This thesis presents a RRAM-crossbar simulation framework aimed at precise and fast simulation.
Specifically, the model simulates a memristive crossbar with parasitic wire resistances, generating output currents and tracking the internal memristive states based on applied input voltages. Implemented in C++, the developed model has a clear interface making it suitable for integration into larger simulation frameworks for CIM-based accelerators. Experimental results demonstrate that the simulator is significantly faster than Cadence Spectre, while maintaining sufficient accuracy for use in behavioral-level CIM simulations.
The complete model is divided into three sub-modules: a memristor model, a linear crossbar model, and a non-linear crossbar model. The memristor model is based on the JART VCM v1b var model by Bengel et al. [2], and its implementation is a faithful translation of the associated Verilog-A code [3], with additional functionality for simulation in C++. Additionally, other memristor models can be implemented through an abstract memristor class.
Experimental results show that the developed simulation framework is significantly faster than Cadence Spectre while retaining a relative error below 1%. Additionally, the crossbar and the memristors are modeled to more closely reflect physical device behaviour than in other RRAM simulation frameworks. Finally, a study of linear and non-linear memristor simulation in a crossbar shows a measurable difference, suggesting approximating memristors as linear impacts simulation accuracy

In this work, we propose an IoT smart classroom framework which will be the base for smart classroom and hybrid teaching applications. The prototype introduces sensor readout capabilities, with which temperature, humidity, and loudness in a classroom can be monitored. Furthermore, the prototype introduces capabilities to collect and display measurements. Additionally, this prototype will assist an educator in a hybrid teaching setup by offering additional functionality, namely notifying the educator of online questions and giving an overview of environmental measurements in the classroom. With this prototype, the educator is able to control whether the students online are able to hear physically present students and vice versa. The prototype also introduces a way to notify the educator of any questions from students attending online. The goal of this prototype is to make the first steps to improve the hybrid teaching environment by reducing the workload on the educator and by making it easier for online students to interact with the educator. This prototype is split into three theses, focusing on sensor hardware, the Bluetooth mesh network, and the server respectively. This work will have a higher focus on designing and creating a server for this prototype, which will collect and display sensor measurements.