A Memetic Algorithm-Based Design Space Exploration for Datapath Resource Allocation During High-Level Synthesis

摘要

System designers have started adopting high-level synthesis (HLS) for architectural design because of the higher levels of abstraction offered. The HLS tools provide multiple design choices with tradeoff among different design parameters. Design Space Exploration (DSE) involves optimizing the synthesis options to achieve best tradeoffs among the metrics of interest. With the aim of exploring the design space in a feasible amount of time, we present a novel automated DSE approach. In particular, meeting the constraints presented by different parameters of interest is modeled as a multi-objective problem and solved using Memetic algorithm. The effectiveness of different variations of the Memetic algorithm in solving the DSE problem is studied and a Firefly algorithm-based solution is proposed with a novel probabilistic local search mechanism. The proposed approach is compared with existing solutions and the results prove that the proposed approach outperforms both existing solutions and other variations of Memetic algorithms in terms of convergence time and quality of results. In addition to that, a case study has been included to demonstrate the applicability of the approach. Results show that the proposed approach achieves a 33% improvement in cost, 10 x improvement in speed and 4x improvement in hypervolume.