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The most common algorithm used in iterative decoding of low-density parity check (LDPC) codes is based on a generic class of the sum-product algorithm, which has a nonlinear dependence on the log(tanh()) function. The implementation based on fixed precision has substantial loss of accuracy and is computationally expensive with full precision. A suboptimal version of belief propagation called the offset-min-sum algorithm is generally used in hardware implementation. This paper proposes a generic scalable architecture for minimum search during check-node operation in the offset-min-sum algorithm applicable to regular as well as irregular LDPC codes with check node of any degree d. For an LDPC code with maximum check node degree d, the proposed architecture consists of 2(d-2) 2 × 1 multiplexers and 3(d-2) two-input compare-and-select units (CSUs). This has latency of [2⌈log2(d)⌉-2]tdc when ⌈log2(d)⌉-log2(d) <; log2(4/3) else [2⌈log2(d)⌉-3]tdc, with tdc representing the delay of a two-input CSU. The proposed architecture has been implemented for d = 20 using a TSMC 0.18-μm CMOS process.