CI on ALPS

.buildkite/run_tests.yml

@@ -5,6 +5,7 @@ steps:
         version:
           - "1.10"
           - "1.11"
+          - "1.12-nightly"
     plugins:
       - JuliaCI/julia#v1:
           version: "{{matrix.version}}"
@@ -33,6 +34,7 @@ steps:
         version:
           - "1.10"
           - "1.11"
+          - "1.12-nightly"
     plugins:
       - JuliaCI/julia#v1:
           version: "{{matrix.version}}"

ci/cscs-gh200.yml

@@ -0,0 +1,33 @@
+include:
+  - remote: 'https://gitlab.com/cscs-ci/recipes/-/raw/master/templates/v2/.ci-ext.yml'
+
+unit_test:
+  extends: .uenv-runner-daint-gh200
+  image: julia/25.5:v1
+  script:
+  - julia -e 'println("Instantiating project");
+              using Pkg;
+              Pkg.develop(; path=pwd())'
+  - julia -e 'println("Running tests");
+              using Pkg;
+              Pkg.test("JustPIC"; test_args=["--backend=CUDA"])'
+  variables:
+    WITH_UENV_VIEW: 'juliaup'
+    SLURM_JOB_NUM_NODES: 1
+    SLURM_NTASKS_PER_NODE: 1
+    SLURM_GPUS_PER_TASK: 1
+    SLURM_TIMELIMIT: "00:30:00"
+
+ref_test:
+  extends: .uenv-runner-daint-gh200
+  image: julia/25.5:v1
+  script:
+    - julia --project -e 'using Pkg; Pkg.instantiate()'
+    - julia --project -e 'using Pkg; Pkg.add("CUDA")'
+    - julia --project scripts/single_particle_advection_MPI_ci.jl
+  variables:
+    WITH_UENV_VIEW: 'juliaup'
+    SLURM_JOB_NUM_NODES: 2
+    SLURM_NTASKS_PER_NODE: 4
+    SLURM_GPUS_PER_TASK: 1
+    SLURM_TIMELIMIT: "00:30:00"

