A Reconfigurable Hardware Architecture for Miscellaneous Floating-Point Transcendental Functions

Abstract

Transcendental functions are an important part of algorithms in many fields. However, the hardware accelerators available today for transcendental functions typically only support one such function. Hardware accelerators that can support miscellaneous transcendent functions are a waste of hardware resources. In order to solve these problems, this paper proposes a reconfigurable hardware architecture for miscellaneous floating-point transcendental functions. The hardware architecture supports a variety of transcendental functions, including floating-point sine, cosine, arctangent, exponential and logarithmic functions. It adopts the method of a lookup table combined with a polynomial computation and reconfigurable technology to achieve the accuracy of two units of least precision (ulp) with 3.75 KB lookup tables and one core computing module. In addition, the hardware architecture uses retiming technology to realize the different operation times of each function. Experiments show that the hardware accelerators proposed can operate at a maximum frequency of 220 MHz. The full-load power consumption and areas are only 0.923 mW and 1.40×104μm2, which are reduced by 47.99% and 38.91%, respectively, compared with five separate superfunction hardware accelerators.

Low-Power and Low-Latency Hardware Implementation of Approximate Hyperbolic and Exponential Functions for Embedded System Applications

“…There is a substantial amount of published material that describes the hardware implementation of these functions (exponential and hyperbolic). In general, there are five common types of computing methods for implementing these functions include the look-up table (LUT) approach [4], [5], the polynomial approximation methodology [6], [7], and the coordinate rotation digital computer (CORDIC) algorithm [8]- [11], Piecewise polynomial approximations [12]- [14] and Hybrid (table-driven) approaches [15], [16]. The approximate and stochastic computing approaches [17]- [20] have also garnered considerable interest in recent years.…”

Modification of Intertwining Logistic Map and a Novel Pseudo Random Number Generator

“…Researchers have proposed various hardware accelerators to implement transcendental function calculations, such as the CORDIC algorithm [23]. However, the CORDIC algorithm requires many iterations to achieve the required high accuracy [24]. There is no uniform standard for the realization of transcendental functions.…”