Approximate Logic Synthesis Using BLASYS

TL;DR

This paper presents BLASYS, an open-source tool for approximate circuit synthesis using Boolean Matrix Factorization, enabling trade-offs between accuracy and design metrics like area and power.

Contribution

Introduction of BLASYS, a scalable method employing Boolean Matrix Factorization and partitioning for efficient approximate circuit synthesis.

Findings

Achieves 48.14% average area savings

Introduces 5% average relative error

Demonstrates effectiveness on multiple benchmarks

Abstract

Approximate computing is an emerging paradigm where design accuracy can be traded for improvements in design metrics such as design area and power consumption. In this work, we overview our open-source tool, BLASYS, for synthesis of approximate circuits using Boolean Matrix Factorization (BMF). In our methodology the truth table of a given circuit is approximated using BMF to a controllable approximation degree, and the results of the factorization are used to synthesize the approximate circuit output. BLASYS scales up the computations to large circuits through the use of partition techniques, where an input circuit is partitioned into a number of interconnected subcircuits and then a design-space exploration technique identifies the best order for subcircuit approximations. BLASYS leads to a graceful trade-off between accuracy and full circuit complexity as measured by design area. Using an open-source design flow, we extensively evaluate our methodology on a number of benchmarks, where we demonstrate that the proposed methodology can achieve on average 48.14% in area savings, while introducing an average relative error of 5%.