I have been using Julia to simulate calculations involving directed networks. Monte Carlo simulations(100 iterations) with a network with 100 nodes used to take 10mins. But the code doesn’t scale well, for a directed network with 500 nodes the same set of operations take 90 minutes. I am a new migra…

Can you supply a piece of code that shows this behaviour? It could be a memory issue. If you use the package BenchmarkTools.jl to run your main function it should show you how much memory was allocated. Perhaps for 500 nodes this value is larger than your physical memory?

I tried to optimize it in all ways possible (that I know of). The code is below, and any inputs on how to improve the same are welcome. using Pkg using Distributed using BenchmarkTools using JLD using Plots @everywhere using Distributions @everywhere using StatsBase @everywhere using LightGraphs …

g::SimpleDiGraph ; Make this g::SimpleDiGraph{Int64} or g::SimpleDiGraph{Int32}. Otherwise the type is not concrete. I recommend optimizing a single-threaded / sequential implementation first, and I recommend taking a look at Profile.@profile before posting here, and isolating the core issues of…

I have tried to use @profile, but as a beginner I find the output of the Profile.print() extremely hard to understand. I face the same issue with the benchmark tools. I have written the code after referring to several Julia resources for best coding practises.

Note that both Juno and ProfileView.jl can help you visualize your profiling results and make them more accessible.

I apologize for maybe sounding annoyed. In order to get better help here, I suggest you refactor a little. First, remove all @everywhere / multithreading / distributed annotations; single threaded performance needs to be optimized first. Second, you need to refactor the code you post here in order t…

Networks' Simulation

General Usage Performance

mauro3 May 21, 2019, 7:11am 4

Here’s how to quote code: PSA: how to quote code with backticks.

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