optick VS tiny-differentiable-simulator

Does anyone here have experience with Optick: https://github.com/bombomby/optick ? It looks great but I haven't got the chance to try it. Was wondering how it compares to the other tools listed here.

As a free alternative, I've had multiple people recommend Optick, but I haven't had the chance to play around with it yet, so I can't vouch for it myself.

I have used Tracy to improve the performance of a latency sensitive application. The main advantage of this tool, in comparison to something like the Visual Studio profiler, is the fact that it can highlight the inter thread dependencies and synchronization between the threads. The other main feature, in my opinion, is the statistical tab that is associated to the recorded events: it can show the statistical distribution of the duration of all the invocations of functions and it allows to identify patterns in the performance of the application. Furthermore, a table can be used to sort the invocations of the functions and quickly jump to the point in time when the sample was recorded.

Other notable tools that implement a functionality similar to what is provided by Tracy are Optick https://github.com/bombomby/optick and Intel VTune (sadly specific to only Intel processors) in the Threading analysis.

we don't do systematic perf measurements beyond prod metrics but if we did the good tools are uiCA/IACA/etc, tracy/brofiler, perf/vtune

I highly recommend checking out Optick. I use it almost daily at work :)

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