Savant: Automatic parallelization of a scheduling heuristic with machine learning

This paper investigates the automatic parallelization of a heuristic for an NP-complete problem, with machine learning. The objective is to automatically design a new concurrent algorithm that finds solutions of comparable quality to the original heuristic. Our approach, called Savant, is inspired from the Savant syndrome. Its concurrency model is based on map-reduce. The approach is evaluated with the well-known Min-Min heuristic. Simulation results on two problem sizes are promising, the produced algorithm is able to find solutions of comparable quality.