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Speed up the solver() #70
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Hi @lemon234071, It depends on the solver that you choose. To reduce computation time is better to use a commercial solver like GUROBI, CEPLEX or MOSEK. All of them offer academic licenses, but personally I prefer MOSEK because its academic license is less restrictive and also supports all kind of cones. On the other hand, for linear models GUROBI is a little faster in academic version but has more restrictions in the number of variables and constraints. Best, |
I found that the rp.Portfolio() has the default self.solvers = ["ECOS", "SCS", "OSQP", "CVXOPT"]. |
I use these solvers by default because are open source and are installed by default with CVXPY. |
Thank you first, i just tried MOSEK with just pip install MOSEK . It faster but it return the None solution while other solvers return a weights.... |
It's because you need a valid license. In riskfolio-lib install instructions are the links to get an academic license. |
Thank you very much i ll try it. |
It works thank you very much, btw, did you try the Cvxpylayers on GPU? Would it be faster??? |
No, I didn't try cvxlayers. I use a Macbook air, so I don't have a GPU to try cvxlayers, but based on the information I read on papers, blogs and forums; commercial solvers like GUROBI, CPLEX, XPRESS and MOSEK are the best. |
Thank you very much! |
Hello there, me again! Thank you for your time first! I still have some problems with the speed: 1, With constraints "upperlng“ and “nea”, my problem should be solved with numerical methods. My sincerest thanks! |
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Is there any method to make the solve() faster, for example to use multi cpu or gpu?
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