This paper proposes a high-speed architecture to realize two-variable numeric functions. It represents the given function as an edge-valued multiple-valued decision diagram (EVMDD), and shows a systematic design method based on the EVMDD. To achieve a design, we characterize a numeric function f by the values of l and p for which f is an l-restricted Mp-monotone increasing function. Here, l is a measure of subfunctions of f and p is a measure of the rate at which f increases with an increase in the dependent variable. For the special case of an EVMDD, the EVBDD, we show an upper bound on the number of nodes needed to realize an l-restricted Mp-monotone increasing function. Experimental results show that all of the two-variable numeric functions considered in this paper can be converted into an l-restricted Mp-monotone increasing function with p=1 or 3. Thus, they can be compactly realized by EVBDDs. Since EVMDDs have shorter paths and smaller memory size than EVBDDs, EVMDDs can produce fast and compact NFGs.

Numerical function generators (NFGs) realize arithmetic functions, such as ex,sin(πx), and , in hardware. They are used in applications where high-speed is essential, such as in digital signal or graphics applications. We introduce the edge-valued binary decision diagram (EVBDD) as a means of reducing the delay and memory requirements in NFGs. We also introduce a recursive segmentation algorithm, which divides the domain of the function to be realized into segments, where the given function is realized as a polynomial. This design reduces the size of the multiplier needed and thus reduces delay. It is also shown that an adder can be replaced by a set of 2-input AND gates, further reducing delay. We compare our results to NFGs designed with multi-terminal BDDs (MTBDDs). We show that EVBDDs yield a design that has, on the average, only 39% of the memory and 58% of the delay of NFGs designed using MTBDDs.