Efficient power grid verification, critical in modern integrated circuits, is computationally demanding because of increasing grid sizes. Vectorless approach to grid verification estimates worst-case voltage noises without detailed evaluation of load current excitations. We study voltage noise assessment in RLC models of VDD and GND networks in integrated power grids. Transitory circuit behaviours are captured by transient constraints, while abstract grid model is utilized to accelerate convergence. Heuristics are proposed to extract constraints that restrict power consumption profiles to realistic scenarios. Bounds on voltage overshoots and undershoots are evaluated by formulating multiple optimization problems. We propose ways to mitigate storage and computational requirements on processing resources, enabling users to deploy computations on economical Cloud Computing platforms. Recommended solution is parallelizable, thereby reducing the overall verification time. Experimental results suggest that the proposed technique is practical and scalable for industrial grids.

Power grid (PG) simulation is critical for analysis and verification of power supply noises for robust and reliable integrated circuit (IC) designs. Computational demands to simulate PG for ICs with increasing complexity is never-ending. Cloud computing platforms can be leveraged to mitigate costs associated with making these resources available. However, since simulation data usually contains sensitive design information, simulating on third-party platforms lead to major security concerns. In this paper, we propose a framework for secure PG simulation on Cloud. A transformation algorithm to hide current excitations is presented, while still allowing a majority of computations to be completed on Cloud. We employ multiple compression strategies to significantly reduce communication overheads. Experiments show that our framework can achieve similar turn-around time as an insecure simulator on Cloud, while securing current excitations and output voltage vectors with reasonable communication and computational overheads.

Power grid (PG) simulation is critical for verification of supply noises in IC design. Computational demands for simulating PG is high. Cloud computing can be leveraged to mitigate these costs. However, simulating on third-party platforms lead to major security concerns. We propose a framework for secure PG simulation on Cloud. Multiple compression strategies are employed to reduce communication overhead. Turnaround time similar to an insecure simulator on Cloud can be achieved, while securing current excitations and output voltage vectors at reasonable costs.