How to speed up these functions?

General Usage Performance
19

I’m getting some puzzling results. Consider this:

using LoopVectorization

t = [26, 94]
c = [26, 94]
x = collect([25 12]')

α = 2.85
β = [-13.3, -0.006]

function logℒ_fast(α, β, t, c, x)
    eα = abs(α)
    n, k = size(x)
  
    (n == length(t) == length(c) && length(β) == k + 1) || throw(DimensionMismatch())
    s = zero(typeof(α))
    @inbounds for i in 1:n
      xb = sum(@inbounds(x[i, j] * β[j+1]) for j in 1:k) + β[1]
      ti = t[i]
      s += (1 - (c[i] == ti)) * (log(eα) + (eα - 1) * log(ti) + xb) - ti^eα * exp(xb)
    end
    return s
end

function logℒ_fast_turbo(α, β, t, c, x)
    eα = abs(α)
    n, k = size(x)
  
    (n == length(t) == length(c) && length(β) == k + 1) || throw(DimensionMismatch())
    s = zero(typeof(α))
    @turbo for i in 1:n
      xb0 = 0.0
      for j in 1:k
        xb0 += x[i,j] * β[j+1]
      end
      xb = xb0 + β[1]
      ti = t[i]
      s += (1 - (c[i] == ti)) * (log(eα) + (eα - 1) * log(ti) + xb) - ti^eα * exp(xb)
    end
    return s
end

Those are the same functions you defined above, however:

julia> logℒ_fast_turbo(α, β, t, c, x)
NaN

julia> logℒ_fast(α, β, t, c, x)
-0.6702178908853803

I can’t figure out what’s going on here.

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