Thermoset polymers are an area of intense research due to their low cost, ease of processing, environmental resistance, and unique physical properties. The favorable properties of this class of polymers have many applications in aerospace, automotive, marine, and sports equipment industries. Molecular simulations of thermosets are frequently used to model formation of the polymer network, and to predict the thermomechanical properties. These simulations usually require custom algorithms that are not easily accessible to non-experts and not suited for high throughput screening. To address these issues, we have developed a robust cross-linking algorithm that can incorporate different types of chemistries and leverage GPU-enabled molecular dynamics simulations. Automated simulation analysis tools for cross-linking simulations are also presented. Using four well known epoxy/amine formulations as a foundational case study and benzoxazine as an example of how additional chemistries can be modeled, we demonstrate the power of the algorithm to accurately predict curing and thermophysical properties. These tools are able to streamline the thermoset simulation process, opening up avenues to in-silico high throughput screening for advanced material development.