Specifications of data computations may not necessarily describe the ranges of the intermediate results that can be generated. However, such information is critical to determine the bit-widths of the resources required for a datapath implementation. In this paper, we present a novel approach based on interval computations that provides, not only guaranteed range estimates that take into account dependencies between variables, but estimates of their probability density functions that can be used when some truncation must be performed due to constraints in the specification. Results show that interval-based estimates are obtained in reasonable times and are more accurate than those provided by independent range computation, thus leading to substantial reductions in area and latency of the corresponding data-path implementation.
Carlos Carreras, Juan A. López, Octavio Nie