Power Management Aware Low Leakage Behavioural Synthesis

Different power management techniques have been developed to target leakage-reduction at runtime of a design by orders of magnitude. To advance an optimization, different power modes and especially costs of state transitions have to be considered in early steps, e.g. during scheduling, allocation and binding of high-level synthesis. We present an operation scheduling, binding and allocation approach that includes different power modes into optimization to support an efficient power management. Our ILP-based scheduling performs an operation clustering and serves as a heuristic to minimize the amount of power state transitions. In the subsequent binding, operations are then bound to resources cluster-wise, which can be put to sleep states for longer continuous times. The evaluation shows that the high gain of power management (in our work power gating) is increased by up to further 31.1% compared to a high level synthesis approach that neglects power management during optimization. These leakage savings only base on synthesis improvements and do not introduce extra costs in terms of area or delay.