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@MonssafToukal
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The goal of this PR is to allow the user to parallelize the evaluation of solvers when using the bmark_solvers(solvers, problems;...) method. It can be run in parallel locally or with any form of distributed computing backend supported by ClusterManagers.jl.

Currently, there are a couple of issues:

  • it does not work with CUTEst.jl problems
  • There is no doc for it. A code snippet can be added to the documentation.

A Dict{Symbol, DataFrame} of statistics.
"""
function bmark_solvers(solvers::Dict{Symbol, <:Any}, args...; kwargs...)
function bmark_solvers(solvers::Dict{Symbol, <:Any}, args...;parallel_eval=false, kwargs...)
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is this mandatory? what happens if we try to run the benchmarks in parallel and there is only 1 proc?

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it's mandatory to set parallel_eval=true if you want to benchmark in parallel. If you still have 1 proc, it won't do it in parallel. I added this keyword in case the user is handling multiple procs and does not want evaluate solvers in parallel. We could get rid of it it's not necessary.

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@dpo dpo Sep 6, 2022

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Ok we could leave it, at least for debugging, but let's set it to true by default.

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2 participants