I have a rather difficult model with binary variables and a quadratic (blinear) objective. I first tried running Gurobi 9.1.2 on my desktop, which has 4 cores, and it was progressing fairly nicely. Since I also have access to a large multi-core (in this case 32) computer, I decided to run it on that with exactly the same settings (the only non-standard setting I made was mipgap=0.10). It does much worse with 32 cores! For example, after looking at 56000 nodes in the B&B tree, the 4 core version has a gap of 20.7%, but the 32 core version has a gap of 28.1%. In addition, the 4 core version after examining only 2900 nodes finds an incumbent which is better than anything that the 32 core version has found after 426000 nodes. So, this tells me that just increasing the number of cores available has to be combined with some parameter changes, but which ones?
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