FWIW, I didn't bother getting too deep into an analysis (I was an undergrad and not really savvy enough to deep dive, but maybe I could now if I went back :) )
Our model was a space weather model of the solar wind speed and density - it was very iterative, and I think that iterative nature is what contributed to quirks in the transition - think of the issues when summing say, 0.1 ten times in Python (or other languages) - ultimately, we didn't need to do any real work to show that our converged model was within a margin of error and still presented the same results in terms of predicting solar flares - but it was still a lingering curiosity that the numbers weren't exactly the same (as you say!) - most of the work was done in finding the right compiler parameters to not break existing code, while taking advantage of the larger memory space.
Our model was a space weather model of the solar wind speed and density - it was very iterative, and I think that iterative nature is what contributed to quirks in the transition - think of the issues when summing say, 0.1 ten times in Python (or other languages) - ultimately, we didn't need to do any real work to show that our converged model was within a margin of error and still presented the same results in terms of predicting solar flares - but it was still a lingering curiosity that the numbers weren't exactly the same (as you say!) - most of the work was done in finding the right compiler parameters to not break existing code, while taking advantage of the larger memory space.