Continual Hashing for Efficient Fine-grain State Inconsistency Detection [abstract] (IEEE Xplore, PDF)
Jae W. Lee, Myron King, and Krste Asanovic
Proceedings of the 2007 IEEE International Conference on Computer Design (ICCD), October 2007.
Transaction-level modeling (TLM) allows a designer to save functional
verification effort during the modular refinement of an SoC by reusing
the prior implementation of a module as a golden model for state
inconsistency detection. One problem in simulation-based verification
is the performance and bandwidth overhead of state dump and comparison
between two models. In this paper, we propose an efficient fine-grain
state inconsistency detection technique that checks the consistency of
two states of arbitrary size at subtransaction (tick) granularity
using incremental hashes. At each tick, the hash generates a signature
of the entire state, which can be efficiently updated and compared. We
evaluate the proposed signature scheme with a FIR filter and a Vorbis
decoder and show that very fine-grain state consistency checking is
feasible. The hash signature checking increases execution time of
Bluespec RTL simulation by 1.2% for the FIR filter and by 2.2% for the
Vorbis decoder while correctly detecting any injected state
inconsistency.