mixed prec on tendencies not sum of tend

Author: milankl

src/Continuity.jl

@@ -62,7 +62,7 @@ function continuity_itself!(Diag::DiagnosticVars{T,Tprog},
 
     @inbounds for j ∈ 1:n
         for i ∈ 1:m
-            dη[i+1,j+1] = -(Tprog(dUdx[i,j+1] + dVdy[i+1,j]))
+            dη[i+1,j+1] = -(Tprog(dUdx[i,j+1]) + Tprog(dVdy[i+1,j]))
         end
     end
 end

src/Diffusion.jl

@@ -234,7 +234,7 @@ function add_drag_diff_tendencies!( u::Array{Tprog,2},
 
     @inbounds for j ∈ 1:n
         for i ∈ 1:m
-            u[i+2,j+2] += Δt_diff*(Tprog(Bu[i+1-ep,j+1] + LLu1[i,j+1] + LLu2[i+1-ep,j]))
+            u[i+2,j+2] += Δt_diff*(Tprog(Bu[i+1-ep,j+1]) + Tprog(LLu1[i,j+1]) + Tprog(LLu2[i+1-ep,j]))
         end
     end
 
@@ -245,7 +245,7 @@ function add_drag_diff_tendencies!( u::Array{Tprog,2},
 
     @inbounds for j ∈ 1:n
         for i ∈ 1:m
-             v[i+2,j+2] += Δt_diff*(Tprog(Bv[i+1,j+1] + LLv1[i,j+1] + LLv2[i+1,j]))
+             v[i+2,j+2] += Δt_diff*(Tprog(Bv[i+1,j+1]) + Tprog(LLv1[i,j+1]) + Tprog(LLv2[i+1,j]))
         end
     end
 end

src/TestJuls.jl

@@ -1,3 +1,13 @@
 include("Juls.jl")
 using .Juls
-RunJuls()
+using BFloat16s
+
+Base.round(x::BFloat16, r::RoundingMode{:Up}) = BFloat16(ceil(Float32(x)))
+Base.round(x::BFloat16, r::RoundingMode{:Down}) = BFloat16(floor(Float32(x)))
+Base.round(x::BFloat16, r::RoundingMode{:Nearest}) = BFloat16(round(Float32(x)))
+
+a = BFloat16(1.2)
+floor(a)
+
+#RunJuls(BFloat16,Tprog=Float32)
+#RunJuls(BFloat16,Tprog=Float32,output=true,nx=200,Ndays=100,initial_cond="ncfile",sst_initial="rect",sst_rect_coords=[0.,0.5,0.,1.0],outpath="/local/home/kloewer/julsdata/mixedprec")

src/rhs.jl

@@ -296,7 +296,7 @@ function momentum_u!(Diag::DiagnosticVars{T,Tprog},S::ModelSetup) where {T,Tprog
 
     @inbounds for j ∈ 1:n
         for i ∈ 1:m
-            du[i+2,j+2] = Tprog(qhv[i,j] - dpdx[i+1-ep,j+1] + Fx[i,j])
+            du[i+2,j+2] = Tprog(qhv[i,j]) - Tprog(dpdx[i+1-ep,j+1]) + Tprog(Fx[i,j])
         end
     end
 end
@@ -316,7 +316,7 @@ function momentum_v!(Diag::DiagnosticVars{T,Tprog},S::ModelSetup) where {T,Tprog
 
     @inbounds for j ∈ 1:n
         for i ∈ 1:m
-             dv[i+2,j+2] = Tprog(-qhu[i,j] - dpdy[i+1,j+1] + Fy[i,j])
+             dv[i+2,j+2] = -Tprog(qhu[i,j]) - Tprog(dpdy[i+1,j+1]) + Tprog(Fy[i,j])
         end
     end
 end