使用Julia中的StaticArrays.jl进行性能分配和复制

Question

我曾考虑使用StaticArrays.jl包来增强代码的性能。然而，我只使用数组来存储计算的变量，并在设置了某些条件后再使用它们。因此，我将SizedVector类型与普通向量进行比较，但我不理解下面的代码。我还尝试了StaticVector，并使用了围绕Setfield.jl.的工作

using StaticArrays, BenchmarkTools, Setfield
function copySized(n::Int64)
v = SizedVector{n, Int64}(zeros(n))
w = Vector{Int64}(undef, n)
for i in eachindex(v)
v[i] = i
end
for i in eachindex(v)
w[i] = v[i]
end
end
function copyStatic(n::Int64)
v = @SVector zeros(n)
w = Vector{Int64}(undef, n)
for i in eachindex(v)
@set v[i] = i
end
for i in eachindex(v)
w[i] = v[i]
end
end
function copynormal(n::Int64)
v = zeros(n)
w = Vector{Int64}(undef, n)
for i in eachindex(v)
v[i] = i
end
for i in eachindex(v)
w[i] = v[i]
end
end
n = 10
@btime copySized($n)
@btime copyStatic($n)
@btime copynormal($n)
3.950 μs (42 allocations: 2.08 KiB)
5.417 μs (98 allocations: 4.64 KiB) 
78.822 ns (2 allocations: 288 bytes)

为什么SizedVector的情况确实有更多的分配，因此性能更差？我没有正确使用SizedVector吗？它是否应该至少具有与普通阵列相同的性能？

提前谢谢。

Julia话语的交叉帖子

Answer 1

我觉得这是苹果和桔子的比较(大小应该静态存储在类型中(。更具说明性的代码可能是这样的：

function copySized(::Val{n}) where n
v = SizedVector{n}(1:n)
w = Vector{Int64}(undef, n)
w .= v
end
function copyStatic(::Val{n}) where n
v =  SVector{n}(1:n)
w = Vector{Int64}(undef, n)
w .= v
end
function copynormal(n) 
v = [1:n;]
w = Vector{Int64}(undef, n)
w .= v
end

现在基准：

julia> n = 10
10
julia> @btime copySized(Val{$n}());
248.138 ns (1 allocation: 144 bytes)
julia> @btime copyStatic(Val{$n}());
251.507 ns (1 allocation: 144 bytes)
julia> @btime copynormal($n);
77.940 ns (2 allocations: 288 bytes)
julia>
julia>
julia> n = 1000
1000
julia> @btime copySized(Val{$n}());
840.000 ns (2 allocations: 7.95 KiB)
julia> @btime copyStatic(Val{$n}());
830.769 ns (2 allocations: 7.95 KiB)
julia> @btime copynormal($n);
1.100 μs (2 allocations: 15.88 KiB)

Answer 2

@phipsgabler是对的！当在编译时静态地知道大小时，静态大小的数组具有性能优势。然而，我的数组是动态调整大小的，其中大小n是一个运行时变量。

改变这一点会产生更明智的结果：

using StaticArrays, BenchmarkTools, Setfield
function copySized()
v = SizedVector{10, Float64}(zeros(10))
w = Vector{Float64}(undef, 10*2)
for i in eachindex(v)
v[i] = rand()
end
for i in eachindex(v)
j = i+floor(Int64, 10/4)
w[j] = v[i]
end
end
function copyStatic()
v = @SVector zeros(10)
w = Vector{Int64}(undef, 10*2)
for i in eachindex(v)
@set v[i] = rand()
end
for i in eachindex(v)
j = i+floor(Int64, 10/4)
w[j] = v[i]
end
end
function copynormal()
v = zeros(10)
w = Vector{Float64}(undef, 10*2)
for i in eachindex(v)
v[i] = rand()
end
for i in eachindex(v)
j = i+floor(Int64, 10/4)
w[j] = v[i]
end
end
@btime copySized()
@btime copyStatic()
@btime copynormal()
110.162 ns (3 allocations: 512 bytes)
48.133 ns (1 allocation: 224 bytes)
92.045 ns (2 allocations: 368 bytes)