A global criticality/local phase driven algorithm for the constrained hardware/software partitioning problem

An algorithm for the constrained hardware/software partitioning (assignment and scheduling) problem is presented. The key feature of the algorithm is the adaptive objective mechanism governed by the combination of global and local measures. As hardware area minimization and latency constraints present contradictory objectives, a global time-criticality (GC) measure selects an objective function in accordance with feasibility. In addition to global consideration, local characteristics of the nodes are emphasized by classifying nodes into local phase (LP) types. A local phase 1 node (extremity) has an obvious preference for an implementation on the basis of its area/time requirements. A local phase 2 node (repeller) is a repeller to an implementation on the basis of relative preferences of other nodes. At each iteration, the global and local criteria are superimposed by a threshold mechanism so as to determine the best implementation. The algorithm has quadratic complexity in the number of nodes and has shown promising behaviour on the examples tested