GPU Ensemble tracing

This example demonstrates the usage of GPU for ensemble tracing. Since GitHub Actions do not have GPU runners for now, we do not show the results on page.

using TestParticle
using DiffEqGPU, OrdinaryDiffEq, CUDA, StaticArrays
using CairoMakie

"Set initial state for EnsembleProblem."
function prob_func(prob, i, repeat)
   prob = @views remake(prob, u0=[prob.u0[1:3]..., i/3, 0.0, 0.0])
end

## Initialization

B(x) = SA[0, 0, 1e-11]
E(x) = SA[0, 0, 1e-13]

x0 = [0.0, 0.0, 0.0] # initial position, [m]
u0 = [1.0, 0.0, 0.0] # initial velocity, [m/s]
stateinit = [x0..., u0...]

param = prepare(E, B, species=Electron)
tspan = (0.0, 10.0)

trajectories = 3

## Solve for the trajectories

prob = ODEProblem(trace!, stateinit, tspan, param)
ensemble_prob = EnsembleProblem(prob; prob_func, safetycopy=false)
sols = solve(ensemble_prob, Tsit5(), EnsembleGPUArray(CUDA.CUDABackend()); trajectories)

## Visualization

f = Figure(fontsize = 18)
ax = Axis3(f[1, 1],
   title = "Electron trajectories",
   xlabel = "X",
   ylabel = "Y",
   zlabel = "Z",
   aspect = :data,
)

for i in eachindex(sols)
   lines!(ax, sols[i], idxs=(1,2,3), label="$i", color=Makie.wong_colors()[i])
end

f

While EnsembleGPUArray has a bit of overhead due to its form of GPU code construction, EnsembleGPUKernel is a more restrictive GPU-itizing algorithm that achieves a much lower overhead in kernel launching costs. However, it requires this problem to be written in out-of-place form and use special solvers. Additionally, a timestep dt or saveat keyword is required for dense outputs.

using TestParticle
using DiffEqGPU, OrdinaryDiffEq, CUDA, StaticArrays
using CairoMakie

"Set initial state for EnsembleProblem."
function prob_func(prob, i, repeat)
   prob = @views remake(prob, u0=SA[prob.u0[1:3]..., i/3, 0.0, 0.0])
end

## Initialization

B(x) = SA[0, 0, 1e-11]
E(x) = SA[0, 0, 1e-13]

x0 = SA[0.0, 0.0, 0.0] # initial position, [m]
u0 = SA[1.0, 0.0, 0.0] # initial velocity, [m/s]
stateinit = SA[x0..., u0...]

param = prepare(E, B, species=Electron)
tspan = (0.0, 10.0)

trajectories = 3

## Solve for the trajectories

prob = ODEProblem(trace, stateinit, tspan, param)
ensemble_prob = EnsembleProblem(prob; prob_func, safetycopy=false)
## saving time interval is required for dense output! 
sols = solve(ensemble_prob, GPUTsit5(), EnsembleGPUKernel(CUDA.CUDABackend());
   trajectories, saveat=0.4)

## Visualization

f = Figure(fontsize = 18)
ax = Axis3(f[1, 1],
   title = "Electron trajectories",
   xlabel = "X",
   ylabel = "Y",
   zlabel = "Z",
   aspect = :data,
)

for i in eachindex(sols)
   lines!(ax, sols[i], idxs=(1,2,3), label="$i", color=Makie.wong_colors()[i])
end

f

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