Sums with multiple terms
Would it be possible to take advantage of sums with many terms, so that x + y + z becomes logsumexp([x,y,z]) as opposed to logaddexp(x, logaddexp(y, z)) ?
I just tried a small benchmark and it does look a bit faster:
julia> using LogarithmicNumbers, BenchmarkTools
julia> function mysum(a::AbstractVector{ULogarithmic{T}}) where {T}
m = typemin(T)
se = zero(T)
for x in a
if x.log < m
se += exp(x.log - m)
elseif x.log == m
se += one(T)
else
se = muladd(se, exp(m - x.log), one(T))
m = x.log
end
end
lse = m + log(se)
return exp(ULogarithmic, lse)
end;
julia> a = exp.(ULogarithmic, rand(1_000));
julia> @btime sum($a)
29.931 μs (0 allocations: 0 bytes)
exp(7.446988417750581)
julia> @btime mysum($a)
4.841 μs (0 allocations: 0 bytes)
exp(7.446988417750575)
My implementation of logsumexp is from https://www.nowozin.net/sebastian/blog/streaming-log-sum-exp-computation.html. I think we better not use LogExpFunctions.jl because
- it has several unwanted dependencies
- it wouldn't access the
x.logeasily
Cool! How does the benchmark compare when the array has two elements? I'm just wondering if your version is essentially a faster +. I haven't looked at my + for a while but AFAIR it has a lot of branching to deal with special cases (NaN, Inf, 0).
For two elements my version is slightly worse, and also probably less numerically stable
julia> using UnicodePlots
julia> n_vals = vcat(2, 10 .^ (1:7));
julia> current_implem = zeros(length(n_vals));
julia> my_implem = zeros(length(n_vals));
julia> for (k, n) in enumerate(n_vals)
a = exp.(ULogarithmic, rand(n))
current_implem[k] = @belapsed sum($a)
my_implem[k] = @belapsed mysum($a)
end
julia> lineplot(
log10.(n_vals),
current_implem ./ my_implem;
xlabel="log array size", ylabel="perf gain"
)
┌────────────────────────────────────────┐
7 │⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⡀⠀⠀⠀⠀⠀│
│⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠒⠉⠉⠉⠉⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠉⠉⠒⠒⠢│
│⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⠀⠀⠀⠀⠀⢀⠜⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⠀⠀⠀⠀⢰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⠀⠀⠀⢀⠇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
perf gain │⠀⠀⠀⠀⡸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⠀⠀⢀⠇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⠀⠀⡸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⠀⢀⠇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⠀⡸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⢠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⠈⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
0 │⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
└────────────────────────────────────────┘
⠀0⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀7⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀log array size⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
Bumping this, any interest in a PR?
Sure, what would the PR be? A new sum function?
Yeah probably, but I don't know how to make it général enough to accept arbitrary iterators yet still find a workable eltype