A power-efficient adaptive heapsort for fpga-based image coding application (abstract only)

This paper presents an adaptive heap sort architecture for an image coding implementation on FPGA, which specifically addresses the issue of sorting different amount of data located in each subband during the coding. The proposed sorting architecture is easily scalable. Performance of the sorter only depends on the amount of data sorted. The efficient usage of dual port memories yields high throughput up to 50 Msamples/s and their adaptive trigger/shutdown provide the average dynamic power reduction up to 20.9%. We designed this architecture and incorporated it in our Adaptive Scanning of Wavelet Data (ASWD) module which reorganizes the wavelet coefficients into locally stationary sequences for a wavelet-based image encoder. We validated the hardware on an Altera's Stratix IV FPGA as an IP accelerator in a Nios II processor based System on Chip. The architectural innovations can also be exploited in other applications that require high throughput and scalable sorting. Our experiments show that compared to an embedded ARM CortexA9 processor running at 666 MHz, our architecture at 100 MHz can provide around 13X speedup while consuming 242 mW average core dynamic power.