FPGA-Based Wordlength Optimization for DSP

Fixed-point representations are commonly used in DSP designs to efficiently use hardware resources. It is, however, a challenge to determine an appropriate fractional wordlength of all signals in order to reach a good balance between accuracy and hardware cost. Extensive simulations can be used to characterize a design and perform wordlength optimization (WLO), however, this tends to be slow when the DSP design is complex. FPGA emulation, which allows data to be streamed in hardware, is significantly faster than software simulation. We introduce an FPGA-accelerated WLO framework which utilizes a new WLO algorithm based on a tree-structured Parzen estimator developed for higher convergence speed. This framework is evaluated for three DSP designs; two finite-impulse response filters and one phase recovery design. The results show that our new WLO framework reduces the DSP accuracy evaluation time by a factor of 300–500 over simulation.