# Threads memory allocations

**URL:** https://discourse.julialang.org/t/threads-memory-allocations/33675
**Category:** General Usage
**Created:** [January 22, 2020, 8:07pm UTC](https://discourse.julialang.org/t/threads-memory-allocations/33675 "2020-01-22T20:07:13Z")
**Posts on this page:** 3
**Page:** 1

<div class="post-metadata">

### Author: ![squirrel](https://avatars.discourse-cdn.com/v4/letter/s/96bed5/32.png) [@squirrel](https://discourse.julialang.org/u/squirrel)
#### Post date: [January 22, 2020, 8:07pm UTC](https://discourse.julialang.org/t/threads-memory-allocations/33675/1 "2020-01-22T20:07:13Z")

</div>

Hi. I’m really trying to understand parallel programming in Julia. Can someone please explain to me why using threads requires so many memory allocations?

```julia
using BenchmarkTools
using .Threads

function test_serial(u)
    for i in eachindex(u)
        u[i] = threadid()
    end
end

function test_threads(u)
    @threads for i in eachindex(u)
        u[i] = threadid()
    end
end

u = zeros(Int64, 1000)

```

```julia
julia> @benchmark test_serial($u)
BenchmarkTools.Trial:
  memory estimate: 0 bytes
  allocs estimate: 0
  --------------
  minimum time: 336.647 ns (0.00% GC)
  median time: 347.059 ns (0.00% GC)
  mean time: 373.924 ns (0.00% GC)
  maximum time: 922.167 ns (0.00% GC)
  --------------
  samples: 10000
  evals/sample: 221

julia> @benchmark test_threads($u)
BenchmarkTools.Trial:
  memory estimate: 2.72 KiB
  allocs estimate: 29
  --------------
  minimum time: 8.099 μs (0.00% GC)
  median time: 9.700 μs (0.00% GC)
  mean time: 10.360 μs (0.00% GC)
  maximum time: 136.400 μs (0.00% GC)
  --------------
  samples: 10000
  evals/sample: 1

```

---

<div class="post-metadata">

### Author: ![affans](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/affans/32/11911_2.png) [@affans](https://discourse.julialang.org/u/affans)
#### Post date: [January 22, 2020, 8:55pm UTC](https://discourse.julialang.org/t/threads-memory-allocations/33675/2 "2020-01-22T20:55:22Z")

</div>

I am not sure if that’s “so many allocations”, but as far as I know, this is just the overhead of using the parallel threading library.

---

<div class="post-metadata">

### Author: ![pbayer](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/pbayer/32/11675_2.png) [@pbayer](https://discourse.julialang.org/u/pbayer)
#### Post date: [January 22, 2020, 9:03pm UTC](https://discourse.julialang.org/t/threads-memory-allocations/33675/3 "2020-01-22T21:03:43Z")

</div>

The `for` loop allocates tasks and fetches the result, thus it essentially it reduces to:

```julia
julia> @benchmark threadid()
BenchmarkTools.Trial: 
  memory estimate: 0 bytes
  allocs estimate: 0
  --------------
  minimum time: 4.150 ns (0.00% GC)
  median time: 4.282 ns (0.00% GC)
  mean time: 4.453 ns (0.00% GC)
  maximum time: 37.888 ns (0.00% GC)
  --------------
  samples: 10000
  evals/sample: 1000

```

vs

```julia
@benchmark ((t = @async threadid()); fetch(t))
BenchmarkTools.Trial: 
  memory estimate: 704 bytes
  allocs estimate: 7
  --------------
  minimum time: 14.258 μs (0.00% GC)
  median time: 16.535 μs (0.00% GC)
  mean time: 18.000 μs (0.00% GC)
  maximum time: 97.452 μs (0.00% GC)
  --------------
  samples: 10000
  evals/sample: 1

```

times your threads for the memory estimate