Area-Efficient Architectures for Large Integer and Quadruple Precision Floating Point Multipliers

Manish Kumar Jaiswal and Ray C.C. Cheung
Department of Electronic Engineering, City University of Hong Kong, Hong Kong.


Abstract

Large integer multiplication and floating point multiplication are the two dominating operations for many scientific and cryptographic applications. Large integer multipliers generally have linearly but high area requirement according to a given bit-width. High precision requirements of a given application lead to the use of quadruple precision arithmetic, however its operation is dominated by large integer multiplication of the mantissa product. In this paper, we propose a hardware efficient approach for implementing a fully pipelined large integer multiplier, and further extending it to Quadruple Precision (QP) floating point multiplication. The proposed design uses less hardware resources in terms of DSP48 blocks and slices, while attaining high performance. Promising results are obtained when compared our designs with the best reported large integer multipliers and also QP floating point multiplier in literatures. For instance, our results have demonstrated a significant improvement for the proposed QP multiplier, for over 50% improvement in terms of the DSP48 block usage with a penalty of slight additional slices, when compared to the best result in the literature on a Virtex-4 device.