Power Optimization for Universal Hash Function Data Path Using Divide-and-Concatenate Technique

We present an architecture level low-power design technique called divide and concatenate for universal hash functions based on the following observations. (1) The power consumption of a w-bit array multiplier and associated universal hash data path decreases as O(w
⁴
) if its clock rate remains constant. (2) Two universal hash functions are equivalent if they have the same collision probability property. In the proposed approach, we divide a w-bit data path (with collision probability2
^-w
) into two/four w/2-bit data paths (each with collision probability 2
^-w/2
) and concatenate their results to construct an equivalent w-bit data path (with a collision probability 2
^-w
). A popular low-power technique that uses parallel data paths saves 62.10% dynamic power consumption incurring 102% area overhead. In contrast, the divide-and-concatenate technique saves 55.44% dynamic power consumption with only 16% area overhead.