Analyze algorithmic time complexity of a simulation

ML-for-B-E / nevergrad

A Python toolbox for performing gradient-free optimization

https://facebookresearch.github.io/nevergrad/

MIT License

2 stars 0 forks source link

Open akouete-kpakpo opened 2 years ago

akouete-kpakpo commented 2 years ago

Linked to #19

A simulation takes several hours to run. The time complexity seems to be in

optimization budgets tested (the default problem tests budgets=[25, 50, 100, 200])
num_workers=[1, 30, 60]
optimizers=['NGOpt10', 'CMandAS2', 'CMA', 'DE', 'MetaModel']
irrigation problems: (the default problem tests 17 irrigation problems funcs = [Irrigation(i) for i in range(17)])

Analyze time complexity and see how we can run a meaningful simulation in the minimum time

akouete-kpakpo commented 2 years ago

@abiolaTresor could you work on this? Would be ideal to have some inputs before tomorrow.

Let me know if anything unclear.

akouete-kpakpo commented 2 years ago

@abiolaTresor could you give status on this issue? If you don't have time to work on it, I can take over?

akouete-kpakpo commented 2 years ago

@abiolaTresor I will unassign you as you're are working on more urgent task.