Accelerating Parameter Extraction of PSP MOSFET Model on SoC Platform

Abstract

In this paper, a novel approach to accelerate parameter extraction process of surface-potential-based (PSP) MOSFET model is presented for the submicron MOS transistor. To reduce the computational time, Field Programmable Gate Array (FPGA) implementation of PSP model library — SiMKit is demonstrated using Xilinx’s Zynq [Formula: see text] (Multi-processor System-on-Chip) platform. Parameter extraction is carried out using Particle Swarm Optimization (PSO) algorithm for 65[Formula: see text]nm technology nMOS devices. With the available measurement data, 32 various PSP model parameters are extracted. Experimental results validate the performance and accuracy of parameter extraction by achieving Root Mean Square Error below 10% for various current–voltage characteristics of nMOS device. 41.57% acceleration in execution time for extraction process is achieved by Zynq [Formula: see text] platform compared to the conventional computer-based software approach. In addition, various design optimization directives are explored, and their performances are compared as a part of RTL generation of SiMKit.