PORA: A Physarum-inspired obstacle-avoiding routing algorithm for integrated circuit design

Abstract The plasmodium of Physarum polycephalum, a large, amoeboid cell, has attracted much attention recently due to its intelligent behaviors in pathfinding, danger avoidance, and network construction. Inspired by the biological behaviors of this primitive organism, in this study, we explore the optimization capability of Physarum polycephalum systematically and present the first Physarum-inspired obstacle-avoiding routing algorithm for the physical design of integrated circuits. We simulate the foraging behaviors of Physarum polycephalum using a novel nutrition absorption/consumption mathematical model, thereby presenting an efficient routing tool called Physarum router. With the proposed routing approach, for a given set of pin vertices and a given set of on-chip functional modules, a rectilinear Steiner minimal tree connecting all the pin vertices while avoiding the blockage of functional modules can be constructed automatically. Furthermore, several heuristics including a divide-and-conquer strategy, a non-pin leaf node pruning strategy, a dynamic parameter strategy, etc., are integrated into the proposed algorithm to fundamentally improve the performance of the Physarum router. Simulation results on multiple benchmarks confirm that the proposed algorithm leads to shorter wirelength compared with several state-of-the-art methods.

[1]  Jeff Jones,et al.  Network Division Method Based on Cellular Growth and Physarum-inspired Network Adaptation , 2017, Int. J. Unconv. Comput..

[2]  Athanasios V. Vasilakos,et al.  Physarum Optimization: A Biology-Inspired Algorithm for the Steiner Tree Problem in Networks , 2015, IEEE Transactions on Computers.

[3]  Guolong Chen,et al.  DPSO-based Rectilinear Steiner Minimal Tree construction considering bend reduction , 2011, 2011 Seventh International Conference on Natural Computation.

[4]  Jeff Jones,et al.  Physarum machines imitating a Roman road network: the 3D approach , 2017, Scientific Reports.

[5]  D. T. Lee,et al.  Two algorithms for constructing a Delaunay triangulation , 1980, International Journal of Computer & Information Sciences.

[6]  Chris C. N. Chu,et al.  Fast and accurate rectilinear steiner minimal tree algorithm for VLSI design , 2005, ISPD '05.

[7]  Ian F. Akyildiz,et al.  On the Solution of the Steiner Tree NP-Hard Problem via Physarum BioNetwork , 2015, IEEE/ACM Transactions on Networking.

[8]  Cheng-Kok Koh,et al.  Manhattan or non-Manhattan?: a study of alternative VLSI routing architectures , 2000, ACM Great Lakes Symposium on VLSI.

[9]  Andrew Adamatzky,et al.  Practical circuits with Physarum Wires , 2015, ArXiv.

[10]  Zili Zhang,et al.  An intelligent physarum solver for supply chain network design under profit maximization and oligopolistic competition , 2017, Int. J. Prod. Res..

[11]  Marcus Brazil,et al.  Steiner trees for fixed orientation metrics , 2009, J. Glob. Optim..

[12]  Jeff Jones,et al.  Routing Physarum with Electrical Flow/Current , 2011, Int. J. Nanotechnol. Mol. Comput..

[13]  Ke Li,et al.  Slime mold inspired routing protocols for wireless sensor networks , 2011, Swarm Intelligence.

[14]  Andrew Adamatzky,et al.  Physarum machines: encapsulating reaction–diffusion to compute spanning tree , 2007, Naturwissenschaften.

[15]  Evangeline F. Y. Young,et al.  Generation of optimal obstacle-avoiding rectilinear Steiner minimum tree , 2009, 2009 IEEE/ACM International Conference on Computer-Aided Design - Digest of Technical Papers.

[16]  Qian Wan,et al.  A bio-inspired optimal network division method , 2019, Physica A: Statistical Mechanics and its Applications.

[17]  Guolong Chen,et al.  FH-OAOS , 2016, ACM Trans. Design Autom. Electr. Syst..

[18]  A Adamatzky,et al.  Routing Physarum with repellents , 2010, The European physical journal. E, Soft matter.

[19]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[20]  Chris C. N. Chu,et al.  FLUTE: Fast Lookup Table Based Rectilinear Steiner Minimal Tree Algorithm for VLSI Design , 2008, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[21]  Yong Deng,et al.  A Bio-inspired Network Design Method for Intelligent Transportation , 2019, Int. J. Unconv. Comput..

[22]  T. Nakagaki,et al.  Intelligence: Maze-solving by an amoeboid organism , 2000, Nature.

[23]  Athanasios V. Vasilakos,et al.  A Biology-Based Algorithm to Minimal Exposure Problem of Wireless Sensor Networks , 2014, IEEE Transactions on Network and Service Management.

[24]  Wei Qiu,et al.  Optimal approach on net routing for VLSI physical design based on Tabu-ant colonies modeling , 2014, Appl. Soft Comput..

[25]  Hai Zhou,et al.  EBOARST: An Efficient Edge-Based Obstacle-Avoiding Rectilinear Steiner Tree Construction Algorithm , 2008, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[26]  Toshiyuki Nakagaki,et al.  A mathematical model for adaptive vein formation during exploratory migration of Physarum polycephalum: routing while scouting , 2017 .

[27]  ObSteiner: An Exact Algorithm for the Construction of Rectilinear Steiner Minimum Trees in the Presence of Complex Rectilinear Obstacles , 2013, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[28]  M. Hanan,et al.  On Steiner’s Problem with Rectilinear Distance , 1966 .

[29]  Xia Li,et al.  An artificial bee colony algorithm for multi-objective optimisation , 2017, Appl. Soft Comput..

[30]  Chyi Hwang,et al.  A simple and efficient real-coded genetic algorithm for constrained optimization , 2016, Appl. Soft Comput..

[31]  Yong Deng,et al.  A Bio-Inspired Algorithm for Route Selection in Wireless Sensor Networks , 2014, IEEE Communications Letters.

[32]  Yu Hu,et al.  lambda-OAT: lambda-Geometry Obstacle-Avoiding Tree Construction With O(nlog n) Complexity , 2007, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[33]  Liang Li,et al.  Obstacle-avoiding rectilinear Steiner tree construction in sequential and parallel approach , 2014, Integr..

[34]  Sankaran Mahadevan,et al.  A Bio-Inspired Approach to Traffic Network Equilibrium Assignment Problem , 2018, IEEE Transactions on Cybernetics.

[35]  David S. Johnson,et al.  The Rectilinear Steiner Tree Problem is NP Complete , 1977, SIAM Journal of Applied Mathematics.

[36]  Joseph L. Ganley,et al.  Routing a multi-terminal critical net: Steiner tree construction in the presence of obstacles , 1994, Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94.

[37]  Chih-Hung Liu,et al.  High-performance obstacle-avoiding rectilinear steiner tree construction , 2009, TODE.

[38]  A. Tero,et al.  A mathematical model for adaptive transport network in path finding by true slime mold. , 2007, Journal of theoretical biology.

[39]  A. Tero,et al.  Minimum-risk path finding by an adaptive amoebal network. , 2007, Physical review letters.

[40]  Guolong Chen,et al.  Obstacle-Avoiding Algorithm in X-Architecture Based on Discrete Particle Swarm Optimization for VLSI Design , 2015, TODE.

[41]  Michail-Antisthenis I. Tsompanas,et al.  Evolving Transport Networks With Cellular Automata Models Inspired by Slime Mould , 2015, IEEE Transactions on Cybernetics.

[42]  Jianfeng Guan,et al.  A Novel Physarum-Inspired Routing Protocol for Wireless Sensor Networks , 2013, Int. J. Distributed Sens. Networks.

[43]  A. Tero,et al.  Rules for Biologically Inspired Adaptive Network Design , 2010, Science.

[44]  Seth Pettie,et al.  An optimal minimum spanning tree algorithm , 2000, JACM.