How to distinguish between a CPU and a memory bottleneck? - c++

Question

I want to filter some data (100s of MB to a few GBs). The user can change the filters so I have to re-filter the data frequently.
The code is rather simple:
std::vector<Event*> filteredEvents;
for (size_t i = 0; i < events.size(); i++){
const auto ev = events[i];
for (const auto& filter : filters) {
if (filter->evaluate(ev)) {
filteredEvents->push_back(ev);
break;
}
}
if (i % 512 == 0) {
updateProgress(i);
}
}
I now want to add another filter. I can do that either in a way that uses more CPU or that uses more memory. To decide between the two I would like to know what the bottleneck of the above loop is.
How do I profile the code to decide if the bottleneck is the cpu or the memory?
In case it matters, the project is written in Qt and I use Qt Creator as the idea. The platform is Windows. I am currently using Very Sleepy to profile my code.

Answer 1

Intel vTune is a free graphical tool available for all of Windows and Linux and macOS. If you want something easy to set up, straightforward to read, and you're using Intel CPU, I'd say vTune is a good choice. It can automatically give you suggestions on where your bottleneck is (core vs memory).
Under the hood I believe Intel vTune is collecting a bunch of PMU (performance monitoring unit) counter values, LBR, stack information etc. On Linux, you are more than welcome to utilize the Linux Perf tool and collect performance stats for yourself. For example, using perf record + perf report in tandem tells you the hotspot of your application. But if you're concerned about other metrics, for example cache miss behavior, you'll have to explicitly tell perf what performance counter to collect. perf mem is able to address some of that need. But afterall, Linux Perf is a lot more "hard core" than the graphical Intel vTune, you better know what counter values to look for if you want to make good use of Linux Perf - sometimes one counter will directly give you the metric you want to collect, other times you have to do some computation on several counter values to get your desired metric. Use perf list to appreciate how detailed it can profile your machine and system's performance.