meta2meta

You should run Julia code directly to benchmark instead of calling it in Python through pyjulia.

Thank you for your hard work on SciML ecosystem and community, Rackauckas!

The new Modelica-like usage of ModelingToolkit.jl is really a game changer for acasual DAE system simulation in Julia. It makes composable hierarchical component-based simulation of large and complex system possible with pure Julia.

Based on full featured dynamic simulation capability and machine learning ecosystem (Flux.jl etc), Julia will be a perfect choice for reinforcenment learning research, where simulation and training process can all be implemented in pure Julia with promising performance. It delivers the promise of "solve two language problem" of Julia language.

Rackauckas has done a lot of work to create the whole scientific machine learning (SciML) ecosystem (with collaborators).

Symbolics.jl is the new step to a universal CAS tool in Julia to bridge the gap between symbolic manipulation and numerical computation

It is especially useful as a foundation for equation-based simulation package ModelingToolkit.jl. In the foreseeable future, I expect ModelingToolkit.jl can be comparable with the Modelica ecosystem to provide fast, accurate modeling and simulation capability and easy integration with machine learning methods for Julia ecosystem, which is crucial for engineering application and scientific research.

I see "#include <terark/fsa/cspptrie.inl>" in the "memtable/terark_zip_entry_index.cc" but I can't find "cspptrie.inl" in the repo. Is the code auto-generated or not open source now?