Improved heuristics for finite word-length polynomial datapath optimization

Polynomial datapath optimization using constraint solving and formal modelling

“…Even with the run-time optimizations described in Section IV, our algorithm takes considerably more time than [13]. This is not surprising, since we are comparing heuristic and exact algorithms.…”

“…In the first experiment, we have employed phase-shift keying (PSK) that is used in digital communication from [4], digital image rejection unit (DIRU), Degree-5 Filter (PFLT), multivariate cosine wavelet polynomial (MVCS), an anti-aliasing function (ANTI) [4], a Savitzky Golay filter (SG2) and Quadratic polynomial (QUAD) benchmarks and applied our method to the benchmarks listed in Table I as singleoutput polynomials. These benchmarks have been used in previous work on polynomial datapath optimization such as [13], [10]. We have synthesized the polynomials using a traditional logic synthesis tool in 0.25µm CMOS technology.…”

“…We compare the results of our approach to the one of [13] that has been shown to perform about 20% to 40% better than state-ofthe-art synthesis approaches. Even with the run-time optimizations described in Section IV, our algorithm takes considerably more time than [13].…”

“…Another algebraic method has been proposed in [12] and then improved in [13]. The main idea is similar to algebraic division techniques used in logic synthesis.…”

“…The presented paper abstracts the optimization heuristics in [12], [13] to employ a symbolic partitioning algorithm and to use formal methods to find a minimal factorization with respect to the cost function. The algorithm is later extended to work on multiple polynomials.…”