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Selectively breaking data dependences to improve the utilization of idle cycles in algorithm level re-computing data paths

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2 Author(s)
Kaijie Wu ; Dept. of Electr. & Comput. Eng., Polytech. Univ., Brooklyn, NY, USA ; Karri, R.

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.

Published in:

Reliability, IEEE Transactions on  (Volume:52 ,  Issue: 4 )