Time Varying vs. Fixed Acceleration Coefficient PSO Driven Exploration during High Level Synthesis: Performance and Quality Assessment

The performance of particle swarm optimization ( PSO) greatly depends upon the effective selection of vital tuning metric known as acceleration coefficients ( especially when applied to design space exploration ( DSE) problem) which incorporates ability to clinically balance between exploration and exploitation during searching. The major contributions of the paper are as follows: a) A novel analysis of two variants of acceleration coefficient ( hierarchical time varying acceleration coefficient vs. constant acceleration coefficient) in PSO and their impact on convergence time and exploration time in context of multi objective ( MO) DSE in HLS. The analysis assists the designer in pre-tuning the acceleration coefficient to an optimal value for achieving better convergence and exploration time before DSE initiation; b) A novel performance comparison of PSO driven DSE ( PSO-DSE) with previous works based on quality metrics for MO evolutionary algorithms such as generational distance, maximum pareto-optimal front error, spacing, spreading and weighted metric. When two variants of acceleration coefficients ( constant and time varying) were compared, it was revealed from the results that the PSO-DSE has on average 9.5% better exploration speed with constant acceleration coefficient as compared to hierarchical time varying acceleration coefficient. Further, with setting of constant acceleration coefficient, the PSO-DSE produces results with efficient generational distance, maximum pareto-optimal front error, spacing, spreading and weighted metric as compared to previous approaches.