> whereas the scientist has to simulate the true physical equations. Every model of nature is an approximation. In high-performance computing, it is often a se

> whereas the scientist has to simulate the true physical equations. Every model of nature is an approximation. In high-performance computing, it is often a serious tradeoff where to "cut corners" to make the computation even feasible (e.g. - Which grid size or tesselation do we use? - Do we use a more regular grid to make use of optimizations or do we use a more irregular grid/tesselation for more precision at the places where it matters? - Do we use a simpler or more sophisticated model? - For multi-scale problems: do we compute each scale individually and combine the results? - etc.). EDIT: In my opinion the central difference to game development is that in science each such possible optimization where one might cut corners has to be deeply analyzed. Simply using an easy, pragmatic shortcut that "looks sufficiently good" is rarely possible in science.