scripts/single_particle_advection_MPI_ci.jl

@@ -0,0 +1,163 @@
+using CUDA
+using JustPIC, JustPIC._2D
+
+using ImplicitGlobalGrid
+import MPI
+
+# Threads is the default backend,
+# to run on a CUDA GPU load CUDA.jl (i.e. "using CUDA"),
+# and to run on an AMD GPU load AMDGPU.jl (i.e. "using AMDGPU")
+const backend = CUDABackend # Options: CPUBackend, CUDABackend, AMDGPUBackend
+
+using ParallelStencil
+@init_parallel_stencil(CUDA, Float64, 2)
+
+# using GLMakie
+
+@inline init_particle_fields_cellarrays(particles, ::Val{N}) where {N} = ntuple(_ -> @fill(0.0, size(particles.coords[1])..., celldims = (cellsize(particles.index))), Val(N))
+
+function expand_range(x::AbstractRange)
+    dx = x[2] - x[1]
+    n = length(x)
+    x1, x2 = extrema(x)
+    xI = x1 - dx
+    xF = x2 + dx
+    return LinRange(xI, xF, n + 2)
+end
+
+function expand_range(x::AbstractArray, dx)
+    x1, x2 = extrema(x)
+    xI = x1 - dx
+    xF = x2 + dx
+    return x = TA(vcat(xI, x, xF))
+end
+
+# Analytical flow solution
+vx_stream(x, y) = 250 * sin(π * x) * cos(π * y)
+vy_stream(x, y) = -250 * cos(π * x) * sin(π * y)
+g(x) = Point2f(
+    vx_stream(x[1], x[2]),
+    vy_stream(x[1], x[2])
+)
+
+function main()
+    # Initialize particles -------------------------------
+    nxcell, max_xcell, min_xcell = 24, 24, 18
+    n = 32
+    nx = ny = n - 1
+    me, dims, = init_global_grid(
+        n - 1, n - 1, 0;
+        init_MPI = JustPIC.MPI.Initialized() ? false : true,
+        overlapx = 2, overlapy = 2
+    )
+    Lx = Ly = 1.0
+    dxi = dx, dy = Lx / (nx_g() - 1), Ly / (ny_g() - 1)
+    # nodal vertices
+    xvi = xv, yv = let
+        dummy = zeros(n, n)
+        xv = TA([x_g(i, dx, dummy) for i in axes(dummy, 1)])
+        yv = TA([y_g(i, dx, dummy) for i in axes(dummy, 2)])
+        xv, yv
+    end
+    # nodal centers
+    xci = xc, yc = let
+        dummy = zeros(nx, ny)
+        xc = @zeros(nx)
+        xc .= TA([x_g(i, dx, dummy) for i in axes(dummy, 1)])
+        yc = TA([y_g(i, dx, dummy) for i in axes(dummy, 2)])
+        xc, yc
+    end
+
+    # staggered grid for the velocity components
+    grid_vx = xv, expand_range(yc, dy)
+    grid_vy = expand_range(xc, dx), yv
+
+    particles = init_particle(
+        backend, nxcell, max_xcell, min_xcell, xv, yv, dxi..., nx, ny, me
+    )
+
+    # allocate particle field
+    particle_args = ()
+
+    # Cell fields -------------------------------
+    Vx = TA([vx_stream(x, y) for x in grid_vx[1], y in grid_vx[2]])
+    Vy = TA([vy_stream(x, y) for x in grid_vy[1], y in grid_vy[2]])
+    V = Vx, Vy
+
+    # time step
+    dt = min(dx / maximum(abs.(Vx)), dy / maximum(abs.(Vy)))
+
+    nx_v = (size(particles.coords[1].data, 2)) * dims[1]
+    ny_v = (size(particles.coords[1].data, 3) - 2) * dims[2]
+    px_v = fill(NaN, nx_v, ny_v)
+    py_v = fill(NaN, nx_v, ny_v)
+    index_v = fill(false, nx_v, ny_v)
+    px_nohalo = fill(NaN, size(particles.coords[1].data, 2), size(particles.coords[1].data, 3) - 2)
+    py_nohalo = fill(NaN, size(particles.coords[1].data, 2), size(particles.coords[1].data, 3) - 2)
+    index_nohalo = fill(false, size(particles.coords[1].data, 2), size(particles.coords[1].data, 3) - 2)
+
+    p = [(NaN, NaN)]
+
+    # Advection test
+    niter = 150
+    for iter in 1:niter
+
+        # advect particles
+        advection!(particles, RungeKutta2(2 / 3), V, (grid_vx, grid_vy), dt)
+        # update halos
+        update_cell_halo!(particles.coords..., particle_args...)
+        update_cell_halo!(particles.index)
+
+        # shuffle particles
+        move_particles!(particles, xvi, particle_args)
+
+        # gather particle data - for plotting only
+        @views px_nohalo .= particles.coords[1].data[1, :, 2:(end - 1)]
+        @views py_nohalo .= particles.coords[2].data[1, :, 2:(end - 1)]
+        @views index_nohalo .= particles.index.data[1, :, 2:(end - 1)]
+        gather!(px_nohalo, px_v)
+        gather!(py_nohalo, py_v)
+        gather!(index_nohalo, index_v)
+
+        if me == 0
+            p_i = (px_v[index_v][1], py_v[index_v][1])
+            push!(p, p_i)
+        end
+
+        # if me == 0 && iter % 10 == 0
+        #     w = 0.504
+        #     offset = 0.5 - (w - 0.5)
+        #     f, ax, = lines(
+        #         [0, w, w, 0, 0],
+        #         [0, 0, w, w, 0],
+        #         linewidth = 3
+        #     )
+        #     lines!(
+        #         ax,
+        #         [0, w, w, 0, 0] .+ offset,
+        #         [0, 0, w, w, 0],
+        #         linewidth = 3
+        #     )
+        #     lines!(
+        #         ax,
+        #         [0, w, w, 0, 0] .+ offset,
+        #         [0, 0, w, w, 0] .+ offset,
+        #         linewidth = 3
+        #     )
+        #     lines!(
+        #         ax,
+        #         [0, w, w, 0, 0],
+        #         [0, 0, w, w, 0] .+ offset,
+        #         linewidth = 3
+        #     )
+        #     streamplot!(ax, g, LinRange(0, 1, 100), LinRange(0, 1, 100))
+        #     lines!(ax, p, color = :red)
+        #     scatter!(ax, p[end], color = :black)
+        #     save("figs/trajectory_MPI_$iter.png", f)
+        # end
+    end
+
+    return finalize_global_grid()
+end
+
+main()