A unified theory of timing budget management

This work presents a theoretical framework that optimally solves many open problems in time budgeting. Our approach unifies a large class of existing time-management paradigms. Examples include time budgeting for maximizing total weighted delay relaxation, minimizing the maximum relaxation and min-skew time budget distribution. We show that many of the time management problems can be transformed into a min-cost flow instance that can be optimally and efficiently solved through well-known combinatorial techniques. Experiments include mapping of several designs, which are implemented using parameterized CoreGen IP cores, on Xilinx FPGA devices. Different time budgeting policies have been applied during the mapping stage. Our time management techniques always improved the area requirement of the implemented testbenches compared to a widely-used path-based method. We also compared the maximum budgeting and fairness in delay budget assignments. Our experimental results show that an average improvement of 19% in area can be achieved when fairness and maximum budgeting policies are combined, compared to pure maximum budgeting.