Design of Double-Precision Fully-Programmable Computational Unit for FPGA and ASIC

Sajjad, M. and Yusoff, M.B.Z. and Ahmed, M. (2020) Design of Double-Precision Fully-Programmable Computational Unit for FPGA and ASIC. In: UNSPECIFIED.

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Abstract

The sensing algorithm of many high-precision sensors is implemented in Field Programmable Gate Arrays (FPGAs) because such devices meet most of the algorithm requirements. But to enhance sensors' performance, it is often required to compensate for their output against environmental variations. This compensation requires implementing polynomial functions in some variables corresponding to the environmental variations. This paper presents a low-cost design for double-precision, reusable, and flexible computational unit for implementing such polynomial functions in digital hardware. The design can be directly used for any FPGA and even for Application-Specific Integrated Circuit (ASIC) development. In the case of ASIC design, it also features the required flexibility to handle sensor to sensor polynomial variations. The design has been verified through simulation for different FPGAs and 350nm technology node ASIC. The design has also been implemented in Spartan-6 FPGA to compensate sensors' output in real-time. © 2020 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 3; Conference of 3rd International Conference on Computing, Electronics and Communications Engineering, iCCECE 2020 ; Conference Date: 17 August 2020 Through 18 August 2020; Conference Code:164385
Uncontrolled Keywords: Application specific integrated circuits; Computer software reusability; Field programmable gate arrays (FPGA); Functions; Polynomials, Computational units; Digital hardware; Double precision; Environmental variations; Fully programmables; Polynomial functions; Sensing algorithms; Technology nodes, Integrated circuit design
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 10 Nov 2023 03:27
Last Modified: 10 Nov 2023 03:27
URI: https://khub.utp.edu.my/scholars/id/eprint/12817

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