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We have built a CPLEX model using the DoCPLEX wrapper in python. The model is quite a complicated one as the solution space is quite large. So we have kept a big time limit to let the model find a reasonable solution. In our local computers with i5 processor, the model seems to find a reasonable solution for the first objective after 20 minutes. So we thought to deploy the model on IBM cloud with highest settings (XL machine with 16 nodes). We then ran the model with the same data assuming it would find a solution faster as it is more powerful than the local machine. However, the model crashed as it ran into an out of memory error. What could be the possible reason and how do we fix this?