# Why so large memory allocations?

**URL:** <https://discourse.julialang.org/t/why-so-large-memory-allocations/75662>\
**Category:** Performance\
**Tags:** memory-allocation\
**Created:** [February 2, 2022, 2:33pm UTC](https://discourse.julialang.org/t/why-so-large-memory-allocations/75662 "2022-02-02T14:33:56Z")\
**Posts on this page:** 7\
**Page:** 1

<div class="post-metadata">

**Author:** ![photor](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/photor/32/14343_2.png) [@photor](https://discourse.julialang.org/u/photor)\
**Post date:** [February 2, 2022, 2:33pm UTC](https://discourse.julialang.org/t/why-so-large-memory-allocations/75662/1 "2022-02-02T14:33:57Z")

</div>

I met a weird problem in the following trivial code:

```julia
using BenchmarkTools

const p=150
dd = randn(p,p)

function d2(ψ::Matrix{Float64})::Matrix{Float64}
    ψr = similar(ψ)
    ddψ = dd*ψ
    @time @inbounds for i in eachindex(ddψ,ψr)
        ψr[i]=ddψ[i]
    end
    return ψr
end

ψ=randn(p,p*p)
@btime d2(ψ);

```

The result is:

```julia
  0.394772 seconds (13.50 M allocations: 257.476 MiB, 4.49% gc time)
  0.396507 seconds (13.50 M allocations: 257.476 MiB, 5.61% gc time)
  0.397738 seconds (13.50 M allocations: 257.476 MiB, 3.80% gc time)
  0.396423 seconds (13.50 M allocations: 257.476 MiB, 4.15% gc time)
  0.430600 seconds (13.50 M allocations: 257.476 MiB, 7.25% gc time)
  0.410795 seconds (13.50 M allocations: 257.476 MiB, 6.39% gc time)
  0.586821 seconds (13.50 M allocations: 257.476 MiB, 26.65% gc time)
  0.486760 seconds (13.50 M allocations: 257.476 MiB, 20.09% gc time)
  0.380750 seconds (13.50 M allocations: 257.476 MiB, 3.97% gc time)
  0.404442 seconds (13.50 M allocations: 257.476 MiB, 5.99% gc time)
  0.402110 seconds (13.50 M allocations: 257.476 MiB, 5.73% gc time)
  0.411570 seconds (13.50 M allocations: 257.476 MiB, 3.88% gc time)
  0.406931 seconds (13.50 M allocations: 257.476 MiB, 6.19% gc time)
  0.404919 seconds (13.50 M allocations: 257.476 MiB, 6.29% gc time)
  0.419291 seconds (13.50 M allocations: 257.476 MiB, 7.73% gc time)
  0.442829 seconds (13.50 M allocations: 257.476 MiB, 9.08% gc time)
  0.456120 seconds (13.50 M allocations: 257.476 MiB, 7.63% gc time)
  0.395785 seconds (13.50 M allocations: 257.476 MiB, 4.61% gc time)
  0.419890 seconds (13.50 M allocations: 257.476 MiB, 3.97% gc time)
  0.405614 seconds (13.50 M allocations: 257.476 MiB, 6.46% gc time)
  0.383479 seconds (13.50 M allocations: 257.476 MiB, 5.23% gc time)
  0.412925 seconds (13.50 M allocations: 257.476 MiB, 6.41% gc time)
  0.410666 seconds (13.50 M allocations: 257.476 MiB, 6.52% gc time)
  0.404238 seconds (13.50 M allocations: 257.476 MiB, 7.23% gc time)
  0.420667 seconds (13.50 M allocations: 257.476 MiB, 6.23% gc time)
  0.420667 seconds (13.50 M allocations: 257.476 MiB, 6.23% gc time)
  0.445725 seconds (13.50 M allocations: 257.476 MiB, 3.58% gc time)
  0.405995 seconds (13.50 M allocations: 257.476 MiB, 6.12% gc time)
  0.413399 seconds (13.50 M allocations: 257.476 MiB, 7.18% gc time)
  415.830 ms (13499133 allocations: 308.99 MiB)

```

So, it’s incredibly slow and the memory allocation is unreasonably large. Why is that? The for loop in the function is expected to have no memory allocation at all.

---

<div class="post-metadata">

**Author:** ![heliosdrm](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/heliosdrm/32/3851_2.png) [@heliosdrm](https://discourse.julialang.org/u/heliosdrm)\
**Post date:** [February 2, 2022, 2:45pm UTC](https://discourse.julialang.org/t/why-so-large-memory-allocations/75662/2 "2022-02-02T14:45:07Z")

</div>

I see a 30x gain by just making `dd` a `const`.

---

<div class="post-metadata">

**Author:** ![nilshg](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nilshg/32/2283_2.png) [@nilshg](https://discourse.julialang.org/u/nilshg)\
**Post date:** [February 2, 2022, 2:49pm UTC](https://discourse.julialang.org/t/why-so-large-memory-allocations/75662/3 "2022-02-02T14:49:57Z")

</div>

Was going to post something very similar - an alternative to `const` is to have `dd` as a function argument (it’s generally not a good idea to have functions depend on global variables):

```julia
julia> function d2(ψ, dd)
           ψr = similar(ψ)
           ddψ = dd*ψ
           @inbounds for i in eachindex(ddψ,ψr)
               ψr[i] = ddψ[i]
           end
           ψr
       end
d2 (generic function with 3 methods)

julia> @btime d2($ψ, $dd);
  29.738 ms (4 allocations: 51.50 MiB)

```

---

<div class="post-metadata">

**Author:** ![lmiq](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lmiq/32/18314_2.png) [@lmiq](https://discourse.julialang.org/u/lmiq)\
**Post date:** [February 2, 2022, 2:55pm UTC](https://discourse.julialang.org/t/why-so-large-memory-allocations/75662/4 "2022-02-02T14:55:28Z")

</div>

See: [Performance Tips · The Julia Language](https://docs.julialang.org/en/v1/manual/performance-tips/)

---

<div class="post-metadata">

**Author:** ![photor](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/photor/32/14343_2.png) [@photor](https://discourse.julialang.org/u/photor)\
**Post date:** [February 3, 2022, 1:47am UTC](https://discourse.julialang.org/t/why-so-large-memory-allocations/75662/5 "2022-02-03T01:47:15Z")

</div>

Yes, you are right, 30x gain and no memory allocation by just making dd a const. Just curious, why the heavy consumption occurs in the for loop instead of the step “ddψ = dd\*ψ”? The for loop seems to have no direct relation to dd.

---

<div class="post-metadata">

**Author:** ![xzackli](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/xzackli/32/38301_2.png) [@xzackli](https://discourse.julialang.org/u/xzackli)\
**Post date:** [February 3, 2022, 2:25am UTC](https://discourse.julialang.org/t/why-so-large-memory-allocations/75662/6 "2022-02-03T02:25:49Z")

</div>

In Julia, type specialization (the secret sauce that makes it faster than Python but still dynamic) occurs at function calls. Nothing at compilation time can be inferred about the type of `ddψ` since it depends on a non-constant global. The for-loop can’t regain knowledge of the type, since it lives in the same function as when disaster struck.

Things would be different if the for-loop was in its own function (see [this part](https://docs.julialang.org/en/v1/manual/performance-tips/#kernel-functions) of the performance tips).

---

<div class="post-metadata">

**Author:** ![photor](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/photor/32/14343_2.png) [@photor](https://discourse.julialang.org/u/photor)\
**Post date:** [February 3, 2022, 2:58am UTC](https://discourse.julialang.org/t/why-so-large-memory-allocations/75662/7 "2022-02-03T02:58:36Z")

</div>

Thanks!