Speaking at SC17 in Denver this week, a panel of smart city practitioners shared the strategies, techniques and technologies they use to understand their cities better and to improve the lives of their residents. With data coming in from all over the urban landscape and worked over by machine learning algorithms, Debra Lam, managing director for smart cities & inclusive innovation at Georgia Tech who works on strategies for Atlanta and the surrounding area, said “we’ve embedded research and development into city operations, we’ve formed a match making exercise between the needs of the city coupled with the most advanced research techniques.”

Panel moderator Charlie Cattlett, director, urban center for computation & data Argonne National Laboratory who works on smart city strategies for Chicago, said that the scale of data involved in complex, long-term modeling will require nothing less than the most powerful supercomputers, including the next generation of exascale systems under development within the Department of Energy. The vision for exascale, he said, is to build “a framework for different computation models to be coupled together in multiple scales to look at long-range forecasting for cities.”