# Memory Problem with JuMP and pmap

**URL:** <https://discourse.julialang.org/t/memory-problem-with-jump-and-pmap/102153>\
**Category:** Optimization (Mathematical)\
**Tags:** jump, distributed\
**Created:** [July 27, 2023, 12:36pm UTC](https://discourse.julialang.org/t/memory-problem-with-jump-and-pmap/102153 "2023-07-27T12:36:55Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![Mkloster](https://avatars.discourse-cdn.com/v4/letter/m/e0b2c6/32.png) [@Mkloster](https://discourse.julialang.org/u/Mkloster)\
**Post date:** [July 27, 2023, 12:36pm UTC](https://discourse.julialang.org/t/memory-problem-with-jump-and-pmap/102153/1 "2023-07-27T12:36:55Z")

</div>

Hallo,

i want to solve some JuMP models in parallel. For this i tryed using pmap from the Distributed libarary. Here you can see a simple example:

```julia
using JuMP, SCIP
using Distributed

addprocs(4)

@everywhere begin
    using Pkg
    Pkg.activate(".")
    using JuMP, SCIP
end
@everywhere function run_problem(model::JuMP.Model ,weight::Float64)

    set_objective_sense(model, JuMP.MIN_SENSE)
    set_objective_function(model, weight * model[:obj])

    optimize!(model)

    return JuMP.value(model[:obj])
end

model = JuMP.Model()

@variable(model, x[1:2], Int)
@expression(model, obj, -2 * x[1] - 3 * x[2])
@constraint(model, 4 * x[1] - 2 * x[2] >= 0)
@constraint(model, 2 * x[2] + 2 * x[1] ≤ 30)
@constraint(model, x[2] >= 0)
@constraint(model, 0.5 * x[1] + 3.75 - x[2] >= 0)

set_optimizer(model, SCIP.Optimizer)
set_silent(model)
@time begin
    for k in 1:100
        sol = pmap(run_problem, repeat([model], 100), ones(100))
    end
end

```

The problem is that the memory is not freed after calling pmap. If I increase the number of iterations the whole memory fills up.  
Thanks for your help and feedback

---

<div class="post-metadata">

**Author:** ![odow](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/odow/32/28685_2.png) [@odow](https://discourse.julialang.org/u/odow)\
**Post date:** [July 27, 2023, 1:12pm UTC](https://discourse.julialang.org/t/memory-problem-with-jump-and-pmap/102153/2 "2023-07-27T13:12:55Z")

</div>

Hi there, welcome to the forum.

Take a read of this tutorial: [Parallelism · JuMP](https://jump.dev/JuMP.jl/stable/tutorials/algorithms/parallelism/)

When working with JuMP models in parallel, you need to construct a model on each worker, rather than creating one and then passing it to the worker.

---

<div class="post-metadata">

**Author:** ![Mkloster](https://avatars.discourse-cdn.com/v4/letter/m/e0b2c6/32.png) [@Mkloster](https://discourse.julialang.org/u/Mkloster)\
**Post date:** [July 27, 2023, 1:40pm UTC](https://discourse.julialang.org/t/memory-problem-with-jump-and-pmap/102153/3 "2023-07-27T13:40:06Z")

</div>

It still needs more memory

```julia
using JuMP, SCIP
using Distributed
using BenchmarkTools

addprocs(8)

@everywhere begin
    using Pkg
    Pkg.activate(".")
    using JuMP, SCIP
end
@everywhere function run_problem(weight::Float64)

    model = JuMP.Model()

    @variable(model, x[1:2], Int)
    @expression(model, obj, -2 * x[1] - 3 * x[2])
    @constraint(model, 4 * x[1] - 2 * x[2] >= 0)
    @constraint(model, 2 * x[2] + 2 * x[1] ≤ 30)
    @constraint(model, x[2] >= 0)
    @constraint(model, 0.5 * x[1] + 3.75 - x[2] >= 0)

    set_optimizer(model, SCIP.Optimizer)
    set_silent(model)

    set_objective_sense(model, JuMP.MIN_SENSE)
    set_objective_function(model, weight * model[:obj])

    optimize!(model)

    sol = JuMP.value(model[:obj])
    # model =nothing
    # GC.gc()
    return sol
end

@benchmark begin
    kappa = 100
    local p = 1
    while p < kappa
        sol = pmap(run_problem, ones(100))
        sol = Nothing
        p += 1
    end
end

```