, and present encoding techniques that combine offline Satisfiability and Optimization Modulo Theories with on-the-fly placement and routing. Preliminary empirical tests on a current generation 2048-qubit D-Wave system support the feasibility of the approach for certain SAT and MaxSAT problems. 1 Superposition is perhaps the best-known and most surprising aspect of quantum physics (e.g. the famous Scrödinger's cat which is both dead and alive prior to observation).

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Section: Routingmentioning

confidence: 99%

Solving SAT and MaxSAT with a Quantum Annealer: Foundations and a Preliminary Report

Bian

Chudak

Macready

et al. 2017

Lecture Notes in Computer Science

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“…The overflowcenter in the following (6) represents the total overflow of the 4 GRG edges connected the congestion center. The mdcenter in (6) stands for the Manhattan distance from the current GRG node to the congestion center. The trend cost is defined in (6).…”

Section: Omsms-mazementioning

confidence: 99%

“…The mdcenter in (6) stands for the Manhattan distance from the current GRG node to the congestion center. The trend cost is defined in (6). It costs more when the searching trend is forward to the congestion center than backward to.…”

Section: Omsms-mazementioning

confidence: 99%

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BU-Router: Researching on Techniques of Global Router

Zhang

2014

AMM

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Variety of routing approaches are employed by global routers in the VLSI circuit designs. Rip-up and reroute, as a conveniently implemented method, is widely used in most of modern global routers. Maze algorithm is always performed iteratively as the final technique to eliminate overflow. Maze algorithm and its ramifications can obtain an optimum solution. However, it will cost much CPU time if being used impertinently. In this work, we present a global router called Bottom-Up Router (BU-Router), with an optimized maze algorithm, which is based on multi-source multi-sink maze. BU-Router processes not the nets but the segments of nets in a sequence ordered by the length. In the progress, segments will be fixed on the global route graph edge, when the edge is saturated, which is as the basis, also known as bottom. Then the edge will be set as a blockage, which wont accept path goes through it any more. This means the edge will push the possible congestion in the future. Besides this, BU-Router optimized cost function in two ways: make the function adaptive and congestion center avoidable. Additionally, a specific optimized maze algorithm is proposed for routing a long distance segment so as to reduce the run-time.

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Global Routing Optimization Analysis based on Deep Reinforcement Learning

Chen,

Cheng

2024

2024 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)

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BoxRouter 2.0: architecture and implementation of a hybrid and robust global router

Cited by 13 publications

References 25 publications

Solving SAT and MaxSAT with a Quantum Annealer: Foundations and a Preliminary Report

Solving SAT and MaxSAT with a Quantum Annealer: Foundations and a Preliminary Report

BU-Router: Researching on Techniques of Global Router

Global Routing Optimization Analysis based on Deep Reinforcement Learning

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