tiny-differentiable-simulator VS tracy

I need differentiable rigid body dynamics because I want to do nonlinear MPC. One library that can do this is C++ is Tiny Differentiable Simulator https://github.com/erwincoumans/tiny-differentiable-simulator. As I understand it, this software uses a C++ auto-diff library and code generation to create CUDA kernels to compute fast derivatives in parallel. This seems pretty fast because it's C++. Another option is Brax https://github.com/google/brax. Brax uses JAX which I've never used, but from what I've seen online, JAX is popular for researchers and probably very good.

https://github.com/google-research/tiny-differentiable-simul...

Yes, Chrome about://tracing is great to visualize your custom timing data. Happy used for the last 5 years in Bullet and recent physics engines, including events across tracing multiple threads:

https://github.com/google-research/tiny-differentiable-simul...

Or our C++ and CUDA Tiny Differentiable Simulator: https://github.com/google-research/tiny-differentiable-simulator

Drake (and also tiny-differentiable-simulator that I know of) are using meshcat and it seems neat to me

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.