High-level macro-modeling and estimation techniques for switching activity and power consumption

We present efficient techniques for estimating switching activity and power consumption at the register-transfer level (RTL), using a combination of macro-modeling for datapath blocks, and control logic analysis techniques based on partial delay information. Previous work on estimating switching activity and power at the RTL has ignored the presence of glitches at various datapath and control signals. We demonstrate that glitches can form a significant component of the switching activity at signals in typical RTL circuits. In particular, for control-flow intensive designs, we show that the controller substantially affects the activity and power consumption in the datapath due to the presence of glitches at control signals. Since the final implementation of the controller is not available during high-level design iterations, we develop techniques that estimate glitching activity at control signals using control expressions and partial delay information. For datapath blocks that operate on word-level data, we construct piecewise linear models that capture the variation of output glitching activity and power consumption with various word-level parameters like mean, standard deviation, spatial and temporal correlations, and glitching activity at the block's inputs. For RTL blocks that operate on bit vectors that need not have an associated word-level value, we present accurate bit-level modeling techniques for glitching activity as well as power consumption. This allows us to perform accurate power estimation for control-flow intensive circuits, where most of the power consumed is dissipated in non-arithmetic components like multiplexers, registers, vector logic operators, etc. Experimental results on several RTL designs demonstrate the accuracy of the proposed estimation techniques. Our RTL power estimator produced estimates that were within 7% of those produced by an in-house power analysis tool on the final gate-level implementation, while being over 50 × faster than its gate-level counterpart.