Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/19382
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dc.contributor.authorShende, Mrunalen_US
dc.contributor.authorMazumdar, Bodhisatwaen_US
dc.date.accessioned2026-10-15T11:52:26Z-
dc.date.available2026-10-15T11:52:26Z-
dc.date.issued2026-
dc.identifier.citationShende, M., & Mazumdar, B. (2026). Resource-Efficient Linear Decomposition of n-Input Majority Using Folded-bias Carry-Save Addition. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. https://doi.org/10.1109/TCAD.2026.3739000en_US
dc.identifier.issn0278-0070-
dc.identifier.otherEID(2-s2.0-105052237215)-
dc.identifier.urihttps://dx.doi.org/10.1109/TCAD.2026.3739000-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/19382-
dc.description.abstractEfficient decomposition of high-fan-in majority functions is important for logic synthesis and technology mapping. The expanded Hamming-weight-plus-threshold (HW+TH) baseline computes a Hamming-weight representation and then applies a separate threshold-add stage. This paper proposes a folded-bias carry-save addition (CSA) approach for decomposing odd n-input majority functions. For the majority threshold Tn = ⌈n/2⌉, the method selects w = ⌈log2(Tn)⌉ and folds the constant K = 2w − Tn into the CSA columns. The majority decision is obtained directly as the carry into column w, eliminating the separate threshold-add stage without materializing a standalone Hamming-weight word. The construction is proved correct and has linear structural size, while its depth and mapped delay are evaluated empirically. The proposed method is evaluated using generator-level arithmetic metrics, pre-mapping structural metrics, logic-synthesis flows, and FPGA implementation. For n ∈ {5, 7,..., 61}, it reduces the mean full-adder count by 28.73% and the mean initial k-LUT node count by 26.02% relative to the expanded HW+TH baseline. After light MIG optimization, the mean node count decreases by 5.07%. Under a common strong ABC+LUT6 flow, the mean LUT6 count decreases by 1.76%. Vivado synthesis on Artix-7 reports reductions of 4.46% in mean CLB-LUT count and 0.34% in mean datapath delay. Under a common two-input AIG normalization, Fiction QCA-ONE layouts reduce cell-layout footprint by 6.74%, quantum-dot cellular automata (QCA) cell count by 14.74%, and critical-path clock zones by 3.97%. These results show that folded-bias CSA reduction consistently provides a smaller structural starting network, while mapped area and delay outcomes remain target and synthesis-flow dependent. © 1982-2012 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systemsen_US
dc.titleResource-Efficient Linear Decomposition of n-Input Majority Using Folded-bias Carry-Save Additionen_US
dc.typeJournal Articleen_US
Appears in Collections:Department of Computer Science and Engineering

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