KernelAbstractions.jl VS Agents.jl

For myself, I use Julia to write my own software (that is run on AMD supercomputer) on Fedora system, using 6800XT. For my experience, everything worked nicely. To install you need to install rocm-opencl package with dnf, AMD Julia package (AMDGPU.jl), add yourself to video group and you are good to go. Also, Julia's KernelAbstractions.jl is a good to have, when writing portable code.

>Higher level abstractions

like these?

https://github.com/JuliaGPU/KernelAbstractions.jl

For kernel programming, https://github.com/JuliaGPU/KernelAbstractions.jl (shortened to KA) is what the JuliaGPU team has been developing as a unified programming interface for GPUs of any flavor. It's not significantly different from the (basically identical) interfaces exposed by CUDA.jl and AMDGPU.jl, so it's easy to transition to. I think the event system in KA is also far superior to CUDA's native synchronization system, since it allows one to easily express graphs of dependencies between kernels and data transfers.

We mean the standard "agent based model" https://www.pnas.org/doi/10.1073/pnas.082080899, https://en.wikipedia.org/wiki/Agent-based_model . The kind of thing you'd use Agents.jl for. For example, look at agent-based infection models. In these kind of models you create many individuals (agents) with rules. Each agent moves around, but if one is standing near an agent that is infected, there's a probability of infecting the nearby agent. What is the average percentage of infected people at time t?

Jullia has packages too.

Agent-based modeling looks like an interesting topic, something ripe for fun little side projects. The short (three paragraph) "Crash course on agent based modeling" [1] from the package docs gave me an idea of why ABM is useful, and scrolling through the example model [2] kinda answers what conveniences the package gives me over implementing the simulation myself.

Has anyone here used ABM for a serious project? Fields like economics and sociology are mentioned, but how prevalent is Agent based modeling in those fields in practice?

[1] https://juliadynamics.github.io/Agents.jl/stable/#Crash-cour...

Are the pieces the agents? I would recommend looking at Collaborative Diffusion for some examples of combining agent-based techniques with game modeling. As for frameworks, check out agentpy or Agents.jl for alternatives that are moreso software libraries that presume knowledge of programming.

I has a look to Julia too. There are nice tools build by JuliaDynamics. I.e. Agents.jl for agent based modeling. It handles collisions. There is also a framework for reinforcement learning. Also for Genetic Algorithms. Then I found a set of libraries related to Geometry. But it seems to be a lot of work to put that together for my use case.

For agent based modelling, you've come to the right place because Agents.jl is great! It has a way to get interactive visualisations from your models, although I haven't used it myself. See this year's JuliaCon talk about Agents.jl to get an idea of what it can do.

I'm always happy to find you have documentation ;). The doc from https://github.com/JuliaDynamics/Agents.jl was pretty helpful to a noob like me.

Here is the issue. Someone already commented saying it's due to a change in InteractiveDynamics.jl and referenced a pull request. I guess all we need to do is wait.