Call Julia from Python using pyjulia, not multithreading
When I run julia 0.3.2 or 0.5 as standalone (mixing model) it uses all available kernels from my server so it was fast. (3M recording 800 sec)
j = julia.Julia()
juliaCode = ""
calcLME = j.eval(juliaCode)
result = calcLME(inputData)
If I call Julia from Python with pyjulia, I see that only one core is occupied by the python process (100% cpu) and all other cores are free. How do I get pyjulia / python to use all the available kernels of my server?
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