This paper addresses the interconnection synthesis problem in microarchitecture-level designs. With emphasis on the speed of data movement operations, we propose algorithms that take into consideration the effect of each data-transfer-to-bus binding on the data transfer delay time. The delay time is calculated as a function of both data source load and data carrier (bus) load. By balancing loads among hardware components, the data transfer delay time (hence the total execution time) is shortened. We consider two types of problems: resource-constrained binding and performance-constrained binding. Two integer linear programming (ILP) formulations are derived to optimally solve the problems. In order to speed up the computation, a bipartite weighted matching method for the resource-constrained binding and a greedy merging method for the performance-constrained binding are also proposed. Both the ILP formulation generators and the heuristics have been programmed. Experimental results indicate that the proposed algorithms are indeed very effective in optimizing the performance aspect of the interconnection design.>

We propose a transformation-based scheduling algorithm for the problem given a loop construct, a target initiation interval and a set of resource constraints, schedule the loop in a pipelined fashion such that the iteration time of executing an iteration of the loop is minimized. The iteration time is an important quality measure of a data path design because it affects both storage and control costs. Our algorithm first performs an As Soon As Possible Pipelined (ASAPp) scheduling regardless the resource constraint. It then resolves resource constraint violations by rescheduling some operations. The software system implementing the proposed algorithm, called Theda.Fold, can deal with behavioral loop descriptions that contain chained, multicycle and/or structural pipelined operations as well as those having data dependencies across iteration boundaries. Experiment on a number of benchmarks is reported.>

The problem of scheduling a loop in a pipelined fashion such that the iteration time (turnaround time) is minimized, given a loop behavior, a target initiation interval, and resource constraints, is considered. The iteration time is an important quality measure of a data path design because of its direct correlation with both the storage and the control costs. The scheduler starts with performing as-soon-as-possible-pipelined (ASAP/sub p/) scheduling without regard to the resource constraint. It then resolves the resource constraint violations, if there are any, by repeatedly rescheduling some operations.>