Open blegat opened 5 years ago
The following test may help in testing performance. It includes large non-convex QCQP feasibility problems from the power system domain, which can be solved with Ipopt. At the time of writing this model build times are similar in time to the solve time, about 2 seconds and 1 second respectively.
@mlubin did a quick review. He found type annoations and the @expression macro could provide a 20% performance boost, but thought that overall model build time is most likely related to this issue.
Closing this for a few reasons:
CrazyDict
is going to lead to more complexityOrderedDict
(reproducibility of expressions) which outweighs the performance concerns.I think in this case we're going to be unavoidably slower than 0.18, but that's a trade-off we made for using OrderedDict instead of pushing terms into a vector and then processing them later.
This came up again in https://github.com/jump-dev/JuMP.jl/issues/3729.
We should investigate other approaches for having a "small dict" as the backing data structure in AffExpr for the common case of an affine expression with one or two elements. (See MOI.Utilities.CleverDict for a related example.)
Creating small constraints like
is rather costly compared to JuMP v0.18. The reason is that creating a
OrderedDict
of two elements is a lot slower than creating aVector
of two elements:Maybe we could create a custom dict optimized for a small number of elements that would not create the internal dictionary if there is 2 elements or less.
That would avoid creating a dictionary for small number of elements.