DAGON: technology binding and local optimization by DAG matching
DAC '87 Proceedings of the 24th ACM/IEEE Design Automation Conference
A new canonical form for fast boolean matching in logic synthesis and verification
Proceedings of the 42nd annual Design Automation Conference
DAG-aware AIG rewriting a fresh look at combinational logic synthesis
Proceedings of the 43rd annual Design Automation Conference
Improving constant-coefficient multiplier verification by partial product identification
Proceedings of the conference on Design, automation and test in Europe
Simulation and SAT-based Boolean matching for large Boolean networks
Proceedings of the 46th Annual Design Automation Conference
BooM: a decision procedure for boolean matching with abstraction and dynamic learning
Proceedings of the 47th Design Automation Conference
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As technology advances, there is an increasing need in the industrial domain for an algorithm that can map macro blocks. This type of algorithm would solve several front-end problems. For example, existing structural or functional algorithms cannot solve the challenge of mapping large-scale functions without boundary information. Fortunately, in practical problems, we only consider the target mapping functions that are the constructs of the datapath, and these macro blocks are easily recognized through their special arithmetic signatures. In this problem, the contestants need to design a mapping algorithm that recognizes macro blocks and replaces the mapped region with the macro blocks. Therefore, we can fairly evaluate the quality of the mapping algorithm as the size reduction of the revised netlist. Under our well-designed benchmarks, we will clearly differentiate the capability of proposed algorithms with several indexes. We look forward to triggering the academic area to investigate on this problem.