https://github.com/sciml/parallelparticleswarms.jl

GPU accelerated Particle Swarm Optimization
https://github.com/sciml/parallelparticleswarms.jl

Last synced: 5 months ago
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GPU accelerated Particle Swarm Optimization

• Host: GitHub
• URL: https://github.com/sciml/parallelparticleswarms.jl
• Owner: SciML
• License: mit
• Created: 2023-09-25T18:10:56.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2025-07-31T21:57:04.000Z (about 1 year ago)
• Last Synced: 2025-08-29T10:23:27.590Z (11 months ago)
• Language: Julia
• Size: 343 KB
• Stars: 24
• Watchers: 5
• Forks: 3
• Open Issues: 14
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# ParallelParticleSwarms.jl

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Accelerating convex/non-convex optimization with GPUs using Particle-Swarm based methods.

Supports Julia's generic SciML interface.

```julia

using ParallelParticleSwarms, StaticArrays, CUDA

lb = @SArray [-1.0f0, -1.0f0, -1.0f0]

ub = @SArray [10.0f0, 10.0f0, 10.0f0]

function rosenbrock(x, p)

    sum(p[2] * (x[i + 1] - x[i]^2)^2 + (p[1] - x[i])^2 for i in 1:(length(x) - 1))

end

x0 = @SArray zeros(Float32, 3)

p = @SArray Float32[1.0, 100.0]

prob = OptimizationProblem(rosenbrock, x0, p; lb = lb, ub = ub)

sol = solve(prob,

    ParallelSyncPSOKernel(1000, backend = CUDA.CUDABackend()),

    maxiters = 500)

```