GPU programming for EDA with OpenCL
Proceedings of the International Conference on Computer-Aided Design
Fast static analysis of power grids: algorithms and implementations
Proceedings of the International Conference on Computer-Aided Design
Deterministic random walk preconditioning for power grid analysis
Proceedings of the International Conference on Computer-Aided Design
Proceedings of the 23rd ACM international conference on Great lakes symposium on VLSI
Voltage propagation method for 3-D power grid analysis
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
Scalable power grid transient analysis via MOR-assisted time-domain simulations
Proceedings of the International Conference on Computer-Aided Design
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Leveraging the power of nowadays graphics processing units for robust power grid simulation remains a challenging task. Existing preconditioned iterative methods that require incomplete matrix factorizations cannot be effectively accelerated on graphics processing unit (GPU) due to its limited hardware resource as well as data parallel computing. This paper presents an efficient GPU-based multigrid preconditioning algorithm for robust power grid analysis. By combining the fast geometric multigrid solver with the robust Krylov-subspace iterative solver, power grid DC and transient analysis can be performed efficiently on GPU without loss of accuracy (largest errors <;0.5 mV). Unlike previous GPU-based algorithms that rely on good power grid regularities, the proposed algorithm can be applied for more general power grid structures. Additionally, we also propose an accuracy-aware GPU performance modeling and optimization framework to automatically obtain the best power grid simulation configurations. Experimental results show that the DC and transient analysis on GPU can achieve more than 25X speedups over the best available CPU-based solvers.