A Parallelized Iterative Improvement Approach to Area Optimization for LUT-Based Technology Mapping

Modern FPGA synthesis tools typically apply a predetermined sequence of logic optimizations on the input logic network before carrying out technology mapping. While the "known recipes" of logic transformations often lead to improved mapping results, there remains a nontrivial gap between the quality metrics driving the pre-mapping logic optimizations and those targeted by the actual technology mapping. Needless to mention, such miscorrelations would eventually result in suboptimal quality of results. In this paper we propose PIMap, which couples logic transformations and technology mapping under an iterative improvement framework to minimize the circuit area for LUT-based FPGAs. In each iteration, PIMap randomly proposes a transformation on the given logic network from an ensemble of candidate optimizations; it then invokes technology mapping and makes use of the mapping result to determine the likelihood of accepting the proposed transformation. To mitigate the runtime overhead, we further introduce parallelization techniques to decompose a large design into multiple smaller sub-netlists that can be optimized simultaneously. Experimental results show that our approach achieves promising area improvement over a set of commonly used benchmarks. Notably, PIMap reduces the LUT usage by up to 14% and 7% on average over the best-known records for the EPFL arithmetic benchmark suite.