Scheduling in high level synthesis using discrete evolutionary programming

Abstract

Scheduling is very important and critical part of high level synthesis. Quality of schedule rules the performance of chip in terms of cost and speed. Define Optimal schedule is a challenging and tedious task. This paper has proposed the concept of Integer Evolutionary Programming (IEP) which is extension and discrete version of Evolution Programming (EP) to handle the scheduling as a constraint optimization problem over the Integer Linear Programming (ILP) formulation of problem. Proposed method can apply over any complexity of problem easily and efficiently. Verification of developed algorithm has given over benchmark problem.