As the integrated circuit industry enters the post-Moore era, the development direction of chips is gradually shifting from computing performance to energy efficiency. However, in the traditional von Neumann architecture, the process of data transferring between computing units and storage units consumes a lot of energy, limiting the energy efficiency of the chip. Memristor is an emerging non-volatile memory device, which can reduce the transmission overhead between computing and storage units and improving energy efficiency. This provides a new paradigm in “in-memory computing”. With the rapid increase in the scale of applications (e.g., neural networks) and the continuous innovation of material and fabrication process, memristor-based in-memory computing circuits and systems need to shorten the design cycle to achieve the co-optimization of devices, circuits, and systems. This tutorial presents a new way to further improve the current performance on Electronic Design Automation (EDA) software to handle large scale simulation and optimization problems with memristor devices. We first present the state-of-the-art EDA works in abstraction and optimization methods of memristor device, circuits, and systems. Then, we will present our contributions in these areas.