Exploiting finite precision information to guide data-flow mapping

Advanced handheld applications are demanding for implementations of higher energy efficiency and higher performance. In typical implementations, the finite precision information is only known after fixed-point refinement, once the data-flow has been frozen. Instead, in this paper we suggest the propagation of finite precision information to drive data-flow transformations in order to achieve a higher mapping efficiency. Then, provided a flexible architecture with low run-time switching overhead, the data-flow under execution can opportunistically be tuned to provide the instantaneous computational accuracy required by the application. Thereby, the average number of operations and the precision of those is minimized. This principle is demonstrated with the implementation of the 128-point FFT present in a WLAN receiver. Compared to a conventional implementation, a reduction of 49% to 65% of the number of cycles can be achieved depending on conditions external to the receiver.