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sidereus
searching PlanetScale…
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4 ms
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by
sidereus
9y ago
For QPs it looks like. Mosek works really well for SDPs. However, it converts QPs to SOCPs before solving them. This slows down a lot the timings.
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sidereus
9y ago
We compared our OSQP solver to other general-purpose solvers. That's why we chose GUROBI and Mosek. There are also examples of control problems for which it is possible to design very efficient tailored methods. However our point is no
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sidereus
9y ago
Haven't tried the MIQP extension against the QPLIB yet. It is just a prototype and it is written in Python. We first need to implement it in C to compare the timings.
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sidereus
9y ago
Which version of OSQP did you try for? 0.2 has improved a lot compared to previous versions (much better convergence behavior with adaptive rho). Even though OSQP can solve also LPs, it is optimized to solve QPs. You can find some benchmark
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sidereus
9y ago
OSQP solves only continuous QPs. For integer variables you need an MIQP solver. We wrote a Python branch-and-bound wrapper around OSQP to solve MIQPs: https://github.com/oxfordcontrol/miosqp However, there are more adv
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sidereus
9y ago
Yes! Cvxpy 1.0 now detects QPs and avoids the slow SOCP reduction. Also, it exploits OSQP to perform factorization caching and warm starting. If you solve parametric QPs in a sequence (e.g., lasso pareto frontier) the speedups are even bigg
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sidereus
9y ago
I am happy to compare IPOPT as well. There was a github issue for this: https://github.com/oxfordcontrol/osqp_benchmarks/issues/1 As I said there, the current IPOPT Python interfaces do not report the timings
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sidereus
9y ago
arXiv paper: https://arxiv.org/abs/1711.08013 benchmarks: https://github.com/oxfordcontrol/osqp_benchmarks It is the default LP/QP solver in cvxpy 1.0: https://github.com/cvxg
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Show HN: OSQP: a new first-order solver for large-scale quadratic programs
(osqp.readthedocs.io)
39 points
by
sidereus
9y ago
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20 comments
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sidereus
9y ago
Very interesting! It would be nice to integrate it into a professional music production tool.