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Interval Arithmetic and Self Similarity Based Subthreshold Leakage Optimization in RTL Datapaths

Abstract : We propose top-down and bottom-up interval propagation techniques for identifying low leakage input vectors at primary inputs of an RTL datapath. Empirically, we observed self-similarity in the leakage distribution of adder/multiplier modules i.e., leakage distribution at the sub-space level is similar to that at the entire input space. We exploit this property to quickly search low leakage vectors. The proposed module library leakage characterization is scalable and is demonstrated on adders/multipliers. Given an RTL datapath, interval propagation is carried out with the low leakage intervals of the module instances with primary inputs. The reduced interval set is further processed with simulated annealing, to arrive at the best low leakage vector set at the primary inputs. Experimental results for various DSP filters simulated in 16 nm CMOS technology with top-down and bottom-up approaches yield leakage savings of 93.6 % and 89.2 % respectively with no area, timing, or control overheads.
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https://hal.inria.fr/hal-01383729
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Shilpa Pendyala, Srinivas Katkoori. Interval Arithmetic and Self Similarity Based Subthreshold Leakage Optimization in RTL Datapaths. 22th IFIP/IEEE International Conference on Very Large Scale Integration - System on a Chip (VLSI-SoC 2014), Oct 2014, Playa del Carmen, Mexico. pp.75-94, ⟨10.1007/978-3-319-25279-7_5⟩. ⟨hal-01383729⟩

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