A cost function based optimization technique for scheduling in data path synthesis

A combinatorial optimization technique has been developed and applied to the scheduling problem in data path synthesis. The cost function is minimized using a gradient-like method, and constraints are satisfied by a new technique analogous to the combination of the penalty method and the feasible direction method used for nonlinear optimization. To overcome the drawbacks of assigning operations to control steps one at a time, this technique assigns all the operations to control steps simultaneously. Experimental results show that this method is as good as or better than other published methods