The paper describes the folding method of logic functions to reduce the size of memories to keep the functions. The folding is based on the relation of fractions of logic functions. If the logic function includes 2 or 3 same parts, then only one part should be kept and other parts can be omitted. We show that the logic function of 1-bit addition can be reduced to half size using the bit-wise NOT relation and the bit-wise OR relation. The paper also introduces 3-1 LUT's with the folding mechanism. A full adder can be implemented using only one 3-1 LUT with the folding. Multi-bit AND and OR operations can be mapped to our LUT's not using the extra cascading circuit but using the carry circuit for addition. We have also tested the mapping capability of 4 input functions to our 3-1 LUT's with folding and carry propagation mechanisms. We have shown the reduction of the area consumption when using our LUT's compared to the case using 4-1 LUT's on several benchmark circuits.

In this paper, a new heuristic algorithm is proposed to optimize the power domain clustering in controlling-value-based (CV-based) power gating technology. In this algorithm, both the switching activity of sleep signals (p) and the overall numbers of sleep gates (gate count, N) are considered, and the sum of the product of p and N is optimized. The algorithm effectively exerts the total power reduction obtained from the CV-based power gating. Even when the maximum depth is kept to be the same, the proposed algorithm can still achieve power reduction approximately 10% more than that of the prior algorithms. Furthermore, detailed comparison between the proposed heuristic algorithm and other possible heuristic algorithms are also presented. HSPICE simulation results show that over 26% of total power reduction can be obtained by using the new heuristic algorithm. In addition, the effect of dynamic power reduction through the CV-based power gating method and the delay overhead caused by the switching of sleep transistors are also shown in this paper.

In this paper, we present a low-power system for the de-quantization and inverse transform of HEVC. Firstly, we present a low-delay circuit to process the coded results of the syntax elements, and then reduce the number of multipliers from 16 to 4 for the de-quantization process of each 4x4 block. Secondly, we give two efficient data mapping schemes for the memory between de-quantization and inverse transform, and the memory for transpose. Thirdly, the zero information is utilized through the whole system. For two memory parts, the write and read operation of zero blocks/ rows/ coefficients can all be skipped to save the power consumption. The results show that up to 86% power consumption can be saved for the memory part under the configuration of “Random-access” and common QPs. For the logical part, the proposed architecture for de-quantization can reduce 77% area consumption. Overall, our system can support real-time coding for 8K x 4K 120fps video sequences and the normalized area consumption can be reduced by 68% compared with the latest work.