UWB Microwave Imaging for Breast Cancer Detection: Many-Core, GPU, or FPGA?

An UWB microwave imaging system for breast cancer detection consists of antennas, transceivers, and a high-performance embedded system for elaborating the received signals and reconstructing breast images. In this article we focus on this embedded system. To accelerate the image reconstruction, the Beamforming phase has to be implemented in a parallel fashion. We assess its implementation in three currently available high-end platforms based on a multicore CPU, a GPU, and an FPGA, respectively. We then project the results applying technology scaling rules to future many-core CPUs, many-thread GPUs, and advanced FPGAs. We consider an optimistic case in which available resources increase according to Moore's law only, and a pessimistic case in which only a fraction of those resources are available due to a limited power budget. In both scenarios, an implementation that includes a high-end FPGA outperforms the other alternatives. Since the number of effectively usable cores in future many-cores will be power-limited, and there is a trend toward the integration of power-efficient accelerators, we conjecture that a chip consisting of a many-core section and a reconfigurable logic section will be the perfect platform for this applicatio