An algorithm for trading off quantization error with hardware resources for MATLAB based FPGA design

ABSTRACT

Most practical FPGA designs of digital signal processing applications are limited to fixed-point arithmetic owing to the cost and complexity of floating-point hardware. While mapping DSP applications onto FPGAs, a DSP algorithm designer, who often develops his applications in MATLAB, must determine the dynamic range and desired precision of input, intermediate and output signals in a design implementation to ensure that the algorithm fidelity criteria are met. The first step in a flow to map MATLAB applications into hardware is the conversion of the floating-point MATLAB algorithm into a fixed-point version using "quantizers" from the Filter Design and Analysis (FDA) Toolbox for MATLAB. We describe an approach to automate the conversion of floating-point MATLAB programs into fixed-point, for mapping to FPGAs by profiling the expected inputs to estimate errors. Our algorithm attempts to minimize the hardware resources while constraining the quantization error within a specified limit.

• Hardware

  • Communication hardware, interfaces and storage

  • Integrated circuits

    • Logic circuits

  • Very large scale integration design