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Selectively Breaking Data Dependences to Improve the . . .

By Kaijie Wu and Ramesh Karri


Although algorithm level re-computing techniques can trade-off the fault detection capability vs. time overhead of a Concurrent Error Detection (CED) scheme, they result in 100% time overhead when the strongest CED capability is achieved. Using the idle cycles in the data path to do the re-computation can reduce this time overhead. However, dependences between operations prevent the re-computation from fully utilizing the idle cycles. Deliberately breaking some of these data dependences can further reduce the time overhead associated with algorithm level re-computing. According to the experimental results the proposed technique, it brings time overhead down to 0–60 % while the associated hardware overhead is from 12 % to 50 % depending on the design size

Year: 2003
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