Hi, guys. I’ve been working in a nonlinear wave equation solver using finite differences. My code works properly but I’d like to improve the performance, im working on a 12000*39000 grid and the average @btime is 15s. I’m pretty sure that I have been allocating memory unnecessarily. Im pretty new at the topic of performance, I’ve already implemented some of the tips on the performance page.

Here’s my code. Any tip on how to improve the performance would be appreciated.

P.D I’ve noticed that commenting the u=copy(u) line makes code10s faster but whenever I do that u stops updating, I’m sure that it’s due to scope issues but I haven’t found a way around.

```
function NLWaveSolver(I, V, G, L, dt, C, T, DX,bp,np)
##########################################
Nt = Int(round(T / dt))
t = range(0, Nt * dt, length = Nt + 1)
dx = dt / C
Nx = Int(round(2 * L / dx)) + Int(1)
x = range(-L, L, length = Nx)
m=Vector{Float64}[]
sizehint!(m,Nt+1)
C2 = C^2
u_1 = zeros(Nx)
u_2 = zeros(Nx)
u = zeros(Nx)
###############################################################
######################## FIRST STEPS #########################################
@avxt for i = 1:Nx
u_1[i] = I[i]
end
push!(m, u_1)
@avxt for i = 2:Nx-1
u[i] =
u_1[i] * (1.0 - C2) + dt*V[i] + 0.5 * C2 * (u_1[i+1] + u_1[i-1]) -
0.5 * dt^2 * G(u_1[i],bp,np)
end
u[1] = DX[1]
u[Nx] = DX[2]
push!(m, u)
###############################################
##################LOOPS########################
function TXloop(a,b,c)
for j = 2:Nt
c = b
b = a
a=copy(a)
@avxt for i = 2:Nx-1
a[i] =
2.0 * b[i] * (1.0 - C2) + C2 * (b[i+1] + b[i-1]) - c[i] -
dt^2 * G(b[i],bp,np)
end
a[Nx]=c[Nx]-C*(c[Nx]-c[Nx-1])
a[1]=c[1]+C*(c[2]-c[1])
push!(m, a)
end
end
TXloop(u,u_1,u_2)
##############################################
##############################################
xv = range(-L, L, length = length(m[1]))
tv = range(0.0, T, length = length(m))
m2 = zeros(length(m[1]), length(m))
for j in eachindex(m)
@avxt for i in eachindex(m[1])
m2[i, j] = m[j][i]
end
end
return m, tv, x, m2
end
```