Comments (2)
jalving
commented on August 12, 2024
1
Apologies for taking awhile to address this question.
Your understanding is mostly correct. For that paper, Plasmo is used to communicate the model structure to enable the use of PIPS-NLP which results in parallel speedups (using the PIPS-NLP schur decomposition strategy). When using IPOPT with Plasmo, the problem is converted and solved same way JuMP would solve it in serial (although Plasmo does provide a nice modular way to build the model).
Technically, Plasmo could be used to parallelize function and derivative computations for Ipopt. This is what is done in MadNLP.jl as described in this paper. We are currently working towards adding this capability to Plasmo directly.
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odow
commented on August 12, 2024
1
Cann be closed?
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Related Issues (20)
- How to insyall Plasmo in julia v0.6.4 HOT 2
- Using a solver other than Ipopt HOT 2
- Adding variables or objective to overall `OptiGraph` object HOT 1
- Docs link in Readme still points to Zavalalab HOT 1
- Modeling with many optinodes does not scale HOT 1
- `aggregate` throws an error for some OptiGraphs when `max_depth` > 0 HOT 1
- Optigraph set_objective is too slow HOT 1
- Quadratic objectives with variables on separate nodes is not supported HOT 1
- Calling `optimize!` on an expanded subgraph resets the solution of a different subgraph HOT 2
- `dual(subgraph, link_ref)` does not work like `value(subgraph, var_ref)` HOT 1
- `unset_binary` function does not work after `optimize!` is called HOT 1
- Retrieving callback data for lazy constraints fails HOT 5
- Does Plasmo.jl decompose solving process? HOT 2
- `dual` does not work on linkconstraints set after `optimize!` is called HOT 2
- Adding nodes to a subgraph after the main graph's backend is initialized does not reset graph backend HOT 1
- Setting `Max` instead of `Min` in objective makes `objective_value` negative HOT 2
- append_to_backend accesses private methods from MOI.Utilities HOT 3
- Can Plasmo be used for nested decomposition (in principle, at least)? HOT 4
- Aggregated graph backend does not update variables correctly HOT 1
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