The Art of Beating the Odds with Predictor-Guided Random Design Space Exploration

TL;DR

This paper presents a predictor-guided random exploration method for MIG-based digital circuit synthesis, significantly accelerating the process and improving circuit quality, while revealing that higher prediction accuracy does not always lead to better results.

Contribution

It introduces a novel predictor-guided random exploration technique that enhances synthesis speed and quality in MIG-based digital circuit design.

Findings

Achieves up to 14x speedup in synthesis process.

Improves MIG minimization by up to 20.94% on benchmark suite.

Increased predictor accuracy does not necessarily improve results or speed.

Abstract

This work introduces an innovative method for improving combinational digital circuits through random exploration in MIG-based synthesis. High-quality circuits are crucial for performance, power, and cost, making this a critical area of active research. Our approach incorporates next-state prediction and iterative selection, significantly accelerating the synthesis process. This novel method achieves up to 14x synthesis speedup and up to 20.94% better MIG minimization on the EPFL Combinational Benchmark Suite compared to state-of-the-art techniques. We further explore various predictor models and show that increased prediction accuracy does not guarantee an equivalent increase in synthesis quality of results or speedup, observing that randomness remains a desirable factor.