JuliaDynamics / JuliaDynamics/ABMFrameworksComparison
Use distributed computing (parallelization) in one of the models?
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Description
The discussion here https://discourse.julialang.org/t/ann-vahana-jl-framework-for-large-scale-agent-based-models/102024 made me realize: Agents.jl allows distributed computing straightforwardly when e.g scanning parameters or running a model several times with different seeds to get statistical convergence.
Yet, none of the comparisons here utilize this. Is this fair to us? Probably not. Should we modify one of the existing exaMPLES so that instead of running a model once, it runs 1000 models each with different rng seed? And each framework may use whatever (API declared) tools to accelarate this computation?
@Tortar thoughts?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Review the existing comparisons and exaMPLES, then read the linked Agents.jl discussion for the proposed benchmark approach. Determine which model should run 1000 seeds and which API-declared acceleration tools each framework can use; done means a defined, comparable distributed benchmark is implemented.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- distributed-systems, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100