Simulation acceleration of image filtering on CMOS vision chips using many-core processors

Abstract

This paper describes an efficient numerical solution to speed up transient simulations of analog circuits on a many-core computer. The technique is based on an explicit integration method, parallelised on a multiprocessor architecture. Although the integration step is smaller than the required one by traditional simulation methods based on Newton–Raphson iterations, explicit methods do not require to compute complex calculations such us matrix factorizations, which lead to long CPU simulation times. The proposed technique has been implemented on a NVIDIA GPU and has been demonstrated simulating Gaussian filtering operations performed by a CMOS vision chip. These type of devices, which are used to perform computation on the edge, include built-in image processing functions, turning them into very complex and time consuming circuits during their design. The proposed method is faster that Ngspice for different image sizes, and for 128 x 128 pixels image size it achieves a speed up of two orders of magnitude.