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Support for user-defined forcing functions. #85

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merged 5 commits into from
Feb 27, 2019
Merged

Support for user-defined forcing functions. #85

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e94cf92
Fixed call to BoundaryConditions constructor. Resolves #84
ali-ramadhan Feb 26, 2019
f493a7f
Hacky support for user-defined forcing functions.
ali-ramadhan Feb 26, 2019
b38c2b5
Hacked in a user-defined forcing function into the 3D deep convection…
ali-ramadhan Feb 26, 2019
93a89e7
Adds forcing tests and tweaks forcing constructors
glwagner Feb 27, 2019
668eb27
Refactored deep convection 3D example to use ifelse forcing.
ali-ramadhan Feb 27, 2019
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3 changes: 3 additions & 0 deletions src/Oceananigans.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,8 @@ export
OperatorTemporaryFields,
StepperTemporaryFields,

Forcing,

LinearEquationOfState,
ρ!,
δρ!,
Expand Down Expand Up @@ -104,6 +106,7 @@ include("planetary_constants.jl")
include("grids.jl")
include("fields.jl")
include("fieldsets.jl")
include("forcing.jl")

include("operators/operators.jl")

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28 changes: 28 additions & 0 deletions src/forcing.jl
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@@ -0,0 +1,28 @@
struct Forcing{Tu,Tv,Tw,TT,TS}
u::Tu
v::Tv
w::Tw
T::TT
S::TS
end

@inline zero_func(u, v, w, T, S, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) = 0
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Is it slower to write @inline zero_func(args...) = 0? This is less explicit, but does not require maintenance.

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Done.


function Forcing(Tu, Tv, Tw, TT, TS)
if Tu == nothing
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Use === when comparing against nothing

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Done.

Tu = zero_func
end
if Tv == nothing
Tv = zero_func
end
if Tw == nothing
Tw = zero_func
end
if TT == nothing
TT = zero_func
end
if TS == nothing
TS = zero_func
end
Forcing{typeof(Tu),typeof(Tv),typeof(Tw),typeof(TT),typeof(Tu)}(Tu, Tv, Tw, TT, TS)
end
5 changes: 4 additions & 1 deletion src/model.jl
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Expand Up @@ -11,6 +11,7 @@ mutable struct Model
G::SourceTerms
Gp::SourceTerms
forcings::ForcingFields
forcing::Forcing
stepper_tmp::StepperTemporaryFields
operator_tmp::OperatorTemporaryFields
ssp # ::SpectralSolverParameters or ::SpectralSolverParametersGPU
Expand Down Expand Up @@ -38,6 +39,8 @@ function Model(N, L, arch=:cpu, float_type=Float64)
stepper_tmp = StepperTemporaryFields(metadata, grid)
operator_tmp = OperatorTemporaryFields(metadata, grid)

forcing = Forcing(nothing, nothing, nothing, nothing, nothing)

time, time_step, Δt = 0, 0, 0
clock = Clock(time, time_step, Δt)

Expand Down Expand Up @@ -71,6 +74,6 @@ function Model(N, L, arch=:cpu, float_type=Float64)
ρ!(eos, grid, tracers)

Model(metadata, configuration, boundary_conditions, constants, eos, grid,
velocities, tracers, pressures, G, Gp, forcings,
velocities, tracers, pressures, G, Gp, forcings, forcing,
stepper_tmp, operator_tmp, ssp, clock, output_writers, diagnostics)
end
14 changes: 7 additions & 7 deletions src/time_steppers.jl
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Expand Up @@ -63,7 +63,7 @@ function time_step_kernel_cpu!(model::Model, Nt, Δt)
update_source_terms!(Val(:CPU), fCor, χ, eos.ρ₀, cfg.κh, cfg.κv, cfg.𝜈h, cfg.𝜈v, Nx, Ny, Nz, Δx, Δy, Δz,
U.u.data, U.v.data, U.w.data, tr.T.data, tr.S.data, pr.pHY′.data,
G.Gu.data, G.Gv.data, G.Gw.data, G.GT.data, G.GS.data,
Gp.Gu.data, Gp.Gv.data, Gp.Gw.data, Gp.GT.data, Gp.GS.data, F.FT.data)
Gp.Gu.data, Gp.Gv.data, Gp.Gw.data, Gp.GT.data, Gp.GS.data, model.forcing)

calculate_source_term_divergence_cpu!(Val(:CPU), Nx, Ny, Nz, Δx, Δy, Δz, G.Gu.data, G.Gv.data, G.Gw.data, RHS.data)

Expand Down Expand Up @@ -210,7 +210,7 @@ function update_buoyancy!(::Val{Dev}, gΔz, Nx, Ny, Nz, ρ, δρ, T, pHY′, ρ
@synchronize
end

function update_source_terms!(::Val{Dev}, fCor, χ, ρ₀, κh, κv, 𝜈h, 𝜈v, Nx, Ny, Nz, Δx, Δy, Δz, u, v, w, T, S, pHY′, Gu, Gv, Gw, GT, GS, Gpu, Gpv, Gpw, GpT, GpS, FT) where Dev
function update_source_terms!(::Val{Dev}, fCor, χ, ρ₀, κh, κv, 𝜈h, 𝜈v, Nx, Ny, Nz, Δx, Δy, Δz, u, v, w, T, S, pHY′, Gu, Gv, Gw, GT, GS, Gpu, Gpv, Gpw, GpT, GpS, F) where Dev
@setup Dev

@loop for k in (1:Nz; blockIdx().z)
Expand All @@ -222,12 +222,12 @@ function update_source_terms!(::Val{Dev}, fCor, χ, ρ₀, κh, κv, 𝜈h, 𝜈
@inbounds GpT[i, j, k] = GT[i, j, k]
@inbounds GpS[i, j, k] = GS[i, j, k]

@inbounds Gu[i, j, k] = -u∇u(u, v, w, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + fCor*avg_xy(v, Nx, Ny, i, j, k) - δx_c2f(pHY′, Nx, i, j, k) / (Δx * ρ₀) + 𝜈∇²u(u, 𝜈h, 𝜈v, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k)
@inbounds Gv[i, j, k] = -u∇v(u, v, w, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) - fCor*avg_xy(u, Nx, Ny, i, j, k) - δy_c2f(pHY′, Ny, i, j, k) / (Δy * ρ₀) + 𝜈∇²v(v, 𝜈h, 𝜈v, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k)
@inbounds Gw[i, j, k] = -u∇w(u, v, w, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + 𝜈∇²w(w, 𝜈h, 𝜈v, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k)
@inbounds Gu[i, j, k] = -u∇u(u, v, w, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + fCor*avg_xy(v, Nx, Ny, i, j, k) - δx_c2f(pHY′, Nx, i, j, k) / (Δx * ρ₀) + 𝜈∇²u(u, 𝜈h, 𝜈v, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + F.u(u, v, w, T, S, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k)
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What happens if you try to pass grid instead of Nx, Ny, Nz, Δx, Δy, Δz?

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On the GPU it complains that the arguments are not isbitstype :(

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Got it. So both Fields and Grids will have to be worked on.

@inbounds Gv[i, j, k] = -u∇v(u, v, w, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) - fCor*avg_xy(u, Nx, Ny, i, j, k) - δy_c2f(pHY′, Ny, i, j, k) / (Δy * ρ₀) + 𝜈∇²v(v, 𝜈h, 𝜈v, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + F.v(u, v, w, T, S, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k)
@inbounds Gw[i, j, k] = -u∇w(u, v, w, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + 𝜈∇²w(w, 𝜈h, 𝜈v, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + F.w(u, v, w, T, S, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k)

@inbounds GT[i, j, k] = -div_flux(u, v, w, T, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + κ∇²(T, κh, κv, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + FT[i, j, k]
@inbounds GS[i, j, k] = -div_flux(u, v, w, S, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + κ∇²(S, κh, κv, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k)
@inbounds GT[i, j, k] = -div_flux(u, v, w, T, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + κ∇²(T, κh, κv, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + F.T(u, v, w, T, S, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k)
@inbounds GS[i, j, k] = -div_flux(u, v, w, S, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + κ∇²(S, κh, κv, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k) + F.S(u, v, w, T, S, Nx, Ny, Nz, Δx, Δy, Δz, i, j, k)

@inbounds Gu[i, j, k] = (1.5 + χ)*Gu[i, j, k] - (0.5 + χ)*Gpu[i, j, k]
@inbounds Gv[i, j, k] = (1.5 + χ)*Gv[i, j, k] - (0.5 + χ)*Gpv[i, j, k]
Expand Down