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DTSTAMP:20240626T180034Z
LOCATION:Level 2 Lobby
DTSTART;TZID=America/Los_Angeles:20240626T180000
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UID:dac_DAC 2024_sess237_RESEARCH1681@linklings.com
SUMMARY:Solving Maximum Flows of Undirected Graphs by Minimizing s-t Effec
 tive Resistances of Electrical Networks
DESCRIPTION:Work-in-Progress Poster\n\nAli Aghdaei (Stevens Institute of T
 echnology), Kuilin Zhang (Michigan Technological University), and Zhuo Fen
 g (Stevens Institute of Technology)\n\nWe introduce a practically efficien
 t algorithm for approximating maximum flows in large undirected graphs bas
 ed on the recent high-performance spectral algorithms. Our approach exploi
 ts a resistor-network optimization framework that can be further accelerat
 ed by leveraging nearly linear-time graph Laplacian solvers. By iterativel
 y sizing up highly-congested edges and sizing down the edges with high eff
 ective s-t resistance sensitivities, approximate maximum flows can be obta
 ined in a highly-efficient manner. The proposed method also has been exten
 ded for solving multi-commodity flow problems. We demonstrate the effectiv
 eness and efficiency of the proposed approach by comparing it with the pri
 or state-of-the-art methods on IBM VLSI benchmarks and other public-domain
  networks such as social networks.\n\nTopic: AI, Autonomous Systems, Cloud
 , Design, EDA, Embedded Systems, IP, Security
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