flamegraph VS heaptrack

You can install cargo-flamegraph with cargo install flamegraph. There are some underlying requirements to be able to use cargo-flamegraph; you will want to take a look at the repo here to make sure you have the right dependencies.

I tried to diagnose the issue with flamegraph, but unfortunately the flamegraph didn't show anything beyond the next call for some reason

having some tools to identify slowness origins (flamegraph is one... but not sure it's the way to go)

I'm currently implementing a solution for the first part of the day 16. It work but it is really slow... I'd like to : - understand why - having some tools to identify slowness origins (flamegraph is one... but not sure it's the way to go) - eventually have some clue/solution/idea - have general feedback on what in my "coding style" is not appropriate for rust (I come from java/kotlin/ts even if I've already coded a bit in c/c++) : for example I love iterator & sequence but i feel they are not really suited to overuse in rust (mostly because of async & result).

Use a profiler. Flamegraph is a good way to visualise profiler output. This lets you identify which functions are taking up a large amount of time - and hence helps you identify where to focus your optimisation efforts.

You tried trying to see what takes the most time under load via flames? https://github.com/flamegraph-rs/flamegraph

Well, in cases like that the answer is straight forward, use a profiler like https://github.com/flamegraph-rs/flamegraph

I don't see any obvious problems with your algorithm. I've had luck using cargo-flamegraph to identify the slow parts of my code. That's going to show you which parts to focus on improving the performance of!

From the readme of cargo flamegraph:

If we are talking replacing the libc allocator, then something like heaptrack is worth mentioning.

https://github.com/KDE/heaptrack

For accurate memory usage I prefer a memory profiler that overrides malloc and friends instead of the ones that probe the OS at regular intervals. You won't find memory spikes with the latter. Try heaptrack on Linux. I haven't found a good one for Windows yet.

I know it is not a profiler, but it is so criminally underrated that I decided to share it: https://github.com/KDE/heaptrack

If none of the above helps - I recommend heaptrack as a tool for tracking down your memory usage.

> memory leaks. It's surprisingly hard to find an easy to use memory leak detection tool.

I can vouch for heaptrack[1] nowadays, although it's pretty much Linux only. It's under the umbrella of KDE, but a heaptrack trace only requires a CLI app, and there is a nice Qt viewer to analyse the memory consumption.

It tracks the memory utilization at the level of malloc'd/free'd bytes. It's fine if your memory leak or other memory utilization problem is on this level. Recently I dealt with an issue, where increasing memory utilization was caused by fragmentation within the allocator. This didn't show up in heaptrack as an increasing memory utilization, but heaptrack still pointed out where most of the temporary allocations happened, leading to the culprit of the fragmentation.

[1] https://github.com/KDE/heaptrack

This is probably what you are looking for https://github.com/KDE/heaptrack

When I had this kind problems (heap related) I always use heaptrack. Take a look here for the details: https://github.com/KDE/heaptrack