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DTSTART:19700308T020000
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DTSTAMP:20260730T152639Z
LOCATION:DAC Pavilion\, Exhibit Floor
DTSTART;TZID=America/Los_Angeles:20260728T170000
DTEND;TZID=America/Los_Angeles:20260728T180000
UID:dac_DAC 2026_sess295_ENGPOST475@linklings.com
SUMMARY:Cost-Based Partial Subgraph Matching for Circuit Pattern Recogniti
 on
DESCRIPTION:Ashutosh Jadhav, Xin Zhao, Ehsan Degan, and Vandana Mukherjee 
 (IBM Research)\n\nIdentifying recurring sub-circuits within large transist
 or-level designs is a common requirement in circuit analysis and verificat
 ion. Traditional approaches rely on exact subgraph isomorphism, requiring 
 identical structure and attributes between a pattern and a design. However
 , real designs often include small structural variations introduced by inc
 remental changes, optimizations, or renaming, causing exact matching metho
 ds to miss relevant instances and increasing manual analysis effort.\nThis
  work presents a scalable framework for partial subgraph matching that qua
 ntifies structural similarity rather than enforcing exact equivalence. Cir
 cuits are represented as attributed graphs, and matching is formulated as 
 an injective optimization problem using a cost-based graph edit distance. 
 The cost function captures label mismatches, unmatched nodes, and missing 
 or extra edges, enabling fine-grained assessment of near-miss matches. To 
 address the computational complexity of partial matching, the framework co
 mbines biased candidate subgraph sampling with an efficient approximation 
 strategy based on greedy initialization and iterative refinement.\nThe app
 roach produces ranked candidate matches along with detailed, interpretable
  difference reports that highlight structural deviations between circuits.
  Experimental results demonstrate predictable runtime scaling with candida
 te budget and consistent behavior across a range of circuit patterns. The 
 framework also establishes a foundation for automated tuning of cost param
 eters and learning-based candidate filtering.\n\nTopics: AI, Chiplet, Desi
 gn, EDA, Quantum, Security, Systems\n\n
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