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Show me a single DAE solver in Haskell that has even come close to the performance we get in the Julia SciMLBenchmarks. Here's just one example. For Haskell pacakages, all I see are wrappers to GSL and Sundials, both of which are slow in comparison. So this is a 8.5x speedup over something that was already faster than what you could find in Haskell. Show me something with decent speed in DAEs or it's useless.
The example is applied to the right-hand side of a generated mass-matrix ODE (DAE) which is then solved using the adaptive time stepping methods of DifferentialEquations.jl. It's a test example that comes from the robotics / rigid body dynamics simulation groups (specifically interested in control) where they before were generating the governing equations with SymPy, and recently switched to try Symbolics.jl (and we got the example because of some performance issues that needed fixing). The comparison is with and without applying the code simplifier before solving. The table shows an average global induced error of 1e-12 when chopping off the 1e-11 * sin(x) terms and smaller. Thus there's nothing "competitive" against standard adaptive time stepping here: it's used to enhance the simulation of generated models that are simulated with the adaptive time steppers.
The example is applied to the right-hand side of a generated mass-matrix ODE (DAE) which is then solved using the adaptive time stepping methods of DifferentialEquations.jl. It's a test example that comes from the robotics / rigid body dynamics simulation groups (specifically interested in control) where they before were generating the governing equations with SymPy, and recently switched to try Symbolics.jl (and we got the example because of some performance issues that needed fixing). The comparison is with and without applying the code simplifier before solving. The table shows an average global induced error of 1e-12 when chopping off the 1e-11 * sin(x) terms and smaller. Thus there's nothing "competitive" against standard adaptive time stepping here: it's used to enhance the simulation of generated models that are simulated with the adaptive time steppers.