On the performance and energy efficiency of FPGAs and GPUs for polyphase channelization

Wideband channelization is an important and computationally demanding task in the front-end subsystem of several software-defined radios (SDRs). The hardware that supports this task should provide high performance, consume low power, and allow flexible implementations. Several classes of devices have been explored in the past, with the FPGA proving to be the most popular as it reasonably satisfies all three requirements. However, the growing presence of low-power mobile GPUs holds much promise with improved flexibility for instant adaptation to different standards. Thus, in this paper, we present optimized polyphase channelizations for the FPGA and GPU, respectively, that must consider power and accuracy requirements in the context of a military application. The performance in mega-samples per second (MSPS) and energy efficiency in MSPS/watt are compared between the two classes of hardware platforms: FPGA and GPU. The results show that by exploiting the flexible datapath width of FPGAs, FPGA implementations generally deliver an order-of-magnitude better performance and energy efficiency over fixed-width GPU architectures.