Simulations, especially those running for extended periods, face challenges when executed on limited computing resources (e.g. a Jupyter Notebook). Often, these simulations may fail due to various constraints, necessitating a complete restart. This process can be time-consuming and inefficient. To address this, we propose the implementation of a feature that allows Simulatrex to save and resume simulations from intermediate states.
Problem:
Currently, when a long-running simulation encounters an issue or runs out of allocated compute resources, it fails entirely. Users must then restart the simulation from the beginning, leading to a significant waste of time and computational resources. This is particularly problematic for users who do not have access to high-end computing facilities and rely on limited resources.
Simulations, especially those running for extended periods, face challenges when executed on limited computing resources (e.g. a Jupyter Notebook). Often, these simulations may fail due to various constraints, necessitating a complete restart. This process can be time-consuming and inefficient. To address this, we propose the implementation of a feature that allows Simulatrex to save and resume simulations from intermediate states.
Problem: Currently, when a long-running simulation encounters an issue or runs out of allocated compute resources, it fails entirely. Users must then restart the simulation from the beginning, leading to a significant waste of time and computational resources. This is particularly problematic for users who do not have access to high-end computing facilities and rely on limited resources.