Abstract
Constrained random simulation is supported by constraint solvers integrated within simulators. These constraint solvers need to be fast and memory efficient to maintain simulation performance. Binary Decision Diagrams (BDDs) have been successfully applied to represent constraints in this context. However, BDDs are vulnerable to size explosions depending on the constraints they are representing and the number of Boolean variables appearing in them. In this paper, we present a word-level analysis tool DomRed to reduce the number of Boolean variables required to represent constraints by reducing the domain of constraint variables. DomRed employs static analysis techniques to obtain these reductions. We present experimental results to illustrate the impact of this tool.
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Keywords
- Boolean Variable
- Binary Decision Diagram
- Constraint Solver
- Boolean Combination
- Hardware Description Language
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
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Kitchen, N., Kuelhmann, A.: Stimulus generation for constrainted random simulation. In: ICCAD (2007)
Yuan, J., Shultz, K., Pixley, C., Miller, H., Aziz, A.: Modeling design constraints and biasing in simulation using bdds. In: ICCAD, pp. 584–590 (1999)
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© 2008 Springer-Verlag Berlin Heidelberg
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Kim, H. et al. (2008). Application of Formal Word-Level Analysis to Constrained Random Simulation . In: Gupta, A., Malik, S. (eds) Computer Aided Verification. CAV 2008. Lecture Notes in Computer Science, vol 5123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70545-1_46
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DOI: https://doi.org/10.1007/978-3-540-70545-1_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70543-7
Online ISBN: 978-3-540-70545-1
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