gprof2dot VS tracy

It also lets you run tools like https://github.com/jrfonseca/gprof2dot on the profiling results to generate comprehensive flowcharts (call graph) for your program.

The closes thing I can think of is gprof2dot. It's used for visual representations after profiling code: https://github.com/jrfonseca/gprof2dot

There are a few tools to visualise the profile dumps. Some of them providing a full GUI for navigatig within your profiling results ( RunSnakeRun), some of them represent the analysis result as a Graph (gprof2dot). I stopped on snakeviz, which is a browser based visualizer. It is easy installed using pip install snakeviz, and then simply run with snakeviz profile_dir. The result looks something like this, and you can dive in to each of the visual parts to see its more close detalization, which is in my opinion is super cool and handy.

i don't really think there is _anything_ that comes even close to tracy https://github.com/wolfpld/tracy.

on top of this, given google's penchant for dumping projects aka abandonware, this would be an easy pass.

The RemedyBG debugger (https://remedybg.handmade.network/) and the Tracy profiler (https://github.com/wolfpld/tracy) both use Dear ImGui and so far I've only read high praise from people who used those tools compared to the 'established' alternatives.

For tools like this, programmers are also just "normal users", and from the developer side, I'm sure they evaluated various alternatives with all their pros and cons before settling for Dear ImGui.

Not the person you asked, but generally you might want to look at "frame-based" profilers. These are typically used in video games, but the concept is general, and can apply to other applications. The "frame" could also be something like a request or transaction being processed. I like Tracy[1], myself.

Another latency metric that you'll see, often w/respect to web apps and microservices is "P99" and similar. This is the amount of time in which 99% of requests get their response. For a higher percentile, you get a better idea of worst-case performance.

[1] https://github.com/wolfpld/tracy

I've not actually used Superluminal, but I use Tracy for similar reasons. It's free though (and, importantly, open source).

For profiling, you can check tracy.

You could try Tracy

There is no such thing as overengineering in fun projects, so I've also adopted Tracy as profiling solution. Works quite nice and gonna save me plenty of times in the future debugging performance spikes on badly optimized math heavy operations.

I know about tools such as tracing, jaeger or tracy. While having a complete tracing could be a potential solution, these tools don't work with no_std.