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GPU cards have been used for scientific calculations for many years. Despite their ever-increasing performance, there are cases where they may still have problems. This article addresses possible performance and memory issues and their solutions that may occur during GPU calculations of iterative algorithms. Specifically, the article focuses on the optimization of transient simulation of extra-large highly nonlinear time-dependent circuits in SPICE-like electronic circuit simulator core enhanced with NVIDIA/CUDA (Compute Unified Device Architecture) interface and iterative Krylov Subspace methods with emphasis on improved accuracy. The article presents procedures for solving problems that may occur during this integration and negatively affect either the simulation speed or the accuracy of the calculation. Finally, a comparison of the implementation of an iterative calculation procedure with the use of GPU cards, calculation by the direct method and calculation on the CPU only is presented.

GPU Accelerated Nonlinear Electronic Circuits Solver for Transient Simulation of Systems with Large Number of Components