Abstract: To facilitate crosstalk analysis for an IC design, a plurality of input vectors are input into a gate-level simulation. In response, the gate-level simulation determines timing windows for all nets within the IC design, may perform aggressor pruning, and may then determine and output aggressor/victim pairs and associated features for the IC design. This gate-level simulation may be accelerated utilizing one or more graphics processor units (GPUs). Additionally, the aggressor/victim pairs and associated features for the IC design are then input into a trained machine learning environment, which outputs predicted delta delays for each of the aggressor/victim pairs. In this way, crosstalk analysis may be performed more accurately and efficiently.

Abstract: The IR drop for a portion of a circuit may include a voltage drop across resistance, and may include a product of current I passing through resistance with a resistance value R. In order to determine IR drop for a circuit in a more accurate and efficient manner, a neural network produces coefficient maps (that each indicate a time-varying distribution of power within an associated portion of the circuit), and these coefficient maps are then used by the neural network to determine an IR drop for each of a plurality of portions of the circuit.