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Copy pathdiffusion_2D_damp_perf_xpu.jl
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diffusion_2D_damp_perf_xpu.jl
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# 2D nonlinear diffusion XPU implicit solver with acceleration
const USE_GPU = true
using ParallelStencil
using ParallelStencil.FiniteDifferences2D
@static if USE_GPU
@init_parallel_stencil(CUDA, Float64, 2)
else
@init_parallel_stencil(Threads, Float64, 2)
end
using Plots, Printf, LinearAlgebra
# enable plotting by default
if !@isdefined do_visu; do_visu = false end
# macros to avoid array allocation
macro qHx(ix,iy) esc(:( -(0.5*(H[$ix,$iy+1]+H[$ix+1,$iy+1]))*(0.5*(H[$ix,$iy+1]+H[$ix+1,$iy+1]))*(0.5*(H[$ix,$iy+1]+H[$ix+1,$iy+1])) * (H[$ix+1,$iy+1]-H[$ix,$iy+1])*_dx )) end
macro qHy(ix,iy) esc(:( -(0.5*(H[$ix+1,$iy]+H[$ix+1,$iy+1]))*(0.5*(H[$ix+1,$iy]+H[$ix+1,$iy+1]))*(0.5*(H[$ix+1,$iy]+H[$ix+1,$iy+1])) * (H[$ix+1,$iy+1]-H[$ix+1,$iy])*_dy )) end
macro dtau(ix,iy) esc(:( (1.0/(min_dxy2 / (H[$ix+1,$iy+1]*H[$ix+1,$iy+1]*H[$ix+1,$iy+1]) / 4.1) + _dt)^-1 )) end
@parallel_indices (ix,iy) function compute_update!(H2, dHdtau, H, Hold, _dt, damp, min_dxy2, _dx, _dy)
if (ix<=size(dHdtau,1) && iy<=size(dHdtau,2))
dHdtau[ix,iy] = -(H[ix+1, iy+1] - Hold[ix+1, iy+1])*_dt +
(-(@qHx(ix+1,iy)-@qHx(ix,iy))*_dx -(@qHy(ix,iy+1)-@qHy(ix,iy))*_dy) +
damp*dHdtau[ix,iy] # damped rate of change
H2[ix+1,iy+1] = H[ix+1,iy+1] + @dtau(ix,iy)*dHdtau[ix,iy] # update rule, sets the BC implicitly as H[1]=H[end]=0
end
return
end
@parallel_indices (ix,iy) function compute_residual!(ResH, H, Hold, _dt, _dx, _dy)
if (ix<=size(ResH,1) && iy<=size(ResH,2))
ResH[ix,iy] = -(H[ix+1, iy+1] - Hold[ix+1, iy+1])*_dt +
(-(@qHx(ix+1,iy)-@qHx(ix,iy))*_dx -(@qHy(ix,iy+1)-@qHy(ix,iy))*_dy)
end
return
end
@parallel_indices (ix,iy) function assign!(Hold, H)
if (ix<=size(H,1) && iy<=size(H,2)) Hold[ix,iy] = H[ix,iy] end
return
end
@views function diffusion_2D_damp_perf_xpu(; do_visu=true, save_fig=false)
# Physics
lx, ly = 10.0, 10.0 # domain size
ttot = 1.0 # total simulation time
dt = 0.2 # physical time step
# Numerics
nx, ny = 16*32*16, 16*32*16 # number of grid points
# nx, ny = 512, 512 # numerical grid resolution
nout = 100 # check error every nout
tol = 1e-6 # tolerance
itMax = 1e5 # max number of iterations
damp = 1-35/nx # damping (this is a tuning parameter, dependent on e.g. grid resolution)
# Derived numerics
dx, dy = lx/nx, ly/ny # grid size
xc, yc = LinRange(dx/2, lx-dx/2, nx), LinRange(dy/2, ly-dy/2, ny)
# Array allocation
ResH = @zeros(nx-2, ny-2) # normal grid, without boundary points
dHdtau = @zeros(nx-2, ny-2) # normal grid, without boundary points
# Initial condition
H = Data.Array(exp.(.-(xc.-lx/2).^2 .-(yc.-ly/2)'.^2))
Hold = copy(H)
H2 = copy(H)
_dx, _dy, _dt = 1.0/dx, 1.0/dy, 1.0/dt
min_dxy2 = min(dx,dy)^2
t = 0.0; it = 0; ittot = 0; t_tic = 0.0; niter = 0
# Physical time loop
while t<ttot
iter = 0; err = 2*tol
# Picard-type iteration
while err>tol && iter<itMax
if (it==1 && iter==0) t_tic = Base.time(); niter = 0 end
@parallel compute_update!(H2, dHdtau, H, Hold, _dt, damp, min_dxy2, _dx, _dy)
H, H2 = H2, H
if iter % nout == 0
@parallel compute_residual!(ResH, H, Hold, _dt, _dx, _dy)
err = norm(ResH)/length(ResH)
end
iter += 1; niter += 1
end
ittot += iter; it += 1; t += dt
@parallel assign!(Hold, H)
end
t_toc = Base.time() - t_tic
A_eff = (2*2+1)/1e9*nx*ny*sizeof(Data.Number) # Effective main memory access per iteration [GB]
t_it = t_toc/niter # Execution time per iteration [s]
T_eff = A_eff/t_it # Effective memory throughput [GB/s]
@printf("Time = %1.3f sec, T_eff = %1.2f GB/s (niter = %d)\n", t_toc, round(T_eff, sigdigits=2), niter)
# Visualize
if do_visu
fontsize = 12
opts = (aspect_ratio=1, yaxis=font(fontsize, "Courier"), xaxis=font(fontsize, "Courier"),
ticks=nothing, framestyle=:box, titlefontsize=fontsize, titlefont="Courier", colorbar_title="",
xlabel="Lx", ylabel="Ly", xlims=(xc[1],xc[end]), ylims=(yc[1],yc[end]), clims=(0.,1.))
display(heatmap(xc, yc, Array(H)'; c=:davos, title="damped diffusion (nt=$it, iters=$ittot)", opts...))
if save_fig savefig("diff2D_damp.png") end
end
return
end
diffusion_2D_damp_perf_xpu(; do_visu=do_visu)