An improved algorithm for in situ adaptive tabulation

In situ adaptive tabulation (ISAT) is a proven storage/retrieval method which efficiently provides accurate approximations to high-dimensional functions which are computationally expensive to evaluate. Previous applications of ISAT to computations of turbulent combustion have resulted in speed-ups of up to a thousand. In this paper, improvements to the original ISAT algorithm are described and demonstrated using two test problems. The principal improvements are in the table-searching strategies and the addition of an error checking and correction algorithm. Compared to an earlier version of ISAT, reductions in CPU time and storage requirements by factors of 2 and 5, respectively, are observed for the most challenging, 54-dimensional test problem.