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I would be happy to use languages like J/K or Julia for our actuarial projection simulations instead of C++. However, despite quicker development times, a factor of 2 in the runtime for our stochastic projections would be terrible. Has anyone experience with those languages in an HPC environment and can compare it to a C++ implementation?

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Dang, someone wanting to replace C++ with J... I'd love to say you could do this, since I am a big fan of J, but if you need to squeeze the last bit of efficiency out of a machine on a problem that can't be parallelized, C++ is probably a pretty good idea. If the "expensive in write time" logic isn't expensive in calculation time, you could wrap the expensive pieces in some verbs which call out to C.

I'm often surprised though; a naive implementation of wavelets in J was quite comparable in runtime performance to a naive implementation of wavelets in C.

Try numba in python. Its usually fortran fast and often faster than Julia.

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