  eGPU, a recently-reported soft GPGPU for FPGAs, has demonstrated very high
clock frequencies (more than 750 MHz) and small footprint. This means that for
the first time, commercial soft processors may be competitive for the kind of
heavy numerical computations common in FPGA-based digital signal processing. In
this paper we take a deep dive into the performance of the eGPU family on FFT
computation, in order to quantify the performance gap between state-of-the-art
soft processors and commercial IP cores specialized for this task. In the
process, we propose two novel architectural features for the eGPU that improve
the efficiency of the design by 50\% when executing the FFTs. The end-result is
that our modified GPGPU takes only 3 times the performance-area product of a
specialized IP core, yet as a programmable processor is able to execute
arbitrary software-defined algorithms. Further comparison to Nvidia A100 GPGPUs
demonstrates the superior efficiency of eGPU on FFTs of the size studied (256
to 4096-point).
