>> What techniques do people use to profile code where the core path takes <<1ms? Make a loop that runs the code 5000 times and time that. What do you mean by

>> What techniques do people use to profile code where the core path takes <<1ms? Make a loop that runs the code 5000 times and time that. What do you mean by "diffuse hot spots"? If a piece of code taking 1ms is called infrequently then optimizing it is not going to have a meaningful impact on your overall execution time. You can measure the time for longer running higher level functions that do a lot. If you then optimize some small function that's a leaf in the call graph, you can see the impact on the larger function - and it probably won't be much. One thing that can happen when nobody cares about performance is that every part of the code gets little inefficiencies and fixing any one of them has very little impact, but fixing ALL of them can be really significant. In that case you should start by profiling or timing the higher level functions and finding ones that have relatively small call trees that you can work on. Once you optimize one piece, the effects of optimizing others are a bit more significant because they are a larger part of overall execution time.