low power robust signal processing
Voltage scaling has proven to be very effective in reducing the power consumption of digital systems. However, voltage overscaling, ie., reducing the voltage below the critical voltage, introduces errors which have to be compensated by additional computations. In this paper, we propose the use of radix-2 redundant binary arithmetic (RBR) as an alternative for designing low power robust systems. We show that for large data widths, such systems have superior energy-delay product (EDP) and error performance compared to 2's complement based systems. However, for smaller data widths, the 2's complement system has better EDP performance, and in such cases, we propose a low complexity prediction technique to compensate for voltage overscaled errors. We evaluate the performance of the RBR system and the 2's complement system for two image processing kernels, namely, the Gaussian filter and DCT/IDCT. We show that the RBR system is the low power design choice for the Gaussian filter with 16 bits precision while the 2's complement system with most significant bit prediction is the low power design choice for the IDCT kernel.
redundant binary arithmetic algorithmic noise tolerance soft dsp