Ventilation with stratified air distribution is commonly used to improve building energy efficiency and indoor environment quality. A fast indoor airflow simulation can be useful for the ventilation design, performance evaluation, and model predictive ventilation control. As an intermediate model between computational fluid dynamics (CFD) and multizone models, a fast fluid dynamics (FFD) was proposed to balance simulation accuracy and computing speed. In this paper, we propose to further speed up the FFD simulation by using a computation reduction technique called in situ adaptive tabulation (ISAT). ISAT is a general function approximation method and was first proposed to speed up CFD simulation for combustion. Using ISAT, we are able to store the key FFD simulation data in a table and retrieve the data from the table for simulations with similar boundary conditions. This paper presents our ISAT-FFD implementation and some preliminary results. In a parametric study with 60,000 simulations, we showed that the ISAT-FFD simulation could compute the key indoor environment data for a natural convection flow at a speed up of 50 times faster than the FFD simulation and the prediction errors are within 1K. In the other case study, we showed that a trained ISAT-FFD model can predict the key environmental data by simply retrieving from the data table with controllable accuracy and little computing time. The ISAT-FFD can also properly handle the scenario when the independent variables are outside pre-trained data range.