Both simulation for design verification and fault simulation in conjunction with automatic test pattern generation could take advantage of the possibility of moving the simulation time forward and backward. Up until now, rollback was allowed only by explicit backup/restore commands issued by the user. The paper presents a technique that makes possibles a "run for T" command, where T can be any time value, either positive or negative. It is based on an adaptive mechanism that automatically controls the parameters of an advanced network status recording system. A major feature is that the user may decide the maximum allowable overhead. Experiments show that the resulting rollback time is on the average very short, and therefore this technique can be efficiently used to improve sequential ATPG algorithms.
Adaptive technique for dynamic rollback in concurrent event-driven fault simulation / Farinetti, Laura; Montessoro, Pier Luca. - STAMPA. - (1993), pp. 576-582. (Intervento presentato al convegno Proceedings of the 1993 IEEE International Conference on Computer Design: VLSI in Computers & Processors tenutosi a Cambridge, MA, USA nel 1993) [10.1109/ICCD.1993.393311].
Adaptive technique for dynamic rollback in concurrent event-driven fault simulation
Farinetti, Laura;
1993
Abstract
Both simulation for design verification and fault simulation in conjunction with automatic test pattern generation could take advantage of the possibility of moving the simulation time forward and backward. Up until now, rollback was allowed only by explicit backup/restore commands issued by the user. The paper presents a technique that makes possibles a "run for T" command, where T can be any time value, either positive or negative. It is based on an adaptive mechanism that automatically controls the parameters of an advanced network status recording system. A major feature is that the user may decide the maximum allowable overhead. Experiments show that the resulting rollback time is on the average very short, and therefore this technique can be efficiently used to improve sequential ATPG algorithms.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2727563
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