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Abstract-This paper examines the hardware implementation trade-offs when evaluating functions via piecewise polynomial approximations and interpolations for precisions of up to 24 bits. In polynomial approximations, polynomials are evaluated using stored coefficients. Polynomial interpolations, however, require the coefficients to be computed on-the-fly by using stored function values. Although it is known that interpolations require less memory than approximations, but at the expense of additional computations, the trade-offs in memory, area, delay, and power consumption between the two approaches have not been examined in detail. This work quantitatively analyzes these trade-offs for optimized approximations and interpolations across different functions and target precisions. Hardware architectures for degree-1 and degree-2 approximations and interpolations are described. The results show that the extent of memory savings realized by using interpolation is significantly lower than what is commonly believed. Furthermore, experimental results on a field-programmable gate array (FPGA) show that, for high output precision, degree-1 interpolations offer considerable area and power savings over degree-1 approximations, but similar savings are not realized when degree-2 interpolations and approximations are compared. The availability of both interpolation-based and approximation-based designs offers a richer set of design trade-offs than what is available using either interpolation or approximation alone.

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We present a flexible hardware architecture for precise gamma correction via piece-wise linear polynomial approximations. Arbitrary gamma values, input bit widths, and output bit widths are supported. The gamma correction curve is segmented via a combination of uniform segments and segments whose sizes vary by powers of two. This segmentation method minimizes the number of segments required, while providing an efficient way for indexing the polynomial coefficients. The outputs are guaranteed to be accurate to one unit in the last place through an analytical bit-width analysis methodology. Hardware realizations of various gamma correction designs are demonstrated on a Xilinx Virtex-4 field-programmable gate array (FPGA). A pipelined 12-bit input/8-bit output design on an XC4VLX100-12 FPGA occupies 146 slices and one digital signal processing slice. It is capable of performing 378 million gamma correction operations per second.Index Terms-Displays, field programmable gate arrays (FPGAs), fixedpoint arithmetic, video signal processing.

Abstract-This paper presents a method for evaluating functions based on piecewise polynomial approximations (splines) with a hierarchical segmentation scheme targeting hardware implementation. The methodology provides significant reduction in table size compared to traditional uniform segmentation approaches. The use of hierarchies involving uniform splines and splines with size varying by powers of two is particularly well suited for the coverage of nonlinear regions. The segmentation step is automated and supports user-supplied precision requirements and approximation method. Bit-widths of the coefficients and arithmetic operators are optimized to minimize circuit area and enable a guarantee of 1 unit in the last place (ulp) accuracy at the output. A coefficient transformation technique is also described, which significantly reduces the dynamic ranges of the fixed-point polynomial coefficients. The hierarchical segmentation method is illustrated using a set of functions including Index Terms-Circuit synthesis, design automation, digital systems, field-programmable gate arrays (FPGAs), piecewise polynomial approximation.