# Repeated serialization for distributed simulation

**URL:** <https://discourse.julialang.org/t/repeated-serialization-for-distributed-simulation/24672>\
**Category:** General Usage\
**Tags:** question, statistics, economics, parallel, distributed\
**Created:** [May 28, 2019, 2:41am UTC](https://discourse.julialang.org/t/repeated-serialization-for-distributed-simulation/24672 "2019-05-28T02:41:38Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![nsna](https://avatars.discourse-cdn.com/v4/letter/n/838e76/32.png) [@nsna](https://discourse.julialang.org/u/nsna)\
**Post date:** [May 28, 2019, 2:41am UTC](https://discourse.julialang.org/t/repeated-serialization-for-distributed-simulation/24672/1 "2019-05-28T02:41:38Z")

</div>

I’m trying to maximize a likelihood function that involves a large number of simulations of a reasonably complex model. Serialization time is a bottleneck. Does anything jump out as being a problem?

Here is an example that captures the important part of my code, although I can’t be certain this is capturing the problem:

```julia
struct Observation
        X::Array{Float64,2}
        y::Array{Float64,2}
        d::Dict{Int,Float64}
        t::Array{Int64}
end

function logl(obs::Array{Observation,1},β::Array{Float64,1})
        out = @distributed (+) for ob in obs
                logl_i(ob,β) # perform simulation and return contribution to the likelihood
        return out
end

```

The code is spending 2/3 of the time serializing, and does so for each call to logl.

Is it the use of a custom struct to store the data? Could variation in the size of the objects in the struct be an issue?