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ParallelParticleSwarms.jl

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GPU accelerated Particle Swarm Optimization

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# 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)
```

ParallelParticleSwarms.jl

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