Data driven signal processing: an approach for energy efficient computing

The computational switching activity of digital CMOS circuits can be dynamically minimized by designing algorithms that exploit signal statistics. This results in processors that have time-varying power requirements and perform computation on demand. An approach is presented to minimize the energy dissipation per data sample in variable-load DSP systems by adaptively minimizing the power supply voltage for each sample using a variable switching speed processor. In general, using buffering and filtering, the computation can be spread over multiple samples averaging the workload and lowering energy further. It is also shown that four levels of voltage quantization combined with dithering is sufficient to closely emulate arbitrary voltage levels.