Specialize default chunk size on static arrays

[ChrisRackauckas]

Since the size is static and known to be sufficiently small, we might as well directly specialize on it. This does so, and it reduces the allocations and noticeably improves the static array ODE solver speed.

using OrdinaryDiffEq, BenchmarkTools
using StaticArrays, LinearAlgebra

# rober
function rober(u,p,t)
    y₁,y₂,y₃ = u
    k₁,k₂,k₃ = p
    du1 = -k₁*y₁+k₃*y₂*y₃
    du2 =  k₁*y₁-k₂*y₂^2-k₃*y₂*y₃
    du3 =  k₂*y₂^2
    SA[du1,du2,du3]
end
ff = ODEFunction(rober,tgrad = (u,p,t)->SA[0.0,0.0,0.0])
prob = ODEProblem{false}(rober,SA[1.0,0.0,0.0],(0.0,1e5),SA[0.04,3e7,1e4])

# Before
@btime solve(prob,Rodas5(),reltol=1.0e-8,abstol=1.0e-8, saveat = 1000) # 122.500 μs (581 allocations: 53.39 KiB)
# After
@btime solve(prob,Rodas5(),reltol=1.0e-8,abstol=1.0e-8, saveat = 1000) # 101.600 μs (32 allocations: 10.50 KiB)

using ModelingToolkit
prob2 = ODEProblem{false}(modelingtoolkitize(prob),SA[1.0,0.0,0.0],(0.0,1e5),SA[0.04,3e7,1e4],jac=true)
@btime solve(prob2,Rodas5(), reltol=1.0e-8, abstol=1.0e-8, saveat = 1000) # 75.000 μs (401 allocations: 51.38 KiB)

It's still better to modelingtoolkitize, but this is still a nice victory.