Graduate Student Posters 2007

Author: Panos Vouzis

Monte Carlo Arithmetic (MCA) enables statistic experimentation with an algorithm during runtime for detection and mitigation of numerical anomalies. Previous studies of MCA have been limited to software floating point. This paper studies how MCA can be used in an FPGA implementation of the Logarithmic Number System (LNS), forming the Monte Carlo Logarithmic Number System (MCLNS). Simulation studies present how MCLNS affects the accuracy vs. performance of an Model Predictive Control (MPC) implementation, and synthesis results give an estimate of the cost of utilizing MCLNS in a Xilinx Virtex-IV FPGA